dipl. ing. eth
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Research Collection
Doctoral Thesis
A methodology for evaluating the metabolism in the large scaleintroduction of renewable energy systems
Author(s): Real, Markus Georg
Publication Date: 1998
Permanent Link: https://doi.org/10.3929/ethz-a-002030296
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ETH Library
Diss.ETH 12937
A methodology for evaluating the metabolism in the largescale introduction of renewable energy Systems
A dissertation submitted to the
SWISS FEDERAL INSTITUTE OF TECHNOLOGY ZÜRICH
for the degree of
Doctor of Technical Sciences
presented by:
Markus Georg Real
Dipl. Ing. ETH
born 10.9.1949
Citizen of Schwyz (SZ)
accepted on the recommendation of:
Prof. Dr. P. Baccini, examiner
Prof. Dr. P. Suter, co-examiner
Dr. H.P. Bader, co-examiner
10. Oktober 1998
Contents
Zusammenfassung
Summary
1. Introduction
Acknowledgements
2. Methodology
2 1 System analysis2 1 1 Requirements for the methodology2 1 2 System configuration2 12 1 PV Subsystems2 12 2 Energy distnbution Subsystems2 123 Glass Subsystems2 1 3 System boundary2 1 4 Indicators
2 1 5 Detailed System layout
2 2 Mathematical description22 1 Material fluxes and Stocks
22 2 Energy fluxes and Stocks
2 3 System equations - model assumptions2 3 1 Material fluxes and Stocks
2 311 Intrmsic equations2 3 12 Balance equations23 12 Model equations23 2 Energy fluxes
2 3 2 1 Intrmsic equations23 2 2 Balance equations2 3 2 2 Model equations2 3 3 Detailed description of selected key processes
2 3 3 1 The process "PV plant"23 3 2 The process "solar cell production"2 3 3 3 The process "balance of System components"2 3 3 4 The process "electrical distnbution
"
24 Model calibration
24 1 Growth model
24 2 Calibration of the part with the material assumption24 3 Calibration of the part with the energy assumption2 4 4 Detailed description of selected Parameter functions
244 1 The Potential of PV plants in Switzerland
244 2 Material and energy flux for BOS components24 4 3 Material and energy flux of the phofon absorbing laye24 5 Electrical energy inputs2 4 5 1 Electncity from hydro2 4 5 2 Electncity from biomass
24 5 3 Electncity from wind
24 54 Electncity from nuclear
24 5 5 Electncity from cogeneration
l
welcher der energetische "Break even" erreicht wird Der Brüterfaktor Ist ein Begriff der
ursprunglich bei nuklearen Brüterreaktoren eingeführt wurde Der Brüterfaktor ist ein
Mass dafür, wieviel mal mehr elektrische Energie die Kraftwerke produzieren im
Verhältnis zum Investment an elektrischer Energie, um die Anlagen zu realisieren Der
Bruterfaktor für Kraftwerke, die mit emeuerbarer Solarenergie betrieben werden Ist
damit insbesondere auch eine Messgrösse im Zusammenhang mit dem Begriffnachhaltiger Entwicklung Ein Brüterfaktor von 1 würde bedeuten, dass die Anlagen
gleich viel Strom produzieren wie zum Bau des Kraftwerkes benötigt wird Die Anlagenwurden zwar wohl mit erneuerbarer Sonnenenergie betrieben, aber die nutzbare
Energie wäre damit noch nicht nachhaltig Der hier definierte Bruterfaktor ist eine
dynamische Grösse und unterscheidet sich vom oft zitierten Erntefaktor, der als
statische Grösse das Verhältnis von Output zu Input berechnet Eine starre Definition
wie gross der Brüterfaktor sein muss, um der Anforderung einer nachhaltigen
Entwicklung zu genügen, konnte auch im Rahmen dieser Arbeit nicht gefundenwerden Dagegen erlaubt die vorgestellte Methode der dynamischen Simulation den
Zusammenhang zwischen den induzierten Material- und Energleflussen zu erkennen
und die Option in einem gesamten Kontext beurteilen zu können
Zudem beschränkt sich der Brüterfaktor auf den Vergleich der elektrischen Grössen Er
ist damit unabhängig vom Einfluss derzufällig gewählten Systemgrenzen, wie sie etwa
bei der Diskussion der Erntefaktoren oft geführt wird Der fossile Input wird als Investment
einer nicht erneuerbaren Resource aufgefasst Die Analyse konzentriert sich dabei auf
die Fragen ob dieser Input nicht erneuerbarer Resource zu rechtfertigen ist
• Wie gross ist die elektrische Energieproduktion in photovoltaischen Solarkraft¬
werken im Verhältniss zum Ertrag, wenn der gleich grosse Einsatz an fossiler Mengein konventionellen Kraftwerken verströmt wird und
• wie steht der für die Erstellung der Solarkraftwerke notwendige Input im Verhältnis
zum übrigen Verzehr dieses Rohstoffes? Handelt es sich um einen signifikantenAnteil oder allenfalls um eine vernachlässigbare Grösse?
Dazu wurden die elektrischen und fossilen Energieflüsse getrennt simuliert Beim Inputfossile Energie" handelt es sich im wesentlichen um nicht energetischen Einsatz wie
Herstellung von Polymeren etc Der energetische Wert dieses Inputs wird gewertetindem man den Input von fossiler Energie in ein PV System mit der Menge Elektrizität
vergleicht, die man bei der direkten Umsetzung in Blockheizkraftwerken erreichen
könnte Mit dem Quotienten wird der "fossile Multiplikationsfaktor" definiert Er hegt für
alle gerechneten Variationen über 20, Das bedeutet, das sich die Investition fossiler
Energie in ein PV Szenario mindestens 20 mal mehr lohnt, als wenn die gleiche Mengefossiler Input direkt verströmt würde Für die Annahme einer mittleren Lebensdauer von
30 Jahren liegt dieser Wert sogar bei etwa 30
Resultate bezüglich dem Material-, und insbesondere aber auch dem
Energiehaushalt variieren sehr stark für die drei verschiedenen PV TechnologienDabei sind sowohl Brüterfaktoren wie auch die fossilen Multiphkationsfaktoren für alle
drei Technologien gross genug, um eine grossmassstäbllche Umsetzung zu
rechtfertigen Einzig für die waferorientierte PV Technologie gibt es aufgrund der
Sensltlvitätsanalyse Vorbehalte, wenn die Lebensdauer nur 20 statt deren 30 Jahre
beträgt und wenn die Umsetzung innerhalb einer statt wie in der Grundvariante
angenommen zweier Generationen erfolgen soll Im ersten Fall sinkt der Brüterwert auf
den Faktor von rund 6, im zweiten Fall ergeben sich doch erhebliche Guterflusse
während der grössten Wachstumsphase insbesondere für Glas und für hochreines
Silizium Für die übrigen Variationen ergeben sich aufgrund der Simulationen
längerfristig Brüterfaktoren zwischen 10 und 60 was bedeutet dass die PV
2
Technologien auch Im Schweizer Klima mehr als genügend Energie erzeugen, um
sich selber zu reproduzieren und Überschussenergie an das Netz abzugeben.
Der Wechsel 'm Richtung einer nachhaltigen Stromversorgung, die auf erneuerbaren
Energiequellen basiert, wurde anhand des schweizerischen Stromnetzes demonstriert.
Werden die Kernkraftwerke In der Schweiz nach Ihrer 43 jahrigen Lebensdauer nicht
ersetzt, ergibt sich zwischen 2010 und 2025 eine Produktionseinbusse, die kaum
rechtzeitig und vollumfänglich von erneuerbaren Energieträgern gedeckt werden
kann, wobei in dieser Studie nicht auf das Sparpotential auf der Verbraucherseite
eingegangen wurde, das durch verbesserte Energieeffizienz ausschöpfbar wäre. Ein
auf etwa drei Jahrzehnte befristeter Ausbau der Btockheizkraftwerke könnte diese
Lücke decken. Unter Einbezug von den anderen möglichen erneuerbaren
Energieträgern wie Wind und Biomasse könnte innerhalb zweier Generationen eine
nachhaltige Stromversorgung aufgebaut werden. Dabei müssten allerdings die
anderen Energieträger ebenfalls in der gleiche Tiefe wie dargestellt am Beispiel der
Photovoltaik auf Ihre Material- und Energieflüsse analysiert werden, um allfälligeEngpässe in der dynamischen Entwicklung zu erfassen.
3
Summary
Thls thesls presents a new method of assesslng the material and energy households of
new energy technologies which are based on renewable solar energy The method is
demonstrated by the large scale Implementation of gnd connected photovoltaic(PV) technology In Swltzerland The Swlss grid is modelled, and electriclty used to
Implement the PV scenarlo Is derived from thls grid As an important feedback, solar
electrlcity generated by the PV plants Is released mto the Swiss gnd, as well as the
electriclty from other sources such as hydro, nuclear, wind and blomass Details of the
PV plants are modelled. includlng the processes to manufacture and transport cells,
modules and balance of System (BOS) components
Modelling Is based on the method of assesslng the dynamlcs of matenal and energyhousehold, developed by Prof P Bacclni and Dr H P Bader at the Swlss Federal
Institute of Technology in Zürich The model which results from the analysis of Systemsincludes 14 processes, which are mterconnected by 12 matenal and 18 energy fluxes
and varlous System mputs and Outputs A set of equations and transfer functions are
used to descrlbe the System Parameter values are used to calibrate the SystemSmce the objective of the new approach is focused on the dynamics and long term
behaviour of the System, most parameter values are implemented in parameterfunctions, which are used to assess potential future trends in technologydevelopments For example, PV module efficiencies are defined as a parameterfunction, based on the assumption of how efficlency will evolve over the time penod of
mterest Three drfferent PV technologies, based on wafers, Sheets and thin films, are
modelled to provide a sensitlvity on some of the technological optlons to convert
incident solar radiatlon Into electricity Sensitivity analysis is performed on factors such
as average lifetime of PV plants or the growth time in which the identified PV potentialshall b© ©xploited Uncertatnftes about these values are considered usmg Gaussian
dlstributlon functions
New metncs like breeding factor and the time span which is needed to reach the
energy break-even threshold are valuable tools to provide msight into how new
technologies such as PV can provide electrlcity to satisfy loads Results indicate. thatPV Implementation within two generations, which has been assumed to be 60 years is
possible with no industrlal constramts with regard to matenal and/or energy needs
Faster time frames, such as for example, Implementation within 30 years would lead to
a very signiflcant flux In float glass, even much larger than used In the building sector
And the flux in punfied Silicon would be even more critical for the wafer-based PV
technology The fossil flux required to implement the PV scenano is mostly used for
non-energy purposes such as making polymers etc The energy content of this flux is
compared If mvested into PV ratherthan Converting it directly into electrlcity by means
of cogeneration, expressed as the fossil multlplier factor
Results Indicate, that there are large vanations between the drfferent PV technologiesbut that both breeding factors as well as the fossil multlplier factor are large enough to
justify the Start of the PV scenarlo Implementation The goal to implement the PV
scenano within one generatlon, which has been assumed to be 30 years, would
Induce substantial material fluxes, which may - at least for the wafer based PV
technology - lead to bottlenecks in supply In terms of energy, large needs within the
starting phase may be favourable, slnce the world market shows abundant energyavailable for the next decade
The transrtion from an energy paradigm which is based on non-renewables to
technologies based on renewable solar input has been analysed, and for In case of
the Swiss grid, demonstrated The shortfall caused by the phase-out of nuclear energy
4
öfter havlng reached the end of its lifetime can not be completely covered In sufficient
time with renewables because of the long implementation time required of
renewables. it is therefore assumed, that cogeneratlon will temporarily be an
important source to tili the gap between the time when nuclear plants are about to shut
down and renewable energy has not yet been fully developed to Its Potential. Other
renewable energy technologies such as bioenergy or wind should be analysed to the
same degree to make sure that the explottation to its assumed potential will not induce
critical energy or material fluxes.
Since this issue has mostly been debated for PV, the study focused around the
questlon of the metabolism of the large scale Implementation of PV plants. Results
clearly show that there is no constralnt in material or energy household, and that. on
the contrary, PV has a slgntflcant breeding potential, whlch Is necessary to achleve a
sustainable energy supply System.
5
1. Introduction
The greenhouse effect with its threat for possible climate change is considered one of
the most senous global environmental Problems (UN, 1992) and Implies that strongrestrictions may need to be placed on the use of fossil fuels Furthermore, fossil
resources are limited, and thelr use is not sustainable, since replenishment is at a rate
approximately one milllon times slower than the actual rate of usage
However, the use of fossil resources dominates the actual global energy supplySystem, with roughly a 75% market share One way of solving this dllemma is to
enhance the efficlency of appllances and to base the global energy system on the
direct converslon of solar energy The solar Insolation on the earth is about 10OD times
larger than the total energy usage of the anthroposphere Assuminga 10% conversion
efficiency from solar to an end-user form of energy, a surface area of roughly 35CU0CO
km2 would be needed to generate the global annual energy consumption of roughly100,000 TWh This is about 5% of the surface of the Sahara, or about equal to the land
surface used from the anthroposphere for the bullt environment, such as for buildlngsand transport Systems
Solar cell technology, offen also referred to as photovoltaics (PV), is one of the
promising ways to harvest solar energy PV provides a direct route to convert solar
radiatlon into electiical energy, a process whlch takes place wlthout releasing any
emissions to the environment PV Is therefore offen perceived as one of the Ideal
optlons to complement or eventually replace environmentally hazardous electncal
energy Technologies such as those based on fossil or nuclear fuel, both of which are
also subject to depletion
Larg© scale Implementation of photovortaic plants1 for electnc energy generation will
Induce signlficant material and energy fluxes The goal of this work Is to provlde a tool
for cybernetic strategies for the metabolic evolution of new energy technologies such
as photovoltaic plants The aim is to develop the methods whlch provide answers and
msights for the following questlons
• How can the metabollsm2 of the large scale Implementation of a new energy
System such as PV be assessed In order to Identify potential cntical paths with
regard to future material and/or energy requirements''
• What are the dynamics in material and energy management to realise large scale
PV plant penetration wrfhin a specific region?
Extensive analyses have already been conducted on the embodied energy of PV
cells and modules of varymg PV technologies and drfferent PV plant designs (Alsema1997 Komiyama, 1996, Dones at al, 1997 Häne et al, 1991, Meridian 1989) The use of
these energy analyses reflects the growing awareness of the need to evaluate
technologies from an environmental standpolnt The current methodology used for
analysing the environmental burdens from energy produclng Systems such as PV
plants is the Life Cycle Analysis (Suter, 1994, Nieuwlaar, 1997, SETAC 1992) The
approach Is sometlmes also referred to as "cradle to grave" analysis, because
Throughout this study, the term PV plant is used to descnbe the completewhich converts solar energy directly into gnd connected electncity and otten
refered to as PV system In this study, however, the term "System is used
sense
The term is defined in "Metabohsm of the Anthroposphere", Bacani and Brunner 1991
6
environmental Impacts are considered over the entire llfetime from the manufacturlngof the Individual components to Installation, use and final dlsposal.
The results of these works have also offen been used to calculate the quantify of
emissions released to the environment, to compare PV technologies wlth other
energy producing technologies or to assess the energy pay back time of dlfferent PV
technologies and/or various PV plant designs.
Other authors have focused thelr analyses on the posslble resource and
environmental constralnts that large scale expanslon of PV technology mlghtencounter (Andersson et al., 1995). Based on the State of technology, resources are
tabularised and compared wlth actual mlning capacities and wlth the maximum
available known resources. Based on an assumed, constant expansion rate of IßOO
TWh/year, the Potential scarclty of elements to make PV plants has been evaluated.
In this work, a new methodology is presented which evaluates the dynamic effects on
material and energy fluxes if the deployment of new energy Systems is assumed. The
methodology Is demonstrated by the large scale implementation of grid connectedPV plants within the System boundaries of Switzerland.
Based on the methodology of material flux analysls (Bacclni and Brunner, 1991: Bacclniand Bader, 1996), a valuable tool to assess Potential critical paths in material flux andindustrial capacity to bullt and Implement PV plants has been established. The methodallows for the assessment of critical fluxes and dynamic factors such as break-even
Points in relation to assumed time frames for reaching the potential of the selected PV
technologies and the PV plants.
The electrical and fossil energy fluxes are slmulated separately rather than havlngthem translated into one unit3. This makes the model a little more complex. but has the
advantage that results are not dependent on arbitrary System boundary selectlon(Menard et al, 1998). Energy pay back time has been defined as a new, dynamicmetric to answer the followlng questions:
• How much energy is required during the initial phase of the PV Implementation, andafter how many years from start is break-even reached? Break-even is defined as
the accumulated electrical energy invested compared to the total electrical
energy harvested from the PV System?
• How does net electrical Output from the PV plants evolve over time and how Is thisa function of various PV technologies.
Three major PV technologies have been analysed: crystalllne wafer, crystalllne sheetand amorphous thin film. In order to better compare these three optlons, all three are
based on Silicon. Silicon Is also the prlme candidate In terms of avallabllity and
physlcal properties and because it is envlronmentally benign.
The amount of float glass needed for module manufacturlng is very large. In order to
analyse the timing of glass supply and possible shortages ,the flux of glass for the
building sector has been added to the model. This facilitates interpretlng the dynamicdevelopment of glass flux needed for the large scale Implementation of PV,compared with existing glass flux in the building industry.
It is assumed that PV plants may become an important source of electricity (Gay, 1992,Pab, 1995, Shell 1997), and that grid connection of PV plants is a very attractive
Normally based on primary energy.
7
approach for future energy supply scenanos The dynamic transition from energy
supply Systems based on non-renewable energy sources to renewables such as
hydro. PV wind and biomass are demonstrated in the example of the Swiss Utility
In Chapter 2, System analysis are descnbed a mathematical descnption is given
model assumptions are explamed and the calibration of the model is given The
findings of these analyses are a set of parameter values which are used to computethe results These results are presented in Chapter 3 Conclusions are given in Chapter 4
Acknowledgements
This work has been made possible with the support of the Swiss Federal Office of
Energy Wrthln this contract the work has been co-ordmated by Dr S Nowak
The methodology applied wrthm the scope of this work has been developed by Prof
Peter Baccmi and Dr Hans-Peter Bader They provided thoughtful comments and
advice for applymg these methods to analyse the metabolism of PV Systems Myspecial thanks are given to Hans-Peter Bader and Ruth Scheidegger who assisted me
in definmg the System and the model equations and who provided support in applymgthe Computer program SIMBOX I would like to thank Gordon Howell of Howell-MayhewEngineering in Edmonton Canada for reviewing the English
8
2. Methodology
This chapter gives
• reasons for selecting the Material Flux Analysis method (MFA, Baccmi and Bader
1996)
• a descrlption of the System analysis which is based on three Subsystems for
modelling PV plant material household and energy fluxes Wrthln the System
analysis. an outline of the selected System boundary and the growth model are
presented
• the mathematical descrlption of the System
ZI System analysis
2.1.1 Requirements for the methodology
The large scale Implementation of new energy technologies such as photovoltaicsinduces large material and energy fluxes There are several questions for which the
chosen method should be able to provlde answers
• Are the induced fluxes signiflcant, how do they compare to other fluxes In the
anthroposphere and what are the dynamics of these fluxes''
• Smce gnd connected PV plants are consldered, what Is the effect on the grid itself
in terms of yearty energy production'' How does the accumulated energy
invested to build and maintain the PV plants compare to their production over
time? Are there cntical time constramts. and how does the time to break-even
between invested energy and PV energy production depend on parameters such
as growth time or cell technology
What is needed is a Simulation of the System In order to do so. a model has to be
established. and a program has to be used which allows the dynamic Simulation of the
Implementation of such new energy technologies Into an existing energy pattern To
compute scenarios, a solid data base of the Parameter function Is required The tools
of this method should also allow for visualisatlon of how fluxes evolve over time to
provide better msight into System behavlour
The average Irfetime of PV plants is assumed to be 30 years4 That means fhat there is
a significant time lag of matenal and energy fluxes between the time when
Implementation takes place and the time when dismantllng will occur at the end of its
Irfetime The production of electric energy occurs m-between the two events In the
case of PV power plants, where they are fuelled by renewable solar energy, almost no
other flux is needed durtng its operatlng Irfetime This resutts in a phase shift in flux
between Investment and energy production, and requires a model which can deal
with issues llke Stocks5
Manufacturers of PV modules give Performance warranties from 10 up to 20
successfull Operation of a stand alone PV System smce 1967 has been reportedinternal letter by "Service Technique de la Navigation aenenne in France
Stock in this context means accumulated matenal
9
Furthermore. there Is uncertainty Involved In the data and System assumptlons. For
example, data about lifetime are offen given as average values, but there exists
uncertainty about these values. Some of the PV plants fall earlier, some will last longerbefore they need replacement. The method has to take these uncertainties into
consideration. Thls is demonstrated by the given example of uncertainties about llfe
time.
Extensive up-to-date work has been carried out to assess the polluting characteristics
of PV plants, taklng Into account not only the direct operatlonal pollution, but
especially upstream and downstream pollution caused by the manufacture of
operatlng resources, Services, or materials or by the disposal of waste (Sutra et al.,
1992). Results on thls are calculated based on the actual pollution released by the
existing infrastructure whlch is needed to manufacture and install, operate, dismantle
and dispose of the PV plants. It Is helpful, in otherwords.to identlfy ecologically harmful
components in the energy System and to introduce Improvements.
However, thls method has a llmitatlon when trylng to address environmental impacts in
relation to a long-term strategy. It provldes a snapshot for a given moment in tlme, but
the dynamlc effects and especially feedback's are not taken Into account. Thls is not
critical, If only a limited number of PV plants are connected to the grid and are
produclng a minor amount of electrlcity, that by itself produces almost no change in
the mix of energy sources. However, to assess the large scale implementatlon of new
energy technologles such as PV, the consideration of feedback on the overall energy
supply System Is essentlal.
The method of Material Flux Analysis (MFA) descrlbed by Baccini and Bader (1996)
allows the assessment of dynamlc material and energy fluxes and provldes Insight into
a system's response when assessing impacts such as the large scale implementatlonofPV.
The two methods, the LCA and the MFA, are complementary and each method has Its
value. Work based on LCA has provided very valuable Information on energy and
material requlrements for the State of technology, and these data have been used a s
a startlng point for definlng future trends to slmulate overall System response when
applying the MFA method.
2.1.2 System configuratlon
The System to slmulate the material and energy fluxes for large scale PV
implementatlon includes all the processes whlch are related to manufacturing,transporting, Installing, operatlng and dismantllng PV plants as well as the electrlcal
and fossil energy dlstrlbutlon and its relevant fluxes between these processes.
The term "process" as used in this work means the transformatlon, transport or storageof goods. However, most of the processes which are involved In implementing the PV
plant scenarlo dlscussed later are not shown in the system layout, because It would
make the System too complex. As a consequence, the selection of processes shown
in the System layout have been limited to those necessary to understand the essential
fluxes and storage. In reality, there Is a very large number of processes linked togetherto provlde the final good such as PV plants. In the model, however, the System is
Condensed to the 14 processes which are essentlal to describe the System.
To provide still a better overview, the System has been arranged into three
Subsystems:
10
• The PV Subsystem, which cornbines all processes to manufacture, transport,
install. operate, dismantle and dlspose or recycle PV plants.
• The energy Subsystems whlch includes electrica! and fossil energy distribution
necessary to manufacture the PV plants and to fuel cogeneration. The electricity
generated by the PV plants from solar Input Is fed Into the energy Subsystem, and
relates to the feedback mentloned above. In orderto slmplify the System structure.
power generation from hydro. nuclear, wind and biomass as well as the load has
been assumed to be outside the System boundary.
• The glass flux from floatglass manufacturing to both the building and the PV
industry. The flux of glass Into the building sector has been added to the System to
allow comparison between an already established material flux and one which is
subject of the Investigation. The inclusion of the already known flux of glass will
provide a better basls to discuss the relevance of the additional glass flux needed
forthe implementation of PV plants.
-System boundarySolat
""
">
energy
Glass SubsystemQuarz __Sandmake glass
Front glass JRecycle
W 1 V
Material — Matemake
^
PV SubsystemPV plants
Energy to
make glassEnergy from
Other electrica!
energy
generators
j Energy to make jPV plants
1 - , 1 , V
Energy SubsystemLoads of
electricity
Fossil
energy
Figure 2.1 shows the slmplifled system configuration wtth 3 Subsystems for PV, Energy and Glass.
The loads and other electrical power generating Systems such as hydro, nuclear, wind and
biomass are outside the System boundaries to slmplify the model layout.
Figure 2.1 shows the three Subsystems and thelr interrelatlon as well as their relatlon to
sonne important processes whlch are considered to be outside the Systemboundaries. Electrical energy produced by the PV plants is fed into the energySubsystem. Since only utitity interconnected Systems are considered, this means that
the electricity from solar is released into the grid.
Energy fluxes for processes outside the System boundary are included in the energyfluxes (fossil and/or electricaD which relate to the process.
In order to provide a better overview of the System layout, the processes involved in
the System description are arranged within the three Subsystems and are highlighted in
Figure 2.2.
n
r
Slass Subsystem
Buildings pass pretreatmenn
Electrical
energylorPV
Solar cell prod BOS procuction
Module
production
Transport
Fossil
energy
lorPV
PV Subsystem
Electrical energy
distnbution Cogeneration
Fossil energy
distnbution
I Energy distribution Subsystem
Bgure 22 Shows (he )4 process needed (o deflne the System, arranged wtlhh (he three
Subsystems. For better clartty. the Kuxes between the processes are notshown.
2.1.2.1 PV Subsystems
The PV Subsystem, shown in Flgure 2.1 and Figure 2.2. includes all processes. related
mass, energy Stocks and fluxes to make. maintain and dismantle PV plants. The
processes which are termed Cell Production, Module Production, and Balance of
System (BOS) Production are related to make the PV plants. Process transportation is
included because it requires energy and involves other goods and materials
(electriclty, fossil fuel, cement for roads, steel for ralls etc.). All necessary transportwhich takes place outside the defined System boundary Is also included in the process
transportation.
The "Electrical energy for PV" process and the "Fossil energy for PV" process includes
all energy fluxes for such processes. The reasons for having them separated from the
"Electrical energy distribution" process and the "Fossil energy distribution" process in
the energy Subsystem are twofold:
• It makes the analysis of the energy flux more transparent; and
• It makes future model enlargement easier. when the metabolism of other energy
optlons such as wind or biomass shall be included in the assessment.
2.1.2.2 Energy distribution Subsystems
The energy distribution Subsystem Includes the two electrical and fossil energydistribution processes and cogeneration, which links fossil fuel with electricity.
Cogenerators are different from normal thermal power plants as they have much
higher efficiency, because the thermal power not transformed into electricity is used in
12
industrial processes or for heating bulldings. Furthermore, new technologies are
assumed such as fuel cells, whlch can be built small, modular and with high conversion
efficiencies.
The Electrical Energy Distribution process represents the grid wlthin Swilzerland. Other
generators as well as all loads. however, are vlrtually transferred outside System
boundaries to make the System more transparent, even though they are physically
located in Swilzerland. If other aspects than the metabolism of PV is Interest. one or all
this processes can be included in the System boundary and treated in an analoguemanner as the assessment of the metabolism of the PV plants.
The fossil energy distribution process Includes only that energy flux which is required to
manufacture. implement and dispose PV plants. Includlng all necessary
transportation. If also Includes the amount of fossil energy which is needed to fuel
cogeneration.
2.1.2.3 Glass Subsystems
The Glass Subsystem includes the production and flux of floatglass into the building
industry and PV module production sectors. The flux of floatglass into the buildingsector has been included in the model because the glass flux becomes signiflcantwhen implementing PV plants on a large scale, and comparlson with an existingindustrial activity provides better inslght to assess It's relevance.
The Subsystem also includes glass recycllng and the relevant process for glass pre-
treatment which is needed for recycllng. Float glass production requires less energy, if
a large amount of glass is recycled6. The glass flux in the building process is
deterrnined by the growth of new bulldings, the amount of glass already installed in
buildings and the time span, whlch determines how long glass will last in the buildings. In
about 2.2 million buildings, roughly one mlllion tons of glass Is installed. (Binz, 1995)
Other glass flux such as the flux in the automotive Industry is around 10,000 tons per year
(Klaus. 1993) and is almost equal to the building or PV sector. It could have also been
used as a reference. To simplify the model, this glass flux has not been consldered.
Glass, which is not recycled has been assumed to end In the landfill, either throughwaste combustion Installation or direct dlsposal.
2.1.3 System boundary
System boundaries have been chosen to be identlcal wtrh the Swlss border for the
following reasons:
• Discussions on the value of new technologies such as PV are offen centred around
questions on related material and energy flux. Switzerland is a hlghly Industrialised
country. and has - in principle - access to all the necessary technologies. Several
political initiatives are focused around the question to promote the use of
renewables, such as PV. The question on the metabolism of large scale
implementation of PV in Switzerland is therefore of greatest Interest.
Already the romans discovered that using recycled glass requires less energy than makingnew glass out from fresh quara and started recycling glass when wood became
energy source (Periin, 1996)
13
• Accurote data are easily accesslble. Yearly Statistical data are published for
exlsting energy flux and prevailing solar radlatlon for all the reglons.
• Due to its large hydro capaclty, the Integration of PV plants Into the Swlss electrical
grld Is well suited. slnce non-avallablltty of solar electrlclty for tlmes with low or now
solar radlatlon can be compensated by hydro electrlclty productlon.
Not all the relevant processes requlred to manufacture PV modules and componentsare wlthln the defined System boundary. In reality, most of these processes are outslde
the selected System border, such as the productlon of glass, polymers, plastlcmaterial. fossil fuel, etc. The relevant energy fluxes from processes outslde Systemboundaries are Included In the energy flux of the relevant process. For example. the
productlon of electronic (or solar) grade Silicon Is not based In Swltzerland. The energy
requlred forthls process (as well as all the pre-combustlon upstream processes ) is
related to the flux of reflned Silicon whlch Is needed to manufacture the solar cells. All
other electrical energy generators except PV plants and cogeneration which are
feeding electrlclty into the "energy dlstributlon Subsystem" process, have been
defined as being outside the System boundaries. Thelr contrlbutlon of electrlclty Is
taken Into account, but Is considered as an Import. Though the merlts of the new
methodology are demonstrated on the large scale Implementation of PV, the method
can also simulate the metabolism of all other power generating Systems such as
blomass orwlnd energy. Reasons for keeplng this generation capacity outside Systemboundaries were purely for slmplicity. Cogeneration is included in the System analysisbecause the flux of fuel to power cogeneration is used for comparlng the fossil flux
required to Implement PV.
On the other hand, there are processes of Interest, which have been included in the
System boundary, but are In reality outside the Swlss border. In partlcular, the
production of float glass is not based In Swltzerland and will most likely never be. for
structural reasons. Since the flux of glass is significant, the manufacturing process has
been Included Into the System configuratlon. Energy requirements for transportationneeds have been assessed accordlngly, öfter having virtually transferred the glass
manufacturing and glass recycllng process into the model boundaries.
2.1.4 Indicators
The implementation of PV plants Induces a large variety of material fluxes such as
glass, solar grade Silicon, polymers, various metals and energy fluxes. Four significantindicators have been identified to provlde an inslght into the major Impacts on the
system's metabolism:
• Energy (in MJ) is of prime interest in assesslng the value of the new technology as a
means to generate large amount of electrlclty. and In comparing this generationwith the needs of energy to implement the PV scenario.
• Glass On kg) Is Important because the slze of its flux Is in the same order of
magnitude as the flux for other industrial applications. Furthermore, it has been
assumed that glass is being used for all PV technologles being considered, and
that it will remain the technical choice to Protect the surface of the photon
absorblng layer from the environment. The usage of glass Is linear to the installed
PV module surface area.
• Solar grade Silicon (in kg) Is of Interest for two reasons: (D the amount of purified
Silicon is, even with a world Wide industrial productlon of about 17J0OO tons for the
electronic industry, still quite small and the amount needed just for the
implementation of the Swlss PV scenario may be significant and (ii) the Induced
14
energy requlrements to provide the purified Silicon is large and strongly depends
on the process to manufacture solar grade Silicon.
• Concrete Cm kg) for gravitational fixture of PV plants on flat roof is. in terms of
absolute weight, very significant. It is of interest to compare this flux with slmilar flux
induced in the anthroposphere.
Other material fluxes are negllgible when compared to other usage in the
anthroposphere. As State of the art. some processes to manufacture solar modules
use still materials, which must be regarded as environmental harmful when needed in
large scale. For example, In crystalline Si solar modules. solderlng the interconnects
between the solar cells is offen performed wifh soldering paste which contains lead.
There are, however, many other industrial technologles which do not contain lead and
which can be used to make the Interconnects. These Solutions may be a little bit more
expensive to implement, but the industry will apply other solderlng methods when, for
instance, the amount of lead used in PV would become a critical item.
2.1 A Detailed System layout
The system shown in Rgure 2.3 includes 14 processes, which are interconnected by 12
material and 18 energy fluxes. There are 4 material and 7 energy inputs. No material
Outputs from the system boundary occur, and all material is etther recycled or
deposited in landfills. There are 13 energy flux Outputs. Eleven of them are related to
waste process heat. O15 is the export of electricity. Oi6 relates to the electrlcity which is
fed to the loads (which are consldered to be outslde the system boundary).
In the system layout, material and energy fluxes are indicated by arrows. The arrows
indicate internal fluxes from one process to another process. or from inputs or Outputsoutslde the selected system boundary. The 14 processes are defined by thelr input.Output, transfer function and/or description of its Stocks. Detailed descriptions of the
key processes are given in chapter 2.3.3. The main driver which induces the initial
material and energy fluxes is determlned by the Implementation rate of PV plants In
process 9. The flow of the material necessary to implement all the PV plants is given In
flux A» Ct). This flux is induced by the sigmoidal growth of PV plants and the transfer
function in the "PV plants" process, and includes the two Issues:
• the growth rate of PV plants withln Switzerland; and
• how long PV plants will stay In Operation, as defined by its transfer function.
The relations between the various fluxes and Stocks are defined in the model
equations. These equatlons contain Parameters and parameterfunetions,
corresponding to system propertles such as Implementation rate, technologicalaspects etc.
The needs for electrical and fossil energy to make and Implement PV plants (includlngall processes such as mining, transportation and dismantllng) Is modelled In the two
processes: "Electrical energy for PV" and "Fossil energy for PV". Separating the
"Electrical energy distrlbutlon" process (the Swlss grid) and the "Electrical distrlbution
for PV* process simplifies the results analysis. The same argument is valld for
introducing a process for the distributlon of fossil energy to the PV Subsystem. Further-
more, this Separation makes the model more flexible and so can aecommodate a
later addition and analysis of the metabolism of other energy Systems. The distinetion
between electrical and fossil fluxes is essential for assessing electrical breedingfactors and fossil multlplier factors, which then become independent of the definition
of arbitrary System boundary. The advantage of this new approach is outlined when
discussing the results in chapter 3.
15
process
different
between
fluxes
identify
to
used
are
Indices
flux
material
afor
"A"
flux
energy
an
for
Stands
'£'
arrows
by
indicated
are
Interactions
processes
14
by
descnbed
configuration.
System
the
of
scheme
the
shows
32
Rgure
M"3)
'distribution
|3„
energy
Fossil
cogeneration
ossil
%
J/
0„
Mi»)
Cogeneration
cogeneration
from
Electncity
elec
tnci
tySolar
Mi">
Land
fill
PV
fFossil
1:*-i3MC«)
forPV
energy
Fossil
O^
Wasje
A,<
waste
Demolition
v,
MO)plants
PV
scraps
fron
tgla
ssPV
l0
A,
module
Fossil
E,,,
plan
tpo
wfer
PV
rejects
fron
tgla
ssPV
,„
A4
0,6
^_~14_5
015
Jk
L
energy
Fossil
I,,
M(5)
distribution
energy
Electncal
EIPV
E5,
> .electncity
Biomass
l10
electncity
Import
Ig
electncity
Nuclear
laI
-^
elec
tric
ity
Wind
l7I
_
electncity
Hydro
l6
transport
Fossil
„Ei,
ofil
lFnssil
3ElaBOS
Fossil
7^E,;
M<»
Transport
.
Module
A»
M'4'
^pr
oduc
tion
Module
_^_
M'7'
procuction
BOS
^L
7K"
TITA
prod
qlass
float
Fossil
?E19
M"01
|scraps
glass
Window
pretreatment
Glass
j,\m
MÜL
Buildings
prod
qlass
lloat
for
glass
Rec
A
V
f=^
Cel
prod
cell
Solar
glas
sWindow
^—
Solarenerqy
U
rmdule
El
E,4
transport
El
E,a
Polymeres
Cu,
AI,
I,
KMi"
fossil
El
1g
E,
it-atas
rFrei
El.cril;»
E|3
—
„
c—J
BOS
ElEr
?
glass
float
E„E|
forPV
energy
Electncal
--&_
Ji^SuEß^
malenal
BOS
\,
W
M«>
prod
glass
Float
->
Quarz
I,1
2.2 Mcrthemcrtical description
The method for the mathematical description of MFA is given in Baccini and Bader
1996 and is applied for the analysis of the metabolism of PV Systems in this work.
The System is described by:
• the System configuration• the System variables• the system equations such as intrinslc. balance and model equations
The model is then callbrated by defining the Parameters, using input and technical
data such as assumption of the transferfunction of the lifetime
With the aim for greater clarity. descriptlons of material and energy fluxes. which are
necessary to implement, operare and dispose the PV plants are separated in two
Steps:
• first step: description of all the relevant material fluxes and Stocks
• second step: description of all the relevant energy fluxes
2.2.1 Material fluxes and Stocks
System variables:
The System variables for the material fluxes and Stocks can be derived from Figure 2.3.where both, the material and the energy fluxes are shown. Figure 2.4 shows only the
material fluxes and Stocks, which makes the understandlng of the mathematical
description easier.
IjSi.P.R.
Electncal
energylorPV
I. AI. Cu, Polymeres,
A10 ?Rflp. glass fnr float Qlass prod,
+1 Float riläsfi pmd I Aas J Buildings L A.,.
Fror I glass
Window glassscraps
«Glass pret
Cell
1BOS procuction
M'7»
Module
^ production ^j iq PV frontglass rkjects
.
kt.
,-Transport |_BOS
A^Modulej Mrp
rer plEJntA.,» PV
PV plants
Demolition waste
Electncal energydistnbutßn
Cogeneration
M"4>
Fossil
energy
forPV
Landfill
Fossil energydistnbution
Fig. 2.4 shows the System analysls and Ihe related material fkoces and Stocks. The diagram derivesfrom figure 2.3. Whh a vlew of greater clarity, energy related fluxes are surpressed.
17
Variables: Number
• Material Stocks
M<2)(t). M°>(t), M(«(t). M<»(t), M^'Ct), M("(t), M">(f), M("»(t), M<">(t)
• Input Fluxes
l,(t).l2(t).l3(t).l/t).
• Intrinsic Fluxes
Aa(t). AaCt). AM(t). A^t). A,10(t). Aj^t). A78(t), A102(f). A,,0(t). A„„(t).A,11(t).AM(t)
9
4
12
Total number of variables 25
These 25 independent variables describe the material metabollsm of the selected
System completely- Wlth regard to the numerical Solution of the System equatlons, It Is
practicable to add the 9 stock change variables M,*... M,(l) to the set of 25
Independent System variables. Of course. thls new set of 34 variables is not any longerasetof Independent variables.
Notation
X2 = M°>
X3 = M"»
X4 = M<«
X5 = M<7'
X, = M»
X7 = M<9)
Xt = M'"»
X, = M<">
Xin = M<2>
x„.= M(3>
X,2 '
= M<4>
X1.V= M(6>
X,4 = M<7>
X,6=M(8)X16=M<"X,7=M<"»X,„=M<">
Xi? = h
X20 = l2
X22 = U
Xj3 = Ajj
Xj4 = A24
X25 = AM
X»3 A»
X27 = A4,0
X» = Ajio
A29 = A78
X» = Ana
X31 = A910
X32 = A)0)1
X33 = A^n
X34 = Ajj
whereas Mi<D dMOdt
Is the differentlatlon on time and slgnifles changes of Stocks.
Auxlliary variables:
By introducing the followlng 6 auxlliary variables, the implementation of the Systemequatlons into the program SIMBOX becomes much easier. Even if this means that 40
Instead of 34 equatlons are to be solved.
Xjs Fractlon of front-glass used for module production.Xm Fractlon of PV frontglass rejects, related to non 100% manufacturing yield (flows
to the process Glass pretreatment for recycllng or landfill)
X37 Flow of photoabsorblng material (Si-cells, a-thln-film layers) used for module
production.Xss Fractlon of auxlliary material such as polymer, aluminium, copper required to
manufacture modules.
Xj, End of life glass front-sheet flow from PV-installations to disposal and/or recyclingplants.
X40 End of llfe BOS-material flow from PV-lnstallatlons to disposal and/or recyclingplants.
18
2.2.2 Energy fluxes and Stocks
System variables
The system variables for the energy fluxes and Stocks can be derived from Fig. 2.3.
Simllar as described In chapter 2.2.1. the energy related fluxes and Stocks are shown In
a separate diagram In Flg. 2.5.
E..EI transpoft
USolarenergy
l1QBiomasselectnci
(Fossil energy
E,
Bpy
Modute
production
Mi«
lK Hydro electncrty J~
filtfind electrica Electncal energy [ EflSljsolarelectncity
UNucleaT^iedricrtj distnbutwnI^-ss^I^—JL.
l,lmporteleclricily .
Buildings
E,JJFossMoa\qteraspioci'y
Glass pretreatmentl—""-
B0S fM^UCtl0n |E.^FossilBd
Transport
E1; aFoseil cell
E12 B Fossil Transport
E.7, Fossil module
Fossil
energyforPV U
PV plants
Eu .Electncity from fossil
Landfill
Cogeneraton
611
E„„=ossil cogenera on
Fossil energy 3,
distnbution *1
r o.^o.^o,
Flg. 2.5 shows the System analysls. restricted to the energy tluxes. The diagram derives from flgure2.3. Material related fluxes are surpressed.
E(t) E(125(f)...
E(1">(t)
Variables
• Stocks of energies1
E<"(t),...
Ec6>(t). E(7)(t).
• Fluxes of energies
Input fluxes: l6 I,
Intrinslc fluxes: E,2, E,ra. E,7. E„, E„2, Ew, EM. E5,. E«, E122. Bw. E123. E124.Et» . E,312 , Ei314 , E^ä
Output fluxes: O,... Os. 07... O10.0,2 - 0,6
Number
12
17
14
These 50 independent variables describe the energy metabolism of the deflned
system completely. As in the previous part describing the material System, the 12 stock
change variables are added to ease the numerical Solution for SIMBOX. This leads to a
total of 62 system variables.
1 In terms of energy Systems, Stocks of energy are referred to as energy storages.
19
Notation
Xb-I. X» = E6, X6e = 04 X,,=E!3> X94=£<4>X4, = l7 X« = E« X„ = 05 X^E«1 X,5=E(5)X« = l, X57 = Era Xro = 07 X83 = E<6> X96=E(7>X45 = l, X.-E» X71 = 08 XM = EOT X97=E(8)X»-l» *,-E„ X„ = 0, *,-E» X98=EOTX47 = l„ X60 = E,M X73 = O10 X86 = EW> X„=£(u»X48 = E,2 \«-E„ X„ = 0,2 Xe7 = E X100=£(,2>X,-E110 X»-EB12 X76 = 0„ X68 = E<'2> X10)=£<13)*o-Ew XM = E,3U X76 = Om *, =E X102=E(W>Xs, = E13 Xm = E145 X„ = 0,6 X«,»?"0
X62 = Em X*-0, X78 = 0,6 X9,=EmX63 = E,8 XM = 02 X7, = E<'> X92=E(2>
0) dE0)Whereas E (t) = ——- is the differentiation in time and signifies changes of energy
dt
storage
The sequence of the variables has been changed wrth regard to the sequence
defmed In the section on the matenal flux, because no energy storage has been
assumed within the model This means, that all the energy Stocks and their
differentiation intime are equal zero, and actually they are superfluous for the System
descnption
2.3 System equations - model assumptions
Distinction is made between general and specific equations The general equationsinclude the so-called intrinsic equations and the balance equations The specific
equations are the actual model assumption
2.3.1 Material fluxes and Stocks
2.3.1.1 Intrinsic equationst t
F, = M<a(t)-MC)(0)-jMt2)(t')df = X,(t)-X,(0)-Jxlo(f)df =0
F, =M(")(t)-M('1)(0)-JM0,>(t')dt' = X,(t)-X,(0)-jx,8(t )df =0
0 0
F, F, simply express that M°'are the differentiation of M(i)mtime
20
2.3.1.2 Balance equations
The balance equations follow from the physical conservation of mass: in- and Outputand change in Stocks are equal zero.
F,0 = M(2) -1, - A102 + Aji + AM= X10 - X19 - X3Q + X23 + X24 = 0
F„=Mt3'-l3 + AM = X1,-X21+X25 = 0
F12 = M(4) - U - A24 - A^ + A^g + A410= X12 - X22 - X24 - Xjg + Xj6 + X27 = 0
F13 = MC6!-A26+A610=X,3-X23 + X28 = 0
F14=M<7'-l2+A78=X14-X20 + X29 = 0
F,5 = M(8> - A78 - A4, + AB- X16 - Xj, - X^ + Xg4 = 0
F16 = MOT - A8, + A„Q + A„,=X,6 - XM +X3, + X33 = 0
F]7= M -A410 -A610 -A910 +A102 + A]01]=X17-X27-X28 -X31 +X3) +X32 = 0
F18= Ivl - A,01, - A,n=X]8-X32-X33 = 0
2.3.1.3 Model equations
The meaning of each equatlon is given in a Short description. Note that the parameterfunctions are defined more in detail In chapter 2.4.
Fw =lv1(2)(t) = X,0(t) = 0
No change of stock within the process float glass productlon
F20=lv1(3)(t) = X„(t) = 0
No change of stock within the process cell production
F21=tv1M>(t) = X12(t) = 0No change of stock within the process module manufacturlng
F22 =Mc6)(t)-P,(t) = X4(t)-P,(t) = 0
M(6) is the assumed quantity of wlndowglass, which is needed In the buildings
F23=!v1c7)(t) = X,4(t) = 0
No stock change stock in process BOS production
F24=lv1(fl)(t) = X16(t) = 0No stock change stock in process transporl
F26 =M(9)(t)-P2(t) = X7(t)-P2(t) = 0
Mm is the assumed quantity of PV power generotion plants instalied in Switzeriand
F26=(v1(,0,(t) = X17(t) = 0No stock change in process glass pretreatment
t
hl = A9io -PsCßjMt.nPsCf )[AM(f)- A410(t')]dt' = X3,(t)-P3(t)X36(t) = 0
0
21
F28 = A,„ -(l-P3(t))jk,(t.t')P6(t')[AM(f)-A4,0(t')]clto
-jk2(U')[ P,2(f) AM(f) +P13(t')l4(f)]dt' - jk2(t,t')A78(f )df0 0
= x*. (t) - 0 - p3 w)x36(t) - XM (t) - X«, (t) = 0
A,,, and A,,0 are materlal flux related to dlspose PV-Plants whlch have reached their
end-of-llfe time
P3 (t) relates to the fraction of how much of the PV frontglass Is recycled respectivelydlsposed In landfllls
k,(t,t') deflnes the transfer function of frontglass recycled in the process glass
pretreatement
F2, = A7e -P4(t)A^ = X^ -p.mx^ = 0
A„ is the BOS-matenal flux The Parameter P4 (t) relates the BOS flux as a fraction of the
flux of modules needed to make the PV plants
t t
F3o = A610 - Jk3Ct.t )A26(t )dt =X28 - jk3(t.t')X23(t )dt =0
o o
A is the flux of windowglass scraps from the buildings to the glass pretreotmentprocess k3 (t t') defmes the transfer function of windowglass in the process buildmg
F31 = A48 -P6[U + A24 + A34] = X26 -P^p.^ + X24 +X26] = 0
Ajj is the flux of PV frontglass rejects, which flows to the glass pretreotment process
and P5 is the Parameter function deflnlng the fraction of rejects Ps is related to
manufacturing yleld
F32 = A102 _P6^''lA4io + A^ig + A910J = X3o -P6(t)[X27 +XM + X3]] = 0
A)02 is the flux of glass from the process glass pretreotment to the float productionwhere floatglass Is monufactured P6 (t) relates to the assumptlons, how much glass will
be recycled, and how much will end In landflll (or may be used for other purposes such
as 1 e the production of foam glass)
F33 = AM - P7tf>A24 = X^ -P7(t)X24 = 0
AM is the flux of photon-absorbing matenal (In the case of the data used in this study it is
electronic or solar-grade Silicon) P7 relates to matenal utllisatlon to make the
absorbing. electron generatlng layer
F34 = I4 -PaWA« = XJ2 -PeCWj,, = 0
l4 is the flux of moterials used to interconnect cells and laminare them to a final module
P8 (t) defines this materlal usage as a fraction to the flux of necessary front glass
Fjs = XjsCt) - P5Ct)[X24(t)- X27(t)] = 0
22
Xs is defined in chapter 2.2.1. P5 (t) defines the fraction of frontglass used actually for
module production.t
FM =X36(t)-Jk1(t.f)X35(t')dr' = 0
o
X» is defined in chapter 2.2.1. k,(t,t') defines the transfer function of frontglass in the
process module manufacturing.
Fs-V»-Paö>V>-0
X37 is defined in chapter 2.2.1. P12 (t) reiates to the fraction of photon absorbing materlal
which is needed for the module manufacturing.
X;» is defined in chapter 2.2.1. P,3 (t) reiates to the fraction of auxillary materlal which Is
needed for module manufacturing.
F3, = X39(t)- Jk2(U' )[X37(f ) + X38(t' )]df = 0
F40 =X40(t)-Jk2(t.f)X2,(f)dt' = 0
0
Note that equatlon Fx to Fa are actually nothing eise than the definitions of the auxlliaryvariables.
2.3.2 Eneigy fluxes
2.3.2.1 Intrinsic equations
F41=Ec»(t)-E(»(0)-j0
F42=...
F62=EM(t)-EM(0)-j0
2.3.2.2 Balance equations
F53 = £(" " Esi + E12 + E„0 + E)3 +E17+ E112 + E1e + E,4 + O, =0= (X,,) - Xjj + X4e + X49 + Xjg + Xj, + Xjj + Xjj + X^ + X45 = 0
FM = E - E12 - E122 + 02 = Os^) - X^ - Xj; + X^ =0
(i) ,
E ff)dt' = X„(t)-Xw(0)-Jx„(t')df = 00
(10 t
E (t')df = XTO(t)-X90(0)-Jx,Q2(t')dt' = 00
23
F66 = e<3)-E13-E,23 + 03 =0W-X5,-X^ + X,; =0
F66=E<4'-EM-E,M + 04 =(X94)-XM-XM + XM =0
F57 = E(6)-l6-l7-lB-U-li0-E«-Ei* + esl+O5 + O15 + O16 =0
- (X^ -X42 -X« -XM -X45 -\e, "X^'X« + X^ + Xy, + X77 + X78 -0
Fjg = £ -E]7-E127 + 07 = (X%) - Xjg -X^ + X70 =0
FM = £<» - E„ - EI23 + Oe = (X,7) -X« -X,, + X71 =0
F60=E<'>-l6 + E96 + O9 =(XW)-X41-X66 + X72 =0
F61 = £<"»-Eno + O10 = (X99)-X49 + X73 =0
F^ = £ - E112 " E1312 + E122 + E123 + EI24 + E,27 + E12e + Ol2 =0
= (XiaV " *52 " X<>2 + Xj7 + Xg, + X^o +XJJ + X61 + X74 =U
F63 = E03)-ln+Ei3i2 + E,3i4 + O,3 =(X,o,)-X47+X62+X63 + X76 =0
FM = £ - E,314 + E146 + 014 = (X]02) - Xjj + X^ + X76 =0
2.3.2.3 Model equations
(i)
F^ = E = X91 = 0 no changes in energy stock
(2)
F66=E =X92=0
F76=E =X102-0 = 0
F„ = |6-P1<E>=X42-P1<B=0
l6the electrical energy flux from hydro power plant P,CE> (t) defines the assumed trend
of development of hydro productlon
F78=l7-P2B=X43-P2I>=0
17 is the electrical energy flux from wind power plant P2(E> (t) defines the assumed trend
of development of electrical energy production from wmdturblnes
Ft^Is" P3 = X14- P3 =0
18 is the electncal energy flux from nuclear power plant P3 (t) defines the assumed
trend of development of electrical energy productlon from nuclear power plants
24
Fao -1? 016 - \ß- X77 - 0
I, relates to electrical energy Import and 0]5 to the export of electrlcity Within the
study, import and export have been assumed to be equal over a one-year time
penod 2
Fbi= ho_ P4 =Ki6" P4 =0
1,0 is the electrical energy flux from Biomass Power Plant P4(f) defines the assumed
trend of development of electrical energy production from biomass fuelied power
plants
FK = E,«- P5 =X„- P6 =0
E145 is the electrical energy flux released from cogeneration plants P5(t) defines the
assumed trend of development of electrical energy production from fossil fuelied
cogeneration plants
P6 defines the trend of Implementation of cogeneration
Note The values of P^Ct) P6e>(t)are deflned in 243 and descnbed in more detail in
243
FM = O,6P7<E>-O5 = X78P7<E>-Xw=0
05 is related to the transmission losses In the gnd p^'is the parameter function deflnmgit's value and trend It does. however, exclude the losses from the fractlon of electncityused to make PV-Plant
F85 = E5I Pr-O,=X6BPr-X65=0
E51 is the total electrical energy required to make the PV plants The process electrical
energy distnbution for PV has been Included in the model to make mterpretationseasler In fact, all the electrical fluxes could also be denved directly from "electrical
distnbution" Separating the requlrements for PV plants has the advantage, that all the
electrical energy flux is now summarlsed In one flow, namely In E51 O, Is related to the
transmission losses to that fraction of electrlcity which is used to make the PV -plants
F86 = El314 P8 -Oi3=X63 Pg "X75=0
E,3,4 is the fossil energy flux needed for cogeneration P8 relates to conversion
efficiency 0,3 is the heat produced, considered in the model as an Output (In realitythis heat has a high economic value and will be used for thermal heating applications)
F87 = E,3,2P,e-O,2=X62P9<D-X74=0
2 Import and export wll be the difference of production and consumptlon Assumptions on 1he
trend of consumptlon are not within the scope of thls study
25
E,312 is the flux of fossil energy needed to make. Install and dlsmantle PV-plants It
mcludes the fossil energy for all pretreatment Steps such as SI02 reduction wrth cocks
cleanlng SI. fabrlcatlon of plastic materlal. transportatlon etc On are the losses (seif
consumption) for handling and transportatlon of the fossil energy
F88 = El2 " P10 A» =X» " Pio X24=0
E,2 is the electncal energy flux needed to make floatglass Only this fraction which is
needed for PV frontglass for PV-module manufactunng Is considered The energyneeded to make float glass whlch is used for windowglass In the bulldings is not
mcluded In the flux E12
Ff» = E122 - ( P,? (AM+ A*) - P,2 A1CE) \A24 + A26
= X57-(Pn (X24+X23) -p£ X30)v X24Y =0
*24+A23
E)22 is the fossil flux needed to make floatglass The energy requirements to make
floatglass decreases when more recycled glass Is added to the flux of new quartzInput P,i(E> and P^ define the potentlal reduction In energy consumption as a function
of amount of recycled glass input
F90 = F.1,0 -OW/W P,T P6 =X« - (X27 + Xs,) P,3 P6=0
Eno is the electrical energy flux needed for the process glass pretreatement Only the
fraction which relates to the glass flux from PV frontglass reject and scraps is taken into
account It does not include the energy requlred for glass pretreatment from the flux
from wlndow glass The energy requirement for the process glass pretreatment is
mamly dominated by the electncity needed for the mechanical millmg of the glassThe flux of fossil energy in this process is neglectable and has therefore not been
considered
F91 = E17 - P14 At8=X50 - P14 X» =0
E,7 is the electrical energy flux needed to manufacture the BOS Components It also
includes all pretreatment steps for the BOS materlal such as electronic componentsand enclosures for power condltioners, all Integration matenal which are needed to
install the PV plants on bulldings etc
F92 = Fil27 - P15'ÖW = X58- P15 X29=0
E127 is the fossil energy flux needed to manufacture the BOS Components It also
includes all pretreatment steps for the BOS matenal such as electronic componentsand enclosures for power condltioners. all Integration matenal which are needed to
install the PV plants on bulldings etc A large fraction of fossil flux is due to the selected
Integration into titted roofs by uslng plastic frames
F93 = E13 - P,T Am = X51 - P,6 X* =0
E,3 is the electrical energy flux needed to manufacture the photon absorbing solar cell
layer It also includes all pretreatment steps especially to precondrtion the Silicon for its(E)
proper application to make elther solar cells or Ihm film layers P,6 is the Parameter
26
function which defines the trend how energy requirements will evolve over time P16 is
a complex function and detailed explanatlon is given in chapter 2 4 3
F« = El23- P|7 Am = Xs<?- P|7 ^24=0
E123 is the fossil energy flux needed to manufacture the photon absorbing solar cell
layer It also mcludes all preatreatment Steps, especially to precondrtion the Silicon for
its proper applicatlon to make elther solar cells or thln film layers P17 is the paramter(E)
function which defines the trend how energy requirements will evolve over time P17 is
a complex function, and detailed explanation is glven in chapter 24 3
F?S = E14- P18 ^B)=X64- P18 X24=0
Eu is the electncal energy flux needed to manufacture modules It also includes all
pretreatment steps, especially to preconditlon polymers needed for the(E)
encapsulation the tabs for the mterconnection and soldenng material Pi8 is defined in
chapter 2 4 3
F% = E124 " P]9 A» =X60 - P]9 X24 =0
Ei« is the fossil energy flux needed to manufacture modules It also includes all
pretreatment steps especially with regard to fossil input tp manufacture the requlred
polymers for module encapsulation P„ Is defined In chapter 24 3
^97 = El8 " P20 ^W = X53- P20 X34=0
E18 is the electncal energy flux needed for transportation, which Is in essence the
electncal energy for rail transports It also includes all the needs to build and maintam<E>
the rail mfrastructure as well as the fabncatlon of the tralns P20 is defined in chapter243
F98 = E128 " P2i ^8? =X61 - P2i X34 =0
E129 is the fossil energy flux needed for transportation, which is in essence the
requirements for trucks and ships It also includes all the needs to bullt and maintain the
mfrastructure as well as the fabrication of the trucks and ships P is defined in chapter243
F,, = E» - jMTO(f) P®(f) P®(M»Cf )) P® df =
0
=X56- jpjff) Pfcr) P^(P2(t')) pgcff'O
E» is the electrical energy which Is produced by the total of the installed PV plantsSince PV Systems are gnd connected, the electricity generated will be fed into the
gnd modelled by the process electrical energy distribution in Box 5 Since the processis of major interest and of key relevance to the large scale Implementation of PV
plants detailed explanations are given in chapter 233 The Parameter values are
defined in chapter 24 3
27
t t
Fioo = ls- jM(9)(f) Rgj>(f) dt'=X4i - JP2(t) p£>(f) dt =0
0 0
l5 is the solar Irradiation which hits the PV plants Instalied I5 Is caiculated as yearly
average values Further explanations are given In chapter 2 3 3
FlOl =El312 P25 " En2= P25 X68-X62=0
E1312 is the total fossil energy required to make the PV plants The process fossil energy
distributlon for PV has been included in the model to make mterpretations easier The
explanation is slmilar to the reasons stated at equation Fjs 0,2 is related to the „losses"
to that fractlon of fossil energy whlch is used to make the PV plants The losses are
<E>
mamly related to seif consumptlon to exploit, reflne and transport fossil energy P25 is
related to the trend. how this selfconsumptlon evolves over time
<E) <E>
F102 = l9" P26 = X/|5 " P26=0
I9 is the total electrlcal energy Import P26 refers to the trend how Import will evolve
over time For ease of analyslng results from the Simulation, it has been assumed that
import and export of electncity will be equal over the considered penods of one year
The System is defined by a total of 102 variables, 39 parameter functions and 105
Parameter values Input data are used to calibrate the Parameters
2.3.3 Detalled doscrlption of selected key processes
Each of the 14 processes whlch form the model is necessary to generate the answers
for the questions stated In the introduction Some of these processes are qurte trivial
and their characterlstics have been descnbed In other publlcations, such as 1 e the
process to make floatglass There are, however, some key processes, which do need
further explanatlon, because their nature is of special interest for the model These
most relevant processes are
• PV plants,• solar cell productlon,• balance of System (BOS) components and
• electrical energy distributlon
For each of this four processes, detalled descnption of the matenal and energy
variables are outlmed, by first showmg the diagram of the System analysis wrth the
process of special interest clipped out from the general layout of figure 23 Then
matenal and energy variable are explamed, and reasons for the relevant equationsare explamed The actual values for the parameter functions are given in chapter 2 4
2.3.3.1 The Process "PV plant"
Wlth regard to the System analysed in this study, the process PV plant Is a key process• the Incident solar energy Is transformed Into electrlcity, which is fed into the
electncal distributlon System and
• the Implementation of PV plants Is responsible for the induced matenal and energyflux
28
I5 Solarenergy
Float glass prod"
M<2>Glass pretreatment "1
1 M'"* 1
Solar cell prod BOS procuctionMIT)
Module
productran
Transport
PV power plant
PV plants
M«
Electrica! energydistribution
Eg5 Solar electncrty
A, ,0PV frontglass scraps
energy
forPV
A9„
Demolition waste
Cogeneratran
Fossil energydistnbution
J
The Flgute 2.6 shows Ihe process 'PV planls'. clipped out from the overan model conflguratlon h
Flgure2.3.
The process PV plant has:
1 Material stock
• M,(t), which represents the development of the stock of PV plant, or with the
terminology of the energy analysts. the accumulated power of all the PV plantsinstalled.
2lnputs
• A8, (t), which describes the flux of PV plant material to the box PV plant• l6(t), which is the incident solar radiation on the installed PV plants
4 Outputs
• A„0 (t), which is the flux from frontglass to the pretreatment process for recycling,• A,„ (t). which is the flux of PV plant material. which is going to landflll öfter PV plant
have reached its end of life time.
• E*j (t). which Is the flux of produced solar electrlc energy from the total amount of
PV plant Installed to the process of electrlc energy distribution (where the solar
electric energy is fed into) and
• O, (t). which is the Output of the process PV Plant, and Is the dlfference between
incident solar energy and electrical energy flowing to the electrical distribution
System in box 5.
These 4 material variables M,(t), A„ (t), A,,0 (t), A,„ (t) are deflned by the followingmodel assumption:
PV plants are made out of goods (such as PV modules. support structure, cables,
power conditioner, etc.), which "tlows" into the process PV plant by the flux A^Cf). and
29
remalns in the process dunng its entire llfetlme. betöre the PV installations needs to be
dlsmantled and belng replaced by new ones Within the model. it is assumed that the
frontglass. which Is needed in the module construction will be recycled. glven In the
flux A,,0 (t), and the rest such as cement blocks, plastlc frames, cables etc will end in
the landfill3. given in flux A,,, (t)
The dynamic transferfunctlon modeis the effect. that - although average life time of PV
installations is 30 years - some will fall earller and need a faster replacement, whereas
some last longer and have a longer llfetlme betöre needing replacement by new PV
plants A Gaussian dlstrlbution of life time probability has been assumed, with average
life time of 30 years, and a Standard deviation of 10 years
This moterial flux into and out of the process PV plant results from the assumed growthof PV plants, which Is glven in equation F^ A sigmoldal growth of PV plant has been
assumed, which is deflned in the Parameter equation P,(t)
The Parameter functions P,. P», P,0. Pn are dlscussed In detail in chapter 2 4
The 3 energy variables l6(t), E«(t), 0,(t) are deflned by the following model assumptlon
The electrical energy produced by the PV plants, which Is fed Into the grid (glven in
process electrical energy distnbutlon), Is defined by the equation F„ =0
E«(t) = jlv1<9)(f) P®<n P®(M(9)(f)) P®Cn dt'
o
whereas
M">(t) Is the growth of the Installed PV plants
P2(E) (t) Is the development of solar cell efficlency over time
Pb <e) CD Is dependent of actual PV orlentation wlth regard to optimal orientation
PM (E) (t) is the incldent solar radlatlon on the installed PV plants
One of the value of this equation Is the following
As technologies improve along the leaming curve, it Is assumed that over time
efficiencies and avallablllty of PV plants as well as manufactunng yields are gettmg
higher and material utilisation Is improving However, it is obvious that PV plants, which
have already been installed at an earller point in time will not increase their
Performance These PV plants Installed at an earher time will remain constant in their
energy production (or eventually may even declme in yearly production yield over
time, as the PV plants become older) The above equation defines that only those
Systems which will be installed at the very moment of the Simulation will reflect the
actual Status of mcreased Performance, combined with the improvements of the
processes to make the components and Systems
This equation Is a slmpllflcation of the following exact one
E,5(t) = 2>Mti fj« fj=> etifisf CellBfldencyl UfllbattonFactorforCellClassl
AMt, Cell class, which was installed in period (t,, t|+dt)
3 Of course, cement and most of the orher BOS material will be recycled, butttie Impact on 1he
overall System response is of minor Influence and has therefore been neclected
30
f,'1' Cell Efficiency
ftf Utilisation Factor for cell, class I
et Solarenergy per year and m2
Usmg the followmg simplrfications
AMti=Mmft, + ^] At
f,'1' = P®(t,) Efficiency is expressed as a real time correlatlon of the moment of PV-
erection
ff = P|p (M(9)(t)) Roof utilisation is actually individuaiiy defined In the sense of a
simplificahon it is assumed that it is function of the solar cell stock
Initially only roof surfaces with high PV-Potential are taken in account Later, when
Mw becomes large, also surfaces with lower yield EYP will be used
et, = p24'ft|) Solar energy per year per kg PV (stock)
it follows
E96(t),XM(9,(tl + f) At PfCr. + f) P^M«(tl+f))p<?(tl+f)t
E95(t) = jMw>(t ) Pf (t ) P©(f) Pg'(f)dto
For the solar mput ls(t). with same proceeding as performed above, follows
5(t) = JMm(t) P2^(t)dt' Solarenergy for the solar cells
o
where
l,5(t) = £AM,, efl
and
etl =-L_.1200-k^*3.6'MJ40 M. m2
'
kWh
m2
0<, finally results from E« and l5 and from the balance equation FM
31
2.3.3.2 Process "Solar cell production"
The process solar cell production describes the manufacturing of the photon
absorbing layer, which serves to generate electriclty from incident solar radiation.
Electrical and fossil energy flux are simulated as well as the required materlal input. It is
the process which Induces the.highest energy flux for the PV plant Implementation.
rFloat glass prod
I M"'
I, Si.P.B,
Electrical
energylorPV
E„ El cell
Buildings Qlass pretreatmentM"°» I
Solar cell prod
A,
Cell
Module
production
M
Electrical energydistributwn
BOS procuction
Transport
PV plants Landfill
—M*">-
Cogeneration
Fossil energydistnbution
Figure 2.7 shows the process „Solar cell production", clipped out from the overall model
configuration in Figure 2.3.
The process cell production has:
1 Material stock
• M3(t), which represents the development of the stock of solar cells.
3inputs:
• l3(t). which describes the material flux required to manufacture the Silicon based
photon absorbing layer. The materlal flux is an Input from outslde the System
boundary. Related energy requirements to this flux are Included in the energy flux
E13(t).andE123(t).
• E13(t), which describes the electrical energy flux required to manufacture the cells
(includes also all pre treatment Steps, which includes processes outside the
System boundary. such as manufacturing of solar or electronic grade Silicon).
• E,23(t), which describes the fossil energy flux required to manufacture the cells
(includes also all pretreatment steps)
32
2 Outputs:
• AM(t), which is the flux of photon absorbing layers to the process for the module
manufacturing• 03, which is the Output of the process PV Plant, and this is in the form of thermal
energy. which is released to the envlronment. Since the flux AM(t) includes almost
zero energy, the Output Q, is the total of electrical and fossil energy input into the
process cell production.
These 3 materlal variables M3(t), l3(t), Aj/t) are deflned by the following model
assumption:
The photon absorbing layers - or solar cells or thln film layers - are made out of
material, which flows into the process solar cell production. The input material Is mainlyelectronic or solar grade Silicon. But there are also other materials needed, such as to
make machines to manufacture the solar cells or consumables, such as dyes or
crucibles as a Containers for the melted Silicon, tt is assumed, that there is almost no
stock of solar cells in the production, and therefore it follows that M3(t) = 0.
One of the major issues of solar cell manufacturing Is the question of how efficient the
input material is used to make the photon absorbing layers. There are greatdifferences between crystalline, sheet and thin film technologies. The relation is
described In equation F^ ,and the porameter function P7(t) deflnes for the three cell
technologies investigated the material utilisation efficiencies. P7(t) is defined in detail
in chapter 2.4,
The three energy variables E13(t), E,a(f), 03(t) are defined by the following model
assumption:
All energy fluxes which relates to the process itsetf, but also to all the pretreotmentSteps are separated in electrical and fossil energy flux. An important pretreotmentSteps is. among others, the manufacturing of solar or electronic grade Silicon,because thls steps are energy intensive. The Output 03 is thermal energy, and no other
usage than heating of the manufacturing buildlng has been assumed. 03 is consideredto be a loss.
2.3.3.3 The Process "balance of System components"
The balance of System (BOS) components includes all material, which is necessary to
combine PV modules to a PV plant. It is the Installations material needed such as
support structure (framlng for the roof tile or supporting cement elements for the flatroof installation), cables, connectors, power condltioner, fuses, electricalinterconnection to the grld etc.
The process BOS has:
1 Material stock
• M7(t), which represents the development of the stock of BOS material.
3lnputs
• E17(t), which is the electrical energy flux to make BOS components• E,27(t), which is the fossil energy flux to make BOS components• yt). which is the material flux requlred to make the BOS components
33
2 Outpuls
• A„(t), which Is the flux of BOS moterial to the process transport• 07(t), which Is the Output of the process BOS. Thls is essentially all thermal losses
from the process.
The 2 moterial fluxes A„(t) and yt) and the 3 Energyfluxes E„(t), Era(t) and 0,(t), are
related through the model assumptlon descrlbed In equations F,4. f„, Fj,, F„. and F„.
Float glass prodM°>
BuildingsM»
Glass pretreatmentiI M""
l2 BOS Matertat
Electrical
energyforPV
Solar cell prodM<»
11BOS procuction F,
Mm | =2
Module
production
M»>
TransportMi«
|_BQS
PV plants
M»
LandliU
M'">
Etectncal energydistribution
Cogeneration
Fossil energydistnbution
Figure 2.8 Shows the process "BOS-produciion", cüpped out from the Overall model
configurafton in Figure 2.3.
The driving flux Is defined by A78. Defined by the model assumptlon, all other processes
are related to thls flux. It is the flux of moterial, which - being transported to the Sites of
PV plants - Is initially the driving flux for the other fluxes. A7e relates to the flux AM.
2.3.3.4 Process "electrical energy dlstributlon"
The electrical grid of Switzerland is modelied in the process "Electrical energy
dlstribution". In addition to PV and cogeneration, the electrical distribution System is
fed from other electrical energy generations Systems such as hydro, nuclear, wind
and blomass. The electrical energy flux to the loads is modelied in one Single flux,
which represents the aggregate of all the loads: 0,6.
The other generators and the loads of the grid are consldered to be outside the
System boundary. The nature of the other generators and of the loads themselves are
not relevant for the investlgatlon of the metabolism of PV. The losses of the process
electric energy distribution System is related to in flux Os, which in fact represents the
various losses of the grid4.
4 Losses of the grid h Switzerland are yearly publlshed h ttie VSE Bulletin (Schweizerische
34
The flux into the load. however, Is of great Interest, because it Is the result of how much
electricity will be avaliable to the loads If electricity generotors which are operoting on
depletable sources5 are replaced by such technologies which are based on
renewable sources. Results are presented In chapter 3.
~liGlass pretreatment l
I M"°> I
Electrical
energyforPV
Solar cell prod BOS procuctionM<«
f—Module
production
M'4>
Transport
PV plants
Mm
I lB Hydro electricity .
[ lT Wind electricity > Electrica! energy
I, NJudearftlentriratyi distnbution (-
In Import electricity .
I,n Biomass electricity m|J
Egs Solar electricity
Landfill
M""
EM s Electricity trom fossil Cogeneration
Fossil energydistnbution
JThe figure 2.9 shows fhe process "Electrica! energy distnbution, clipped out from fhe overall
model configurafion in Figure 2.3.
The process „Electrical energy distributlon" has:
1 Energy stock
• E<5)(t), which represents the development of stock of electrical energy. (In term of
electrical engineering this is equal to electrical energy storage).
7lnputs
• l(,(t) is the Input of electrical energy from hydro• l7(t) Is the input of electrical energy from wind
• le(t) is the Input of electrical energy from nuclear• yt) is the input of electrical energy from Import frorn ptants outside Switzerland• l10(t) Is the Input of electrical energy from biomass power plants• Ew(t) is the flux of electricity, generated In the PV plants• E„ß(t) is the fraction of electricity generated in cogeneration power plants
4 Outputs
• EjiCf) is the electricity flux which is needed to manufacture the PV plants• Os(t) Is the loss of the process electrical energy distributlon (related to grid losses)
Gesamtenerglestattsltk)5 In the example of Switzerland, the non-renewable energy source Is nuclear and b assumed to
be replaced by electricity generatlon technologies based on renewable sources
35
• 0,5(t) is the electriclty, which is exported outslde Switzerland
• 0|6(t) is the electricity flux which Is flowlng to the totality of all loads
The 11 energy fluxes are related through the model assumption described in
equations FS7, F„, F78, „,, F»,, F8„ FM, F«. F„. F102 and Fw
The drivlng fluxes In this assumption are defined by the defined energy Inputs from
hydro, wind, nuclear, biomass. Import and cogeneration The flux denved from PV
plant has already been dlscussed In chapter 2 3 3 1 The other fluxes are related to the
materlal fluxes and result in the flux E5,, or follow from the balance equation
It is assumed, that no direct electrlcal storage in the grld is feasible
2.4 Model calibration
Within the 60 equations which are describlng the System, there are 39 parameterfunctions 13 for the materlal part and 26 related to the energy part Each of this
parameter functlon has a specific meaning wrthin the System Some are defmmg
developments of Stocks over time such as I e the stock of wmdowglass in the buildingsor the accumulated stock of PV plants Other parameter functions are describlng the
transfer functions or transfercoefficent
Calibration means to adapt this parameter functions and coefficients to known data If
no established and proven data are available. data may be extrapolated from the
past by makmg assumption of trends and development into the future Calibration
therefore Is an essential step in the methodology, and significant conclusions rely onthe proper calibration of the model
24.1 Growth modeis
Some of the parameterfunctions are defined as the development over time in the
future There are several established growth model, and some specific charactenstics
will be briefly dlscussed
Growth rate Is determined by
• the upper limit
• the time period• the growth pattem
Most growth pattem of mdustrial products or the Substitution of i e old goods by new
ones follow the sigmoidal (S) - shaped growth6 curve (Fischer, 1970) Accordingly
growth Starts with an exponential phase But then, due to competlng effects or
Saturation, the exponential shape is flattened off, described by the followlng equation
whereas
p, is the final Potential to which growth will develop
a is constant and equal to the initial the growth rate, and
6 Offen also referred Io the teim logistic growlh (Bader and Bacclnl 1996)
36
t gives a mldpolnt tlme of the s-shape curve.
Figure 2.10 gives examples of three different sigmoidal shaped cutves, with growthrate factor a varying from 10. 15 and 20% per year. Extensive analysis have been
made on growth pattern for all sorts of Industrlal and non Industrial growth processes
(Peterka, 1977). Evaluation of this data do provide a good support to valldate whether
the assumed growth model and tlme span for explolting the potentlal such as PV
Systems In Switzerland Is reallstic.
Growth rates of 10 % per year are common In the Industry. As can be seen in Figure2.10, small growth rate needs much longer tlme, or wtthin a predetermined time span, it
already Starts above zero, which means that development has already started
somewhere in the past. Growth rate of 20% per year are also feasible, but it is seldom
that growth rate > 20% per year occur over longer tlme perlods.
5 10 15 20 25 30 35 40 45 50 55 60
Figure 2.10 shows typical sshaped sigmoidal growth rate curves for three different growth
rates a (a = 0.1, a = 0.15, a = 0.2 per year] and fo = 30 years.
It has been assumed that Implementation of PV will not compete on a market level with
other technologies. In a future work, when the methods will be applied to simulate the
metabolism of an entlre energy supply System, competing elements may be
considered. Such competing elements may be the competition between solar
thermal collector and PV solar electric System due to the limited surface area
available on roofs, or the use of biomass for transportation rather than using biomass
for stationary cogeneration. A method to assess growth when competing options are
present is described in (Fischer, 1970).
24.2 Calibration of the part with the materiell assumption
Some of this parameter functlons are given as a ratio between two different masses.
The reference Is the mass of the welght of frontglass, because this Is a value which is
likely not subjeet of change over the considered timespan. Furthermore. It is assumed
that the ratio of weight to surface will also remain constant, which is a reasonable
assumption, if frontglass will remain 4 mm thick on average, and glass will remain the
choiee in the future to make frontcover of PV modules.
P,(t): Amount of glass in building
37
The glass flow in the bullding has been used as a basis to better evaluate the glass flow
in the PV Implementation scenario Today, still a large fraction of glass In the building is
pull glass whlch Is being replaced at high rate of 62000 t/a by floatglass Substitution
has been assumed by a sigmoidal growth rate model, and a slight Increase of the
window inventory has been assumed, which is responsible for the linear term p,, This is
due to the assumption, that In future there will be more Windows per building, and a
sllghtly increase of building Inventory
Pl1+Pl2f
'l+e-p>-»ct-p")piW=. -clft-t.) • linear/slgmoidal
p,, = 1326 106 kg ; p, 3 =0.1482/year
p,2=08843 106 kg/year ; pM=2013/year
• P2(t) Installation of PV plants
The Implementation of PV plants will be accordlng to a sigmoidal growth model
Growth has been assumed to have started in 1990, and an Implementation phase of 60
years (two generatlons) has been assumed The growth rate has been assumed to be
15% per year
Development of PV-plants
P2(t)-P21
l+e"p"(t"p«>
p2, = 5129106kg
P22 =0 15/year
Pj.3 = 2025 years
• P3(t) PV frontglass (for PV modules)
PV frontglass for PV modules will be recycled öfter having reached Its end-of-life
cycle It is assumed, that about 50% will be recycled, when the first modules of the
replacements are due (That Is roughly 20 years after the large scale Implementationstarted) Recycling will improve, and it is assumed that the fraction of frontglass beingrecycled will grow up to 80% within the next 60 years
P3(t)-P31
p3,=08
932 = 0 1/year
p3J=2025 years
• P*(f) Fraction of module weight to BOS matenal
As will be dlscussed in chapter 2441, a spllt of PV plants on tllted and flat roof is
assumed For the 2 appllcations, two existing mountlng technologies have been
assumed Actual average weight has been calculated and put into relation with
module weight, assuming that frontglass will remain 4 mm thick, and assummg glass will
38
remain the matenal of choice (As dlscussed in chapter 3. the results will not change, if
either of this assumptlon will change In the future The energy requirement for this
processes is marginal, and changes in this assumptions may have Impact on costs,
which are beyond the scope of this study, but not on energy flux)
Therefore, it follows
• P5(t) Module manufacturlng yleld
P6(t) = p61+p62 t
Rsi= 1
• P6(t) Transfercoefficlent for recyclmg of frontglass
p Cf> -6]
p6,= 05
p62=0l5/yearp63= 2025 years
• P,(t) Fractlon of mass of photon absorbing layer to PV frontglass
n W - Pl6 4 Plö 5 e
The values for the Parameters are defined in chapter 24 3, where the values for the
matenal utilisation are given for the process .solar cell production"
• P8 (t) Fractlon of AI + Cu + Polymer to frontglass
P8(t) = p8, e-p»jt
Pei = 0123
pS2 = 0 0037/year
• P, (t) ki(t.t') Transfer function of installed PV-plants
k,(t,t') = — e2o'2
x^SOyears c, =10years N,=Norm
• Piotf) k2(t,t') Transfer function of BOS - material float production
(t-r-T,)'
k2 (t, f) = — e2a'
t2 = 30 years a2 = 10 years N2 = NormIN2
• pn (t) k3(t,t') Transfer function of wlndow glass in buildmgs
39
k3(t, V) = ~ e2o"'
x3 = 30 yearsIN*
a3 =10 years
• Pi2 (t): Yleld cells production
Pl2.1=lp,M=0
• P13 (t): Yield AI + Cu + Polymer
Pl3(t)=Pw +P,32 t
Pl3.1 = 1
Pl3J = fJ
24.3 Calibration of the part with ttie energy assumption
• P,(E> (t): Electricity from hydro
P1<E)(t) = p1)(E)+pu<Bt
P,,^ 120" 10'MJ/yearPu®= 0.1
* 10' MJ/year
• P2(E> (t): Electricity from wind
PfCÖ—n(E)
1+e -pf2(t-pa>
Py(E) = 2.88 '10 'MJ/year
Pa'*>= 0.25/year
PM<B= 2015 years
• P3(E) (t): Electricity from nuclear power plant
P3<E>(t) = P„=.
81.4 for 1995StS2010
75.4 for 2010<t<2011
62.6 for 201 l<t<2012
53.3 for 2012<t<2019
26.5 for 2019 <ts 2024
10'MJ/year
. ??> (t):
Pf(t) =
Electricity from blomass
Pd.l
1+e-p8ff-pS)
P4., <E)= T10'MJ
P4/'= 0.15/year
Pum= 2020 years
40
p(E)m_
P51. Pj4 n(B
61+8-pBo-pB> 1+e-fBa-pB)
Ps4
P6, ® =50* 10'MJ/year P^® =405* 10'MJ/yearP5iE=0 25 MJ/year P65
B= -0 16 MJ/year
P5/>= 2015 years P6/S(B=2030 years
• P6(E) (t) Development of efficlency of cogeneration technology
P6<E)(t) = P?!-pf2 e"pS '
P6,®=055P6/>=0275PM(E>= 006/year
• P7(B(t) Transmission losses
d<bp® =0.0865 pf'=0 1/year
p(E),n=D(E)____P72___M71 ^"
7 w_Mn
i+e-*«^> p© =0.025 p£=2005year
• Pf (t) Distnbution losses of fossil fuei. related to fossil requirements for co¬
generation
Ff(t) = P^> p® = 0035
• P£ß(t) Distribution losses of fossil fuei. related to PV-fossil energy usage for PV-
implementation
P,<E)(t) = P^ p^=0035
• P® (t) Specific electrical energy flux of Float Glass Productlon
P1(o'«) = P^1 p®=066MJ/kg
• P® (t) Specific fossil energy flux of Float Glass Productlon, first coefficient
P,cP(t) = P,(?, pft =4.84MJ/kg
• P/ftf) Specific fossil energy flux of Float Glas Productlon, second coefficient
P,(|)(t) = p{f, pf2', = 15MJ/kg
• P®(t) Electrical energy flux for the process pretreatment of glass recycling
P® Ct) = p,?, pf3>, = 0 036 MJ/kg
• P^I'Ct) Specific electrical energy flux of BOS matenal
41
Pi?(t) = p{?i p|?, = 102MJ/ko
• Pffft) Specific fossil energy flux of BOS material
P,5DCt) = Pil>, p{|)1 = 4 26MJ/kg
• P,(E)(t) Specific electrical energy flux for solar cells
pS>Ct>=lü[<p'6,<B +P^2(E)e-^e,)(p,64<E> + Pl66<EV*"<BV(p167<E> +PlM(E)e-p-e>t)]The factor Vio derives from the fact, that the frontglass material has been assumed to
be constant 4 mm thick over the entlre Implementation perlod This equals to 10 kg per
m2 Smce material utllisatlon Is given In kg per m2, a reduction by the factor equal to
glass in kg per m2 is necessary
Because three dlfferent solar cell technologles (Silicon wafer, sillcon-sheet and thm
film) are considered, the followlng Parameters are defined with three values, one for
each of the technologles Descrlptions are glven In chapter 24 4 3 2
305MJ/kgSi 159MJ/kgSI 015/a Si
pf6>, = 80 MJ/kgSI . p<?2 = OMJ/kgSi , p®3 = 0/a Si-sheet
20MJ/kgSi OMJ/kgSi 0/a amorph
1 6 kgSi/m2
p,= 0 3kgSi/m2 ,
0 006kgSi/m2
04kgSi/m2
p<?5= 0 7kgSi/m2 ,
0 004 kgSi/m2
015/a
pf6'6 = 015/a
015/a
Si
Si - sheet
amorph
1200MJ/m2
p<E„>7= 450MJ/m2 ,
100MJ/m5
618MJ/m2
p<E>B=150MJ/m2.50MJ/m2
015/a
piE4>,= 0/a
0/a
Si
Si-sheet
amorph
where „a" Stands for year
Pif (0 Specific fossil energy flux for solar cells
1P1?(t) = ^[(p,71®+P„/'e-^<!,')(p174<E'+p,76«e-^<E,,)+ (p177<E> + p,78®e-'J«.,B,)]
42
43
technologies.differenttheforefficienciesoflimitupperdefming
parametertheisp^jtimeoverevolvewillcellsolarofefficiencieshowWdefmesp22
0.15'
0.06'
110
PefyeafP®3=0'5007'=P2221=0,7;P22
0.150.07180
P22,(E>-P222tE)e-p-(E,',=PI)(t)
technologiesfilmthinamorphousfor11%andwafersheetSifor17%Si-Cz,for
18%betoassumedbeenhaswhichlimit,upperantowardslineasymptoticanalongmovmgareefficienclesafterwardsthatanddecades.twonextthewithinmadebewill
progresstheofmostthatassumed.IsItovertime.increosewillefficiencymoduleThe
efficlencymoduleofDevelopmentP&Q)•
51MJ/kg=0p«j>,p2n©=Pi?(t)
trams)boats,(trucks,transportationforfluxenergyfossilSpecificPji'CO•
17MJ/kgp§.,=0P2o,<B=P®(t)
rail)essence(intransportationforfluxenergyelectricalSpecificCt)P|o}•
amorph8.71
Si-sheet8.71MJ/kg=p{|;,
Si8.71
Pl„<s=P<?Ct)
manufacturingmoduleforfluxenergyfossilSpecificP®(t)•
amorph02
Sheet-SiJ/kgM52=PJHii<E)Pia=ft)P®Si4.32
manufacturingmoduleforfluxenergyelectricalSpecificP/fft).•
amorph
Si-Sheet
Si
0.15/a
0.15/ap®9=0.15/a
50MJ/m2p(E>8=100MJ/m2;
MJ/mz49
p(O7=150MJ/m2,170MJ/n-/
amorph
Si-sheet
Si
15/a0
0.15/ap®6=0.15/a
kgSi/rrv'0.004OOOokgSi/m''
0.7kgSi/m'=
5p^;.OSkgSi/rr/
04kgSi/m'!,©
16kgSi/rrr
p17.4.
D(E)
amorph0.15/a'
27MJ/kgSi'
140MJ/kgSi
Si-Sheet0/a=p®3OMJ/kgSi;=p\f280MJ/)<oSI,=p^,Si0.15/a27MJ/kgSi120MJ/kgSI
• p23 ^ Development of the potential of PV Installations
It Is assumed that the potential will be developed within 60 years, along the path of a
slgmoldal growth
pßfyffl!.,, (R P23 2(B P§,=0 95 p®=0C01/yearr23 uvi ;-p23i
~
n <E!/t _ <b\
1 + eP2" l P*' ' pg 2
= 0 2 p§ 4= 2000 years
• P2?(t) Amount of solar energy which is irradiatmg onto the installed PV surface
p(E)(t)= p od_p ©e-PK,»« P(£, = 8136MJ/akgPV pgs=015/a
24 241 242
p24>2=9 73MJ/akgPV
• P®(t) Electrical energy which is used for transporting fossil energy (only the
fraction Is considered which denves from the fossil flux for the PV manufacturmgand Implementation)
Pf(t) = P25® p§,=0015
• P®Ct) Assumed electrical energy Import
Electrical energy is traded with countnes outside the System boundary Switzerland For
reason of better understanding the System response and wrth regard to the goalsstated Import and export have been assumed to be equal. and for the time bemg has
been put to zero
P» « = P26i(E) P»i = 0 10' MJ/year
IAA Detaiied desctiption of selected Parameter functions
Some of the parameter function do need more detaiied explanations in order to make
assumptions transparent This concems especially the explanation with regard to
• Analysis of the potential of PV plants within the selected System boundary(Switzerland) and assumptions how this potential may be exploited
• Definition of technical layout of PV plants and the matenal and energy requirementsinvolved for the selected designs
• Material and energy requirements to manufacture the photon absorbmg layers to
generate the electncity as a function of the selected PV technologies
2.44.1 The potential of PV plants in Switzerland: P2(t)
Switzerland Is a relatively small country densely populated and except for hydro and
minor biomass utilisation, the energy resources are by almost 80% supplied from
abroad In the electrical energy sector - which is of major interest within the scope of
this study - around 539% of the electncity is produced by hydroenergy and is based
on renewable energy source Production from nuclear power plants account for 43%,
and 3 1% from fossil fired generators both subject to environmental concern and
depletion of fuel resources (VSE Bulletin 8/1997)
44
Direct solar radiation vanous wifhm the different climatic zones from roughly 4'000
MJ/m2 x a in the northem part to 5'000 MJ/m2 x a r the southern part of Switzerland The
total Irradiation onto Switzerland amounts to roughly 2 x 10M MJ, whlch Is about 15000
tirnes more than total electrlcal consumptlon of 135 x 1CP MJ In 1996 Up to today, this
huge and renewable resource Is almost untapped
Stnce free avallable surface on the landscape Is rare and its use for technical
Installations to harvest solar radiation will be - wlth some exceptions - too expensive
Integration of PV Systems in the bullt environment presents the hlghest opportunltles for
PV (Gregory 1995. Schnitter et al 1981) And n fact, PV Systems already appear on
rooftops and facades of buildings, parklng lots, hlghway sound barrlers, bus shelters
and other mfrastructure elements So far, this are mostly pilot and demonstration
projects
The question remains how large the potentlal for PV System in Switzerland is, if the
Integration will become part of modern bullding mfrastructure This Potential has been
evaluated in various studies, such as in (Real 1984, Minder 1991) The most recent, and
probably also the most elaborate evaluation of the area available on buildings where
PV plants can eventually be incorporated has been performed by (Gutschner, 1995)
This report does not only provide a very comprehensive overview of existing studies,
but provides clear assumption and system boundarles for building Integration and
Potential surface utilisation, based on Statistical data on buildings
Not all of the identified surfaces have an optimal orientation, which would be facingdue south and wrth an elevation angle of the PV modules of 30" from the horizontal
plane There Is a reductlon in energy production when installations are made on
building roofs which are not optimal orientated or whlch may be shaded partly duringthe day The fraction between energy Output of a PV plant build on an actual
compared to an optimal orientation is deflned as the Energy Yleld Parameter (EYP) EYP
is a measure which defines the losses in energy production taking into account that
very few roofs are directly facing south
It is assumed that in the beginnlng where PV plants are still expensive and non-
renewable energies abundant and economical more attractive than electricity
generated in PV plants, installations will be made on those surfaces, whlch are dosest
to the optimal orientation
It Is therefore assumed, that the initial value of EYP is 095, and decreasing following the
curve descnbed in P^sft) Deviatlons from this optimal orientation will cause a
reduction in produced energy
Minimal
EYP
Losses of energy
production
Absolute surface
area in m2
fraction of buildingsurface in %
m2 surface
per capita
09 10% 46Ü6O000 163 658
08 20% 126'230Ü00 44,6 1803
07 30% 153'150OX) 54,1 21 £8
06 40% 17479CJ0OO 61 & 2497
05 50% 179'92Ö000 63/J 25,70
Tab 2 1 shows absolute values of potentlal surfaces for PV Implementation onto buildings as a
functlon on the energy yleld Parameter EYP or related energy losses due to non optimalorientation of PVInstallations (Source Gutschner 1995)
45
However, as the exploitation of surfaces contmues over the years. more and more
non optimal surfaces must be considered for PV installations Gutschner has
evaluated five different Potentials, which are classified by the energy yield Parameter
(EYP) Lower EYP factor yields to higher losses in energy production, but resutts in more
available roofs and therefore to a greater overall potential to Install PV plants
Within the Simulation made for model verification and assessing metabollsm of PV flux
In Swltzerland, a Potential surface area of 126'23O000 m2 has been selected for the
following reasons
• The average EYP value is still 08 Therefore production losses average out to be
20% from a scenario where all PV Systems would be Installed at optimal onentation
This value has an impact on the energy and materlal flux, because PV plant (or
matenal) utllisation is 20% off optimal Lower EYP values would have further
negative impact on flux and breedmg factors for PV Systems
• As can be deduced from Table 2 1, the value of EYP equal 08 represents a kind of
Optimum Allowmg still lower EYP results in only marginal tncrease in roof area by
large reduction of energy production per unit installed
• The area, which corresponds to roughly 18 m2 per capita, is reasonable with regardto the total roof surface in Swltzerland Furthermore, the area is similar to the are of
artificial hydro reservoir for electncrty production 'and the energy flux from PV can
therefore be easily correlated to the electrical energy flux from Hydro Also this
surface is about equal to the amount of m2 of wmdow glasses buitt in the Swiss
building Inventory2 (Binz 1996)
It has been assumed that in the begmnmg where PV Systems are still expensive
surfaces dose to optimal will be selected flrst With the mcreased use of building roofs
and facades for producing PV generated solar electrlcity. more and more non
optimal surface will be considered Surface split for model construction is 30% on tilted
roofs. and 70% on flat roofs, as suggested by Gutschner
One of the difficultles of the model is the replacement procedure of PV plants after
havlng reached their end of life point It has been assumed that PV plant life time is
around 30 years (gausslan distnbutlon, mean value 30 years) and that installations will
be replaced after this time It has further been assumed, that dunng this time
efficiencies of new installations, based on newer technologies, will increase
When replacmg the old PV plant, the new ones will have higher efficiencies, but will be
installed at the same Site That means, at this very moment, the model has to evaluate
what the assumption are with regard of the new, improved efficiency - but has to
„remember" the old value of the EYP, which has initially been applied for that particularPV Installation On the other hand, new installations will have to be placed on roofs with
lower EYP values, and the model has therefore to distinguish between PV plants which
are made for replacement and for new installations respectlvely
It is assumed, that this development of installed PV plants will follow sigmoldal growthSince Installed power of PV plants is very linear to covered surface area (with the
For the use of hydroenergy, roughly 130*10* m? of free landscape have been transformed
into artificial lakes to generate electnaty
Today, about 65,4* 10« nVof actual wmdowframe carry about 125,1*10» mP of float glass(The value is about double, because in Swltzerland most Windows have double glazing)The selected value of Potential PV surface is therefore roughly the same as actual
window glass surfaces which has been used in the building sector
46
exception, thot over time the efflclencies of the new PV plants will increase) a constant
ratio between surface and Installation welght has been assumed. Wlth reference to
the resurr from the study from Gutschner. it is assumed that 30% of all the Installation are
on flat roofs. and 70% on tilted roofs. For the Installation of flat roof. the Installation typeSofrel has been chosen, where gravltatlonal foundation is applied to avoid
Penetration of roofing material. For tilted roof, a solar tlle which has been applied for
several hundred kW of PV has been selected. The relevant weights are summarised In
the next chapter.
Furthermore, it is assumed that Integration design will remain constant over the entire
Implementation phase. The reason for this simplification is the following:
• Improvements on Installation designs3will have very minor impact on the Induced
energyfluxes and
• Ratio between BOS mass flow and surface exploltation remains constant over the
considered tlme. The development of surface area In m2 or equlvalent in Kgfollows the sigmoidal growth curve. The actual installed power does increase
slightly faster, since efficiency develops over time, and leads eventually to higherpower levels per m2 or installation weight.
The development of the Potential surfaces follows the equation:
. Potential Surface
1+e-«(t-V
where Potential surface is the overall avallable surface evaluated as Potential Sites for
erecting PV plants.
2.4.4.2 Material and energy flux for BOS components: P4(t)
State-of-the-art techniques for BOS have been assumed. Although improvements can
be envisaged, they are not considered for the Simulation. BOS is quite optlmlsed. but ofcourse further improvements can be envisaged.
However, this improvements may have Implications on other factors such as costs,but they will have minor impacts on the results of the energy and material flux analysis:
• It is assumed that flat roofs will be installed using the Sofrel installation method,which is described in (Müller et al, 1995). Sofrel uses frameless modules which are
clipped onto the prefabricated concrete blocks. At present, this is the most cost-effective and efficient way to physlcally Install PV Systems on flat roofs. Simllar
deslgns have evolved, based on the same principal as Sofrel. The use of gravelinstead of concrete to provlde the necessary weight to wffhstand wlndloads mayhave a minor impact on the economies; it has only minor Impact on the materialand energy flux.
Gravel may replace concrete, and recycled plastic to built Supports on flat roof may bethe low cost option for the future. For these options, no sensitivity analyses have beenmade, since these variations have only minor impact on the results and conclusions.
47
• For slant roofs, it is assumed that all Installation will be made usmg a roof tile, which is
descrlbed in (Krause 19%) Itcombines of alaminate which is embedded into a
plastlc frame Agam, other roof tile construction will evolve, but smce changes will
hardly affect results of this analysis, they are not anticipatedUnder the assumption, that 70% of the Potential will be bullt on slant roof and 30% on flat
roof (Gutschner 1995). table 22 gives the overview of major BOS matenal and energy
requirement
MountmgStructure
Potential Material flux Energy
%
Concrete
kg/m2Plastlc
kg/m2Metal
kg/ m2Total
kg/m2Fossil
MJ/kg
Electrical
MJ/kg
slant roof 70 -- 32 23 55 76 23
flat roof 33 873 - 27 90 04 26
Mix
70 % tilted
30 % flat
100 2605 23 23 30 53 17
Table 2 2 shows the summary of materials and energy used for Implementation of PVon Hat and
tilted roofs It Is assumed that 30% of the Installation will be on tof roofs and 70% on tilted roofs
2.44.3 Material and energy flux for making the photon absorbing layer, developmentof solar cell characteristics: P,,® (t), P,,® (t), Pam (t)
Module efficiencies, energy flows to manufacture Silicon, matenal utilisation and
energy flux for electrical and fossil energy to manufacture the photosensitive layers will
improve over tlme Their development is summansed in Fig 211 The plots in the
columns represent the Parameter functions P16lB (t) and P17(E) (t) as follows
1. column. Different solar cell technologies and related energies: P^' (t)
Three Silicon based technologies have been selected for further demonstration of
model characteristics and metabolism analysis Silicon was chosen as the key raw
matenal for PV appllcations for the followmg reasons
• Silicon is abundant and rts availability and price is almost independent of mdustnal
utilisation4 (Availability and therefore costs for other PV matenal such as i e Indium
may strongly depend on mdustrlal volume Large scale usage for PV
Implementation may cause shortage and subsequent nse in costs)
• Silicon is a low-cost raw matenal In mdustnal application, it is used in scale of
100'000's of tons However, upgrading to a level where it can be used in solar cells is
expensive and requires signrficant amounts of energy when applying todaysprocesses, which are deslgned to meet the higher requirements of the electronic
Silicon represents 25,7 % of the mass of the planet's surface matenal Silicon has played an
important role in the civilisation of manland it has been used to make pottery, tools glass
(Rochow.1987)
48
tndustry. More adequate Clearing procedure for solar grade Silicon5 have been
identified (Cormick 1996, Sanjurjo 1996. Nakamura 1998. Menno 1998)
• Silicon is inert and environmental^ benign. Ultimately, it could even be disposed in
landfills without further treatment processes.
Table 2.3 shows a overview of the selected three solar cell options and thelr
associated productlon technologies. The three technologies. described in detail in
(Green, 1992), are:
• monocrystalline Silicon solar cell, based on the Czochralski process. Main Issues
are very high efficiencies on one hand, which are balanced off by the
disadvantage of bad material utlllsatlon of the high purity Silicon, which is used as
the process input material.
• This limitation of the above mentioned ingot approach can be avoided if the
Silicon can been formed directly into Sheets or ribbons. Several techniques have
been developed for achievlng this. Higher material utilisation has to be balanced
off to a somehow lower cell efficlency (Wald 1990. Sachs 1986).
• Silicon amorphous solar cell, which represents within the scope of this study the thin
film technology. One of it's big advantage is that less material is used to form the
photon absorbing layer (Shah 1996). It is assumed that efficlency will reach 11%6.
Even though It is likely that a mix of the three dlfferent PV technologies may be appliedto realise the overall PV potential, simulatlons had been made with either one of the
selected PV technologies, in order to demonstrate sensitivity of the Individual
technology options.
Silicon technology Photon absorbing layer Manuiacturing technlque
crystalline wafer Czochralskl/wafer cuttlng
sheet thin wafer string ribbon, EFG, continuos
amorphous thin film plasma discharge, continuos
Table 2.3 shows an overview of 1he three selected technologies to vertfy Impact on Hux patternuslng dlfferent Silicon technologies such as crystalline. sheet and thh Um options.
The efficlency of solar cell, defined as the fraction of how much of incident solar
radiatlon is transformed into electrlcity, will increase for all of the solar cell technologiesconsidered for this study. It Is assumed, that the monocrystalline solar cells, which result
from the Czochralski process, will lead to highest efficiencies of 18%. Taken into
account.thatalready today modules are commercially available wlth efficiencies in
the ränge of 16%, this seams a very modest projection.
However, the average efficiency value for commercial modules is probably more in
the ränge of 12 to 13 %. The 18% value Is technical feasible. but an ambitious
Solar grade Silicon refers to the amount of permissible impurities, which are tolerable to
make solar cells. Electronic grade requires a higher degree of cleaning of the Silicon than
would be necessary for the solar industry.
Several different fabrication techniques have been investigated such as glow discharge,sputtering and chemical vapour deposition. Recent progress in depositing a
microcrystalline layer may renew the hope that 11 % stable thin film devices based on
Silicon may be feasible (Shah, 1997).
49
projection for an average value for the market The same considerations are of
course valid for the dlscussion of target efficiencies for sheet and thin film
technologies
Making Si solar cell from sheet has the potential of reachmg high efficiencies
Fabrication of solar cells wlth sheet technologies just started, so projections are
difficult Princlpally, it is based on proven Si-wafer technology. and improvements maybe reached for several reason
• The learning curve just started, and further progress may be based on the
experience made In the tradrtional wafer based solar cell mdustry
• Sheet matenal is crystallme, just like wafers, but they can be produced and
processed much thinner, which may be an important factor for improvmgefficiencies Kiess reports on efficiency gains in the order of 4 to 5% when usmg thin
crystallme Silicon solar cells (Kiess 1995)
The efficiency of amorphous solar cells have improved a lot over the last decade
Stabilised efficiency of 8% have been reported (Unisolar, 1998), and the combination
wrth microcrystalline may make amorphous an attractive device It is assumed that
average market efficiencies will reach 11%
2. column. Electrical energy requirements to manufacture Silicon suitable for makingsolar cells:
^©^6.2© e"*16-3 'arxi
3. column. Fossil energy requirements to manufacture Silicon surtable for making solar
cells:
p17 1 +p17 2e
The energy requirement to produce polycrystalline Silicon as the raw matenal is a
significant fraction of the entire energy flux There are two major processes used todayto purify Silicon, and various other possibilities have been pubhshed (Aratani, 1996
Cormick 1995) Kazuhiko has analysed the sensitivity of life cycle analysis wrth regard to
drfferent production technologies and suggest the use of solar-grade Silicon, rather
than electronic grade Silicon (Kazuhiko, 1996)
It is important to note, that the energy requirement for drfferent technologies can vary
significantly In Order to simplify the model, assumptions of used Silicon punfication
process has been adopted from the current use in the mdustry Czochralski process
has been assumed for wafer technology and the raw matenal for the process is
denved from the Siemens process
On the other side, the PV mdustry who manufactures sheets Si matenal7 has denved
their Silicon from the punfication process based on fluorosilic acid, and the energy
So far, two manufacturer exists who make sheet Si wafer ASE Amenca and EvergreenSolar Ine
50
requirement of the process are In the Order of 5 to 7 times smaller8 (Ibrahim, 1993). Data
in the final results will be plottedforthe Si Czochralski technology based on purificationmethods using Siemens process, whereas sheet Silicon technologles will be based on
the fluorosilic acld process.9
There Is no question that, If wcifer technology will be the choice for large PV
implementation, more cost and energy effective purification lines will be Installed than
belng used today as e.g. in the Siemens process. This may happen as the PV Industrywill further continue to grow (Menno 1998).
4. column. Silicon material utilisation:
P16,4(E)+Pl6,5(E)-"Pl6-6t=Pl7.4(B+Pl7.5(E)-"'
The amount of Silicon used to make the photon absorblng layer is very dlfferent for the
three consldered solar cell technologles. Slnce the process to purify Silicon suitable to
make solar cells induces large amounts of energy fluxes, it is important how efficient
the purified Silicon is processed into solar cells.
There are basic differences between wafer and thin film technologles in the aspiration
process: crystalline Silicon is a direct band gap, and needs minimal thickness of at
least 100 micron to absorb the essential part of the solar spectrum. Amorphous Is a
direct band gap material and needs roughly 2 to 3 microns to achieve the same
effects (Green, 1992). Therefore, there is a prlncipal difference of material utilisation
between crystalline and thin film In the order of two magnltudes.
Furthermore. for making wafers, a cuttlng process Is required to transform ingots into
wafers, and the associated curve losses are 300 micron. Even if in principal 100 micron
would be enough to absorb the solar spectrum, today's manufacturing technology Is
based on 2S0 to 350 microns, because manufacturing yields drops when sawlng and
processing wafers below 250 micron is envisaged. It has been assumed, that in the
future curve losses will not fall below 293 micron, but wafer thickness as low as 200
micron will be used for solar cell manufacturing (Dyne Corp. 1996)
Processes which produces a sheet out of the Silicon melt instead an Ingot and then
slice it into wafer do not have curve losses. Some of them have also the Potential to
manufacture sheet as thin as 100 microns. An average of 150 microns with 95 yield has
been assumed for the long term goal for sheet technologles. Thin film, such as Si
amorphous technology are produced using a depositlon process from a plasma.Today, yield of Silicon is as low as 40%, but improvements of up to 80% has been
assumed for long term projectlon.
Essentially 90% of all polycrystalline Silicon is produced by high temperature depositlon,
using trichlorsilane as the Silicon source intermediate. About 10% of of the polycystallineSilicon production is based on fluorosilic acid, which is converted into Si tetrafluoride, then
to silane before undergoing decomposistion in a fluidized bed reactorto produce granulärpolycristalline Silicon. A fluidized bed reactor is energetically much more efficient than
conventional deposition reactors.
Historically, ingot manufacturing so far has been based on Silicon chunks, whereas
automatic ribbon manufacturing has been designed using high purity granulärpolycrystalline Silicon produced by a process originally developed by Ethyl Corporation,Pasadena, Texas. The process is commercially operating at a level of above 1000 tons per
year.
51
5. column. Electrica! energy requirements to manufacture solar cells:
^6.7^16.8® °-fW
6. column. Fossil energy requirements to manufacture solar cells:
Pl7,7(E)+P17,CE)e"Pl7-9tThe processes to manufacture solar cells have in detail been analysed and
described and data for involved energy requirements have been pubhshed
(Hagedorn 1992, Hüne et al. 1991, Nleuwlaar 1997, Vaucher 1993) Column 5 and 6
shows the trend of energy requirement per m2 to process solar cells.
Electrlcal Energy Fossil Energy Material
utmsatlon
kg/m2
Elektrical Energy Fossil Energy
Modute EfflclencyforS-Material
Processing
fbrSI-Materlal
Processing
for Cell
Processing
for Cell
Processing
MJ/kgS,Ofe MJAgS MJ/m2 MJ/m2
02t 500 T 150 t 2 -.200
Tech 01
r 400
300
200
^_1
0
100 ^_200 \
(f 100
Hl 0 J MIHI 0 lllllll 0 1 ii in 0 4-HH-H
1990 2050 1990 2050 1990 2050 1990 2050 1990 2050 1990 2050
0 2-r 100-ran
100T 1 0
j600 t
800 "V
s 01r
00
SO
4050 0 5 l 400 400 •
Ol
V 200 200
ä 0 +H+tH 0 J+h+h 0 +++++I 0 0 U++++H 0 -H-H-H 0 MH+H
1990 2050 1990 2050 1990 2050 1990 2050 1990 2050 1990 2050
3
°2130-
20-JO
150 0 01 -
L_150
^
200 -
0 1 -Ir~ 10-
100
n0 00
,,...*
1990 2050 1990 2050 1990 2060 1990 2050 1990 2050 1990 2050
ßgure 2 11 shows an overvlew of the assumed development of electrlcal and fossil energy
requirements and matertalutmsatlon for Sl-crysfalllne. Sl-sheet and Sl-amorphous technologlesParameters cra deflned h chapter 2443 Itls assumed that most of the predlcted progress will
be acNeved Inthenrst20 years, and that afterwards rate of Improvements will slow down
24.5 Electrlcal energy Inputs
In order to simulate the entire development of electncrty, assumptions on future
electricty generation from the various sources such as hydro. wind, biogas. nuclear
and cogeneration have been necessary. Thls predictlons have been evaluated and
pupllshed by other experts. In order to make the results more transparent, assumptionsof these developments are given below
52
2.4.5.» ElecMcity «rom hydro: Pf(t)
Within the considered System boundary of Swltzerland, the Potential of hydro Is almost
explorted to rts final Saturation.
A slight linear increase has been assumed. based on analyses given in (Prognos 1996,SEV Bulletin 2/1997). Figure 2.12 gives average values, extrapolated from the past.Annual production can of course vary substantially. as it has In the past (SEV Bulletin,
12/1997).
109 H
100
50
01!
J/a
90 2000 2010 2020 2030 2040 2050
Rgure 2.12 shows the assumed development of e/ectrlclty production from hydro power h
Swltzerland. Within the considered System boundary of Swltzerland. the potentlal of hydro Is
almost explolted to /te Unat saluratlon. A very slight Increase has been assumed.
2.4.5.2 Electricity from biomoss: P4(E)(t)
Estimates indicate that Biomass is a very promising renewable energy source and
could supply primary energy in the ränge of about 40 to 50'IO9 MJ/year. So far, this
Potential is almost untapped. With regard to electricity, this amounts to an annual
production of about 10*10* MJ 10.
Although the Potential of biomass utilisation Is undoubtedly large, yet no clear pictureexists on the technologies which will finally be involved to harvest this renewable
energy. It is assumed that growth to explolt the Potential of 10*10* MJ/year will be
sigmoldal, and implementation of the Potential will take place within 30 years.
Estimate Summary by M. Hinderung from Federal Office of Energy to M. Real of 30.4.1997.
53
10" MJ/a
10
5
.
ß 90 2000 2010 2020 2030 2040 2050
Flgure 2.13 shows the assumed development of potentiell of electrtclly productlonbiomass.
from
The Interest in Switzerland for biomass energy Covers a variety of different
technologies including anaerobic digestion of agricultural waste, gross and other
energy crops as well as the use of wood. The Swiss non-fossil fuel Obligation (NFFO) has
stimulated interest of the administration in biomass energy."
Biomass can be transformed into electricity by various means such as:
• gasifying in anaerobic digestion which has been around for over 100 years and is
technically well proven'2. Its application, however. to agricultural waste has so far
not been economlcally viable. This also includes the use of agricultural residues
such has the combustion of dry animal litter or straw. and the anaerobic digested
wet manure to produce the energy rieh gas13.
• Burning wood and powering conventional steam turbines14
• Gasification of wood. to power steam turbine or to produce methanol (Stucki et al.
1995).
• Production of electricity from ethanol which is derived from biomass (Grass. 1997).
Conversion could be performed in combustion engine, but efficiency would be
much higher if advanced fuel cell technology will be used16.
On June 26, 1996. the Swiss Bundesrat declared in his message about the new agriculturallaw that the Föderal State favours implementation and utilisation of biomass.
Under the trade name „Compogas", an industrial process is beeing marketed and
operates on biogenic munieipal waste.
Various demonstration projeets on farms such as the projeet from Kaspar Günthard, {armer
in Döllikon. Installed in 1993, he gasifies residues of about 900 m3 of liquid manure and
about 12 m3 of residues of vegetables into roughly 460'000 MJ electric power and over 1
Mio MJ of thermal power, of which about 700'000 MJ are used in a mini thermal distribution
grid. The System works about 5'000 hours per year.
Die Genossenschaft Energieversorgung Ormalingen (GEVO) has built a pilot plant with an
electrical generator capacity of 145 kW. The Potential for this technology for electricity
production has been estimated by (Pauli. 1995) to roughly 7,9 x 109 MJ electricity per
year. utilysing about 5 millions ms wood.
54
Technical issues and limited numbers of demonstration projects have so far keptbiomass out of the focus as a potentlally large renewable energy source. Factors such
as biomass energy costs. lack of secure market, supply chains, public perception and
environmental concerns still Influence the uptake of biomass for energy.
A future biomass industry will embrace farming, forestry and energy, each
representlng spread sectors operating within divergent cultures. Although, onlyrepresenting about half of the Potential, wood from natural forest Covers most of the
utilised potential today. Most of the wood Is used for heating, and wood Chips in
Switzerland have reached a semHndustrlal level for heating Systems.
Finally, the use of biomass for electricity production may strongly compete wlth the
use as blofuels for the transportatlon sector (Dinkel and Real, 1998). The advantage of
using biomass for electricity production is its potential application in cogeneratlon,where heat and electricity can be used. Furthermore, cogeneratlon of ethanol in fuel
cell achleves high converslon ratlos from ethanol to electricity, and has already been
demonstrated. Comblned fuel cell/steam turbine cycle may achieve electrical
efflciencies up to 70%, which would make it very attractive for cogeneratlon (Maru,
1997).
245.3 Electricity from wind: P/'ft)
Within the scope of thls work, a potential of 2.9 x 10* MJ/year of electricity productionhas been assumed, whlch represents roughly 50 % of the overall potential, addressedin the lotest study by the Federal Office of Energy, carried out by (Buser, 1995).The
report address an Installation potential for wind turbines of 1 '565 Megawatt.
Prognos has assumed in scenarlo 4 a yearly production by wind energy of 4.27 x 109 MJ
(Prognos, 1997). Still, the reason for having chosen only 50% of the evaluated potentialis arbitrary, but when reviewing the study, it seemed that many of the potential Sites for
erectlng wind turbines where indeed very dlfflcult to access, or may pose aesthetic
Problems, such as the Installations of wind turbines on exposed mountain peaks.
10'MJ/a
3
25
2
1 5
1
05
0
1990 2000 2010 2020 2030 2040 2050
Flgure 2.14 shows the assumed development of electrical energy from wind turbines h
Switzerland,
A 2 MW pilotplant from Energy Research Corp., built in Santa Clara, Ca has demonstrated49.5% conversin efficiency, using natural gas. Similar results have been demonstrated,using 30% dilute ethanol from biomass (Patel, 1997)
55
Wind power Is now the world's fastest growing new energy source based on
renewables. Within a decade, global wind power generating capaclty rose to almost
7'000 MW. Over this time period, a grow rate of 20% has been achieved. Although wind
power still generate less than 1 % of the world's electriclty, the rapid growth and steadytechnology advance of wind power suggests that 1t could become an important
energy source for many natlons within the next decade (DEWI. 1997).
Wind power is being propelled largely by its environmental advantages as well by its
decrease of the costs per kWh produced durlng the last decade. In fact, in many
regions wind power Is now competitlve with conventional power plants. As wind
turbines are further improved, with lighter and more aerodynamic blades as well as
better control Systems, and as they are produced in greater quantrties, costs could fall
even further, maklng wind power one of the world's most economlcal electricitysource. In Switzerland, political support for wind power waned in the lote 1980s, and the
development of an advanced wind energy technology16 was stalled. World-wide,
however, the technology continued to mature.
It Is Interesting to note that unlike in the United States, where most development has
consisted of large groups of up to 100 and more turbines - called wind farms - countries
in Europe have pursued more decentralised approach to wind power development.Most of these machines are installed one up to 20 at a time, across the rural
landscape. Similar Implementation pattern has been assumed for harvestlng the wind
energy potential in Switzerland, where the interest in wind has re-grown in the recent
years. The fact, that up to 70 % of the energy would be produced durlng the winter time
makes wind even more interesting for Switzerland.
2.4.5.4 Electricity from nuclear: P3(B (t)
It Is assumed, that nuclear power plants will not be replaced, öfter they have reached
thelr end-of-life cycle. Since a 43 year life time has been assumed for the operatlngnuclear power plants. electricity from nuclear will decrease, as shown in Figure 2.15.
Detalled data are gfven In the parameter functlon P,(E' (t).
10»MJ/a
90-
80
70-
60-
50-
40
30-
20-
10-
ol . 1 . . . 1 . 1 . 1—
1990 2000 2010 2020 2030 2040 2050
Figure 2.15 shows the development of electricity from nuclear power h Switzerland. If no
replacement of outphaslng nuclear power plants after thelr end-of-llfe time of 40 years &
assumed.
In 1988, one of Europe's largest operational wind turbine was installed in Martigny. The
technology was developed by Swiss consortium led by Alpha Real AG in Zürich. Initial
research was sponsored by the National Energy Foundation NEFF. Loosing interest in the
wind energy has cut further support to almost zero and has stalled further development of
a Swiss wind power technology.
56
2.4.5.5 Electricity from cogeneration: P5(E)(t)
Cogeneration is a type of electrlcal power generatlon. where both electricity and -
otherwise wasted - thermal energy is used. Within the model. cogeneration is fossil
fired, but blomass fuels may be applied m the future as well. The comblned use of
electricity and heat makes cogeneration efficient and cost-competitive with large.central thermal power stations.
In Switzerland. the introductlon of cogeneration accounts for about 0.5 x IO9 MJ (VSE
Bulletin 8/1997)'7. which represents about 3 % of the total electricity produced.
Results of newer studies Indicate a large Potential for cogeneration capacity (Gubser,
1996). Gubser has evaluated the potential of 245 x IO9 MJ, under the assumption that
only cogeneration units wtth a minlmum power level of 8 kW and above will be
installed, representing a total of roughly 240ÜOO installations. Similar figures are also
published within studies sponsored by the Swiss Federal Office of Energy (Prognos,1996). This Report elaborates three different scenarios, wlth each scenarlo having four
variatlons and each Variation having Iwo options. Within the total of 101 different
configuratlons of energy mixes offered, the highest value for cogeneration has been
estimated to be 24 x IO9 MJ/year.
Within the scope of this study. It has been assumed that cogeneration will grow until the
2025to about 30 x IO9 MJ/year. It is assumed that after this time. costs for fossil based
gas and oil will increase.due toworld-wlde increased demand and possible COjtax.The decrease has also been assumed, because cogeneration. if powered by fossil
energy, is based on non-renewable energy. and it's growth can only be temporär/, to
Substitute outphasing nuclear.
10'MJ/a
351
30-
25-
20-
15
10-
5
0-
1990 2000 2010 2020 2030 2040 2050
Flgure 2.16 shows the devetopment of electricity from cogeneration h Switzerland. A strongIncrease h Ihenext decades Is assumed. because low fossil fuel costs and new. Hgn efficient
technotogles will make comblned thermal and etecWc energy productlon cost competltlve, It Is
further assumed. that after Ihe year 2025, Increased world market demand comblned whh
lower productlon due to beglnnlng of depletlon of low cost gas and fossil fuel u* have an
Impact on price. and will consequently reduce electricity from cogeneration.
Statistical data provided in the Annual Yearbook by VSE/BEW and the aggregatesdifferent emerging technologies under the subtitle "Others". Accoräing to H. Pauli, Dr.
Eicher + Pauli AG, cogeneration accounts for about 2.0 TWh in 1996.
57
3. Results
The results of this study provide insight into the metabolism of the large scale
implementatlon of PV plants In Switzerland, and identify potential critical material and
energy fluxes and its relationship to the selected implementation time frame and the
selected PV technology. The model described in Chapter 2 can be used to simulate
the long term development of solar energy supply Systems. The model's equationshave been implemented in the Computer program S/MBOX (Bader and Scheidegger,1994). For each set of Parameters and parameter functions SIMBOX solves the System
equations. The parameter values are deflned in chapter 2.4. For some of these values
variations have been simulated to assess its sensitivities to material and energy fluxes
3.1 Material flux
3.1.1 Growth curve and induced material flux
Figure 3.1 Shows the assumed development of the inventory mass as a result of the PV
plant implementation and the associated induced flux of material to built the PV plantsThis flux is mainly dominated by the BOS material. The needs for front glass account for
about 25 % of the total material flux. Since the actual photon absorbing mass is only a
minor fraction of the PV plant's, the material flux In Figure 3.1 Is almost independent of
the PV technology selected.
Figure 3.1. Assumed development of PVplants In Switzerland (left graph). and the associated
Induced flux of material requ/red to fmptement the PV plants (righf graph). Variations h
Implementatlon tlme are shown. The smooth curve corresponds to an Implementatlon tlme of 60
years. Implementation wilhh 30 years leads to overshootlng at the hlghest growth rate. (Allvalues are h lff kg).
The upper limit of the growth is discussed in detail in chapter 2.3.3.1 and 2.4.4.1. The
installed array surface area is about 126 * 106 m2. which corresponds to an installed
mass of PV plants of approximately 5.000" 106 kg. Approximately one quarter of that
mass is glass, and 64% is associated with concrete. Concrete is used to provide
Support and mass for PV plants on flat roofs, slnce this weight is required to counter the
force of wind loads. From the graphs, the following can be concluded.
• A 60 year implementation time provides a smooth growth of flux with only minor
overshooting occurs. Since the mean value of the transfer function of PV plants(which is equal to the average of their expected life time) is 30 years, the flux does
not stabilise, even when the final exploitation of its potential has almost been
58
reached in 2050. The steady State flow of moterial whlch is needed to replace the
PV plants after they have reached the end of their llfe is only marglnally smaller than
the maxlmum requlred to supply the large growth period around 2025.
• A faster Implementation rate of 30 years leads to high growth rates around 2010
where the fluxes of moterial are substantially higher lhan during the steady State.
With regard to the necessary flux of solar cell moterial (purlfled Silicon) and front
glass. the induced materlal fluxes could be slgnlflcant. as will be dlscussed In detail
in the next two chapters. For other components such as concreto or polymers this
additional flux is negllgible compared to the existing fluxes in Swltzerland. For
example, In the case of concrete, the highest flux is around 2010 (assumlng a 30
year Implementation phase). and Is equal to approxlmately 318 • 10* kg/a. Uslng
today's fabrication technique. 16% Is cement, equal to 50* 106 kg. This
corresponds to approxlmately 1% of the Swlss cement production in 1994. Thoughthis is a lot of cement, in terms of an industrial scale it is far from being a constraint. In
1994 the cement production in Switzertand was 4,3 million t, and In 1995 3,9 mllllon t.
This change of 10% in the cement industry is a much larger fluctuation than that
whlch would be induced by making Supports for PV plants during the largest growthtimes.
Since concrete Is more difficult to recycle than gravel, designs for module Supportswhich are based on gravel instead of cement blocks as the mass to counteract wind
loads are preferred. In fact, such designs have been Introduced as demonstration
projects (Eternit, 1997; Ecofys, 1998). Furthermore, gravel Is already used today on flat
roofs, and the new designs using gravel for mass do not induce more flux of gravelthan is needed now. Slnce only a minor energy flux Is related to this topic, no sensitlvitycalculation was made to analyse the energy impact of these deslgn changes.
3.1.2 Flux of purified Silicon for solar cell production
Figure 3.2 shows the change in Silicon requlrements for the three different solar cell
technologles. The flux is highest fbr the wafer based solar cell technology, whlch Is
confirmed by comparing the data for moterial utlllsatlon as shown In Figure 2.11.
Figure 32. Change tnthetluxof purlfled sScon for solar oef production. The amal flow rate Is
highest for crystallina wafers. andlowest for Silicon amorphous technology. The left graph shows
a 60 year Implementation tlme: the itght graph Is for 30 years. (AI values are shown h I06kg/year).
The manufacturers of Silicon solar cells rely forfeedstock materlal aimost exciusivelyon various forms of Silicon residue generated by the semiconductor Industry. Roughiy
59
10% of the Silicon produced does not meet the high Standards required by the
electronic mdustry and can be used for making solar cells Table 3 1 shows forecasts of
purified Silicon growth rates for the semiconductor industry(what does Vith their
requirement" this mean?)
Year Polysillcon requirement In tons Year by year growth rate
1995 12'200 14
1996 14Ü0O 9
1997 ^S2!X) 8
1998 16500 8
1999 17'800 12
2000 2O000
Table 3 1 Protect development of purified Silicon productlon world-wlde Actual development
may have slowed down compared to projecflons possibly also due to the economlcs ti Asla An
Interesting nofe Is the assumed growth rate ofthe Industry whlch has to provlde the purified Silicontts average growth rate Is about 10% (Dyne Corp 1996)
If one, very optimistlcally, would assume that the electronlcs mdustry would continue to
growat 10% annually, then the productlon of hlgh-quality feedstock would be around
210000 tons In the year 2025 The residue for the solar Industry would then be around
20000 tons, whlch compares with a demand in Switzerland alone of 3500 tons in the
year 2025, if the scenarlo would be based on Si-wafer technology The shortage in solar
grade Silicon Is obvious
The remedy for this shortage would be
• Avold the appllcation of solar cell technologles with low Si-material utillsation, such
as wafer-based solar cells The flux of purified Silicon required for crystalline Sheet
and thin film technologles Is several Orders of magnitude smaller
• Evaluate the Status and Potential of alternative technologies for manufactunng PV
Silicon feedstock by modelllng candldate processes and performlng milestone-
drlven Incremental evaluatlons of pllot-scale programs to verify technical, energyand cost objectlves
3.1.3 Flux of floatglass
The flux of floatglass may present a cntical path when considering the large scale
Implementation of PV plants n Switzerland To assess the importance of the flux of
floatglass Into the PV Subsystem, the flux of window glass wirhin the building sector is
included in the model This has the advantage that the glass flux in the PV Subsystemcan be compared with the flux of an already existing market sector
The flux of glass, both to the building and to the PV sector, is determined by the overall
Potential and the estlmated life time assumption, expressed in the transfer function
The Potential for glass In the building sector Is known (Binz, 1995), and a yearly increase
0,5 % has been assumed
Flgure 3 2 shows the comparison of the glass flux into the building sector (window glass)and to the PV plants (front glass) After nearly reachlng steady State, the fluxes for the
two market sectors would be almost the same Thus the PV sector will need
approxlmately the same amount of glass as is used in the building market This is
60
significant, but by far not impossible. It would require the capacity equal to a thlrd of a
new modern float glass line1.
tO« kg./a70
60
50
40
30
20
10
1990 2000 2010 2020 2030 2040 2050
Flgure 3.3. The development of glass thjxreqjred forthe bullding and PVsectors. Amean value
for Ute time of 30 years for both wlndow and front glass fc assumed, Values are calcutated for an
Implementation time of60 years. (Note, äff values are gtven In 106 kg/year).
Remedies may be In replacing glass by plastic transparent materlals or by developingmodules which use a thinner front glass. The actual base line for the Simulation
assumes floatglass of 4 mm thlckness. Modules may be developed which use a front
glass of 3 mm or less. Such constructlon may be obtained by making the laminate of
the module more robust. I.e. by using thicker plastic backskin materlal.
Furthermore. the Substitution of front glass by polymers, advocated by various
companles in recent years, may reduce the induced materlal flux, slnce polymerswould be much lighter than glass. The analysis of thls Option has not be done, slnce tf
would not significantly change the results of the energy analyses. It would thoughreduce induced materlal flux by about 20%. Furthermore, although progress In
polymers have been reported (Plesslng, 1998), doubts for long term stability are still of
major concern2.
Two major factors may influence the flux of glass needed for PV plants: the assumed
life time and the time span in which Implementation of the PV scenarlo would take
place. These values are defined in the transfer function of the process of the PV plants(Box 9).
In order to provide a better insight and understanding of the Impact of these factors of
the transfer function, two sensltivity analysis have been performed:
• investigate the influence of induced flux of floatglass to the process PV module as
a function of its assumed lifetlme, and
• analyse the Impact of the assumed time span for the large scale implementationof PV plants.
Euroglas, yeariy production of about 150'000 tons of one float glass line. Data from Glas
Trösch AG.
'There is no polymer with zero moisture permeability", quote from DrJ Hanoka, 1998,
Evergreen Solar Inc.
61
Floatglass for PV implementation
Floatglass for Buildings
3.1.3.1 Glass flux as a functlon the assumed lifetime for PV modules
Uncertainty exists regardlng the assumed lifetime of PV plants. Since PV modules
dominate the costs and geometrical size of a PV plant, the module lifetime determines
the plant lifetime. There may be the need to replace other components during the
plant lifetime, such as Inverters, but this Is by no means a lifetime determining action.
There are good reasons to assume, that modules will last 30 years, but the influence of
a shorter lifetime on the flux of floatglass is analysed within this chapter. (In fact, the
uncertainty on the assumed lifetime has been addressed by assuming a Gaussian
probability distribution with a mean and Standard deviation, as explained in chapter2.3.3.1. Therefore variatlons on the assumed lifetime address the Variation of the mean
value of the lifetime.)
A shorter average life time does induce, of course, higher glass fluxes into the process
PV module productlon, since replacement would occur more frequently. Figure 3.4
shows the effect of the flux offrontglass, if the mean value of the lifetime of PV modules
changes from 30 to 20 years.
70
60
50
40
30
20
10
1990 2000 2010 2020 2030 2040 2050
Flgure 3.4.7?ie tluxof floatglass Into the process module productlon for an assumed mean value
llfe time of 30 and 20 years. (All values are gh/en In 10* kg/year).
As can be deduced from Flgure 3.4, the additional flux needed If the average module
lifetime is 20 instead of 30 years is significant, and has an impact especially during it's
steady State phase. This phase is mainly given by the flux to replace out of function PV
plants.
The remedy Is clearly to drive the technical development towards longer lifetimes.
Crystalline Silicon (wafer and sheet options) has a competitive edge over thin film,
because lifetime issues are still to be Investigated for thin film options, where crystalline
technologies have almost proven thelr high lifetime capabilitles.
3.1.3.2 Glass flux as a function of the Implementation time for PV plants
The induced flux of floatglass into the process PV plants is significant, and roughlywithin the same order of magnitude as the flux of glass in the building industry. This
requires substantlal enlargement of float glass production capabilities for the
implementatlon of PV. For PV plants, and therefore for the front glass, an average life
time of 30 years has been assumed. Sensitivity as a function of life time has been
discussed in the previous chapter.
The effect of changes in the assumed implementatlon time of PV is of great interest. If
PV implementatlon should take place within - for example - 30 instead of 60 years, the
62
Variation of assumed
PV-plant lifetime
fluxes of all materlals will strongly Increase during periods of hlghest growth tlme. The
higher need for floatglass requlres a substantlal enlargement of floatglass productioncapaclty. In fact, the maxlmum capaclty would be more than double the steady State
value of float glass needed for the buildings, and the enlargement of float glasscapacity would be needed much sooner, as can be deduced from Rgure 3.5.
Wk9/aFfOnt9lass90
80
70
60
50
40
30
20
10
1990 2000 2010 2020 2030 2040 2050
Rgure 3.5. The Variation of Hoat glass needed torPV.If expto/to/ton of ffls potenllal wtil take place In
30 Instead of 60 years.
Thls effect is significant for the needs of glass, because it must be assumed that similar
development will occur all over Europe. Of course, stronger limltations will occur from
the supply of Silicon feedstock material rather than from the large need for floatglass.as discussed In Chapter 3.1.1. The growth of glass Is more easlly achievable. becausethe industry is already at a very high productivtty. Purifying Silicon, on the other hand. is
rather a small and young industry, where about 10 companies world-wide produce ca
15.000 tons/year.
3.2 Energy Flux
The energy flux is of key Interest in assesslng the Impact of the Implementation of a
new energy technology. Thls is also especially Important for plannlng a new energysupply structures, where energy technologies based of non-renewable sources shall
be replaced by such technologies based on renewable sources. With regard to the
discussion of the result, the following questions are of interest:
• How much energy can be produced by PV, and how does the production evolve
over time?
• What is the impact of different PV technologies on the energy flux pattern,especially regarding its breeding potential
• How does the implementation time of PV impact on energy flows and breedingfactors?
• How much energy can be supplied to the loads if energy supply is based on
renewables?
3.2.1 Discussion of electricity production by PV
The amount of electricity produced by PV in a country like Switzerland depends:
• on the assumed potential. in essence given by available surfaces on roofs, towhich PV can grow. and
• the employed PV technology, with whlch the potential is realised.
63
10»MJ/a
70
60
Solarelectricity
wafet>^^—
x^sheet
A /^thin film
^A1990 2000 2010 2020 2030 2040 2050
Net Solarelectricity
1990 2000 2010 2020 2030 2040 2050
Flgure 3.6. The development of absolute electrlclty production (left graph) and of net electrlcltyproduction (rlght graph) for the three dlfterent PV technologles: crystalllne wafer. sheet and
amorphous thlnflm. (All values are gb/en In 1(P MJ/year).
As can be deduced from Figure 3.6, the net electrical Output (right graph) Is smaller
than the absolute production (left graph), because the necessary electrical energyneeded to make the PV plants is taken into conslderation. In thls sense, the net
electrical Output is the result of the breeding capacity of this electrical energy
produclng technology. Reasons for the values of the assumed Potential has been
given In Chapter 3.1.
In Chapter 3.2, the PV technologles which are considered are descrlbed; Silicon wafer,
sheet and amorphous thln film technologles. The effects of potentlal production are
directly related to the efficlencies of the different technologies. Assumption are givenin Chapter 3.2.2.
3.2.2 Variation of Implementation Hme lor energy flux requirements
Figure 3.7 shows the electrical and fossil energy flux required to manufacture, transport,install and dismantle PV plants (pre treatment steps are included) for the three PV
technologles, based on wafer, sheet and thln film.
10"MJ'a
10
Electricity for PV
\wafer^
——<sheet
_^thmfilm
1990 2000 2010 2020 2030 2040 2050
10»
ior
Fossil Energy for PV
1990 2000 2010 2020 2030 2040 2050
Figure 3.7 shows the energy fluxes wlthln the electrical and fossil energy alstrlbution for PV for the
three PV technologles considered: crystalllne wafer. sheet and amorphous 1hh flm. The
Implementation phase Is 60 years. (All values are given In irfi MJ/year).
64
4.
Appendix
In
shown
are
PVtechnotogy
film
tNn
and
sheet
for
ResL/ts
technology.
forwerterbased
glven
are
3.8
ofFlgure
Values
30andä0years.
of
times
Implementallon
assumed
two
the
to
corresponds
flgure
IndMdual
per
graphs
n*o
77»
MJ/year.
70°
In
gtven
are
Values
Iransportatlon.
for
as
well
as
production
component
BOS
module.
cell,
as
such
processes
IndMdual
the
Into
Input
energy
fossil
and
electrical
of
development
the
shows
3.8
Rgure
2050
2040
2030
2020
2010
2000
990
2)(E
12Float
for
Energy
Fossil
2050
2040
2030
2020
2010
2000
1990
7)(E
l2BOS
for
Energy
Fossil
2050
2040
2030
2020
2010
2000
1990
2050
2040
2030
2020
2010
2000
T990
12345r
(E,2)
PV
Float
for
Electncity
2050
2040
2030
2020
2010
2000
1990
(E„)
BOS
for
Electncity
2050
2040
2030
2020
o'201
2000
'990
3)(E12
Cells
for
Energy
Fossil
5
2050
2040
2030
2020
2010
2000
T990
1234
8)(E
12Tr
ansp
ort
for
Energy
Fossil
_
2050
2040
2030
2020
2010
2000
990
4)(E12
Modul
for
Energy
Fossil
2050
2040
2030
2020
2010
2000
T990
2050
2040
2030
2020
2010
2000
1990
(E,8
)Transport
for
Electncity
2050
2040
2030
2020
2010
2000
990
(E14
)Modul
for
Electncity
2050
2040
2030
2020
2010
2000
1990
(E„)
Cells
for
Electncity
)„
(E„
PV
for
Energy
Fossil
10
years
,,30
(E„)
PV
for
Elec
tnci
ty15
Values are given for the overall energy flux, calculated In the processes "electrical
energy dlstrlbution for PV" and "fossil energy distribution for PV"
The overall need of electrictty is significant for crystallme wafer technology and peaks
wlth almost 10* 109 MJ/year around the year 2025 This correlates wlth the assumed
Phase out of nuclear supply to the grid At this time. If no additional cogeneration is
assumed. this would represent about 6% of the total electncity produced in
Swltzerland Silicon sheet and thin film technology do require much less electrical
energy for the Implementation This additional amount of energy may be provided by
cogeneration, or Imports or savlngs from exlstmg fluxes to the loads as a result of more
energy efflcient energy usage
Figure 3 8 Shows the energy flows for the overall as well as for the Individual processesto Implement PV plants Each graph contams two curves showmg the Implementationwithin 60 and within 30 years Energy fluxes do overswing when the faster
Implementation time of 30 years is considered
3.2.3 Relationship between energy production and investment
PV plants generate electncity and are "fuelled" by a renewable source solar
radiation This fact may lead to the false conclusion that the net energy Output of PV
plants may only be limited by life time. efficiency and available solar input The
analysis of this work, however, has shown that significant energy inputs are necessaryto implement and mamtain the PV scenano The question then is how production of
electncity from solar energy relates to the required electrical input to implement the PV
plants
Based on the dynamics involved in the long-term development of PV charactenstics
and accumulated PV plants installed, new metncs have been defmed to assess
Potential breedmg factors and the point In time, where break even between
accumulated energy investment and productlons is reached These new values are
time dependent Initial values dunng the start-up Implementation phase as well as
dunng steady State are of major interest
Smce Implementation mvolves both electrical energy and fossil flux "Investments
these fluxes are modelled separately In fact, most of the energy requirements are
electrical, and the fossil fluxes account for most of the cases of non-energy related
fluxes such as the fabncation of polymers. plastics, cokes to reduce S1O2 to
metallurgical Silicon, asphalt to make roads which are necessary to transport PV
plants etc
3 2.3.1 DiscussJon of the impact of System boundary selection
To this point in time, energy technologles based on renewables have offen been
validated based on emissions and Energy Pay Back Times (EPBT) The methodologyto assess emissions has been described in Fnschknecht et al, (1994) and to calculate
EPBT in Alsema (1996 and 1997) Caiculations based on the LCA method result in a value
at a given point of time Similarly, other authors have defmed CQ2 pay back times as
the fractlon between the amount of CO2 which was released to make the PV plantsand the amount of CO2 saved which would otherwise be released from fossil-fired
power plants (Inaba, 1997)
The methodology described in Inaba (1997), Alsema (1997), and Frischknecht (1994)does refer to the point that energy flux from fossil and electncity are compared by
66
Converting them to one energy unrt and using the mix of power plants withm the Systemboundanes under consideration
Figure 3 9 77ie emissions summarlsed by Indlcators assumlng electrictty generated by using the
UCPTE mix (assumed tobe 100% as referred to bar indexed by number, 1" n the legend) and
the relative changes if the same PV technology would be manutactured using the electricttyfrom the Swiss Utilities alone as Indexed by bar number „2" (Source Frischknecht 1994) For most
of the major indlcators changes n System boundanes and therefore ti the mix of the electriatysupply will obvlously lead to huge variations In results
Figure 3 9 shows as an example emissions calculated by this method Emissions are
presented based on the assumption that the electncrfy is denved from (i) an Europeanmix as given in the value of the UCPTE and (n) from Swiss gnd alone As can be
deduced from the Figure 3 9 changes in assumed System boundanes result in a hugevariations of calculated emissions
These variations shown in the Figure 39, are therefore the result of the assumptions of
System boundary defmition Similar EPBT values do also depend strongly on selection
of System boundanes There are a number of examples which indicate limitations of
the methodology of trymg to "unify the different character of electncity and fossil
energy
In the case of heat pumps for example advocates and opponents are using the
method and varying the System boundanes to back their arguments If the Systemboundary is chosen to be UCPTE opponents of the applications of heat pumps are
argumg that more CO2 is produced than if fossil energy would be used for direct
heating purposes (May 1996)
If on the other hand the System boundary is selected to be Switzerland the results of
the analysis mdicates the contrary (Rognon 1997) To overcome the inconvenience
that results strongly depend on an arbitrary System boundary selection three new
metncs are introduced and defmed in the next chapters the breedmg factor the pomtof energy break even and the fossil multiplier factor
67
3.2.3.2 Breeding factor of PV plante
The breeding factor Is a new metnc which provides better msight of how energy flows
from "renewable energy technologies" evolve over time with regard to their
production and the needs of energy to implement these Systems Electncal energy
and fossil flux requirements are modelled as mdependent fluxes In the case of the PV
Systems, electncal production is compared wrth electncal energy mvested This
defines the electrlcal breeding factor Bg(t)
The fossil flux required to make PV Systems is compared wrth the amount of electncal
energy if the fossil flux would have been used in cogeneratlon to generate electncityinstead The fractlon of this two fluxes defines the fossil "multiplier" factor MfCO
In the case of electncity production, the electrlcal breeding factor is a „true" metnc in
the sense of It's term It compares electric generation wtth electrlcal input to make the
PV plants
In the case of the fossil input, the term "multiplier" refers to how much more electncity is
generated when fossil flux Is invested in PV (mostly for non-energy reasons such as
making polymers or In the form of coke to reduce the Silicon raw matenal, etc) rather
than usmg its energy content in direct conversion in cogeneration
The electncal breeding and fossil multiplier factor are expressed with the two
mdependent values BE(t) and MF(t) respectlvely In order to have a positive impact on
substrtuting non-renewable energy technologies with PV the breeding and multiplierfactors must comply with the following equations
BE (t) »1
Mf (t) »1
for (t) to equal or be greater than the Implementation time
The new metrlcs are dynamlc values The values for Be (t) and Mf (t) evolve over time
as the technologies Improves, such as better matenal utilisatlon, higher efficiencies
etc The factor is also dependent on EYP and the efficiency of the reference
technology which is used to transform fossil energy mto electncity, as defined in the
Parameter function P6®(t)
Breeding is a term which may be applicable to Systems which do rely on a renewable
energy sources The term breeder has flrst been Introduced in nuclear energy to
describe a type of nuclear reactor, which produces It's own fuel as a by-product from
it's reactlon This type of reactor would operate with a renewable energy source and
would therefore not face the fate of depletion of fuels as other nuclear reactor typesdo3
3.2.3.2.1 The breeding factor for the electrlcal energy
The breeding factor for electncal energy Be(t) Is defined as the ratio between the total
production of solar electncity from a PV plant over Its lifetlme and the invested
electncal energy to implement the PV plant The breeding factor is dependent on PV
3 Technical, financial and environmental constramts have stopped most developmentefforts of the so-called fast Breeder
68
technology. available solar energy Input, on PV plant llfe tlme as well as on EYP Within
this definition, It is the entlre PV plant Performance and not only the efflclency of PV
modules which is taken into consideratlon
The electrical breedmg factor BgCt) Is deflned as
BE(t):J '-PVsolarelectrlcitygenercitlorA' '^'
_0_
2^t ^electrical energy investedPVplant
70
60
50
40
30
20
10
As sumed PV plant
thin film
Elec
fetime 30 years
•tncal breedmgf
70
actor
Assumed PV plant lifetime 20 years
.—»«
50thin film
sheet
sheet30
waferwafer10
1990 2000 2010 2020 2030 2040 2050 1^90 2000 2010 2020 2030 2040 2050
Flgure 3 10 The developmant of the electrical braedlng factor for three PV technologiesconsidered crystalllne wafer sheet and amorphous thin Ulm AI technologies have very
positive breedlng capacltles, but they are obvlously mach higher for sheet and thh Ulm
technologies The left graph shows the breedlng factor assumlng 30 years llfe tlme for PVplantsthe rlght one for 20 years
This factor is an important indlcator to assess how efficient reproduction of Investments
in electrical energy are When aiming at a sustainable energy paradlgm, energySystems must be able to reproduce itself. The breedlng factor would teil, how fast this
reproduction could happen In the case of the scenario sketched out for the largescale Implementation of PV In Swllzerland, excess solar electncity production is partyused to provide clean electrtclty to the grid Low breeding factors would mean that a
large amount of the solar electriclty released from the mstalled PV plants would be
used just to build new ones High breeding factors on the other hand are an indicator
that from already installed PV plants only a minor fractlon of the generated energy is
needed to build new PV plants, and most of the energy generated is useful to satisfythe needs of the loads
B£(t) is also dependent on time and therefore on factors such as EYP(t) This also
explams why after the year 2030 the breeding factor sllghtly decreases This is because
more and more PV plants will be installed wtth less favourable orientation, which, in
terms of energy production, means lower EYP values, and thus has a sllghtly negativeimpact on the breeding factor
3.2.3.2.2 The fossil multiplier factor
To implement PV plants, not only electrical energy but also fossil flux is required Detailsof these fluxes are given in Figure 2 8 for crystalllne wafer technology For the other two
technologies, sheet and thin film, detailed results are given in the Appendix A
69
signiflcant question arises How much more electricity is generated if the fossil flux is
invested in implementing PV plants rather than using its energy content for directly
fuellmg conventional Converters which transform fossil energy into electricity such as
in cogeneration
The fossil multiplier factor MfCO is therefore defined as the amount of electricity
generated in cogeneration units per fossil energy Input compared to the amount of
solar electricity generated if the same amount of fossil input is invested in
implementing PV plants
MF(t) =
Ufetime
JEpvsolarelectricity generation (t )dt
0
per MJ of fossil energy Input
E cogeneration Cf)
per MJ of fossil energy Input
MF(t) is used to assess, whether the amount of energy embedded in the fossil flux to
make PV plants is critlcal for the Implementation of PV If. for arguments sake the
electrlcal breedmg is very high but more fossil energy would be required to implementPV than would be used to produce the same amount of energy in traditional
generatmg plants, it would not make much sense to pursue with the Implementation of
PV plants (unless, for example, the total energy content of the fossil input could be
used by such as by burning the plastics in waste mcmerators) However as can be
deduced from Figure 311, the associated energy content of the Investment of the
needed fossil flux to make PV plants is much smaller than using it for direct power
generation
Fossil breedingfactor
Assumed PV plant Metime 30 years
thifi film shget
90 2000 2010 2020 2030 2040 2050
Assumed PV plant hfetime 20 years
70
60-
50
40-
30
20
10
sheet
wafer
1%0 2000 2010 2020 2030 2040 2050
Figure 3 11 The development of the fossil multiplier factor Mfü) for the three PV
technologies considered crystallina wafer sheet and amorphous fhm film Even the
crystallme wafer based solar cell technology has a very high multiplier factor which
justifies PV Implementation from the point of vlew of the needs of fossil energy The left
graph shows the breedmg factor assuming a 30 year life time for PV plants the nght oneis for 20 years
As mentioned above most of the fossil flux is used for non energy purposes wrth two
mam exceptions energy needed for the float glass process and for transportationThis energy usage could, theoretically be substituted by electricity This would
increase the electncal energy flux by 3%, assuming 100% efficient Substitution in the
case of heatmg the float process with electricity and 50% for transportation (using
70
electrolysls to make hydrogen used In transporratlon). Thls argument could of course
be reflned and implemented in the model. But as can be seen, the fossil multipller
factor Is so large that the usage of fossil fluxes to reallse the PV scenario can easily be
justified. (In thls sense, the fossil flux is considered just llke any other material Input flux).
The energy content of the remainlng fossil flux is about equivalent to 2* 10' MJ/a.
Assuming, that in the year 2050 the energy content in the fossil flux in Switzerland will
decrease from 468 * 10' MJ/a in 1995 to 20% of this value4, whlch Is equal to 100 " 10'
MJ/a. The energy content forthe PV Implementation would account for almost 2%.
Thls is not alarming. but it Is slgnificant, and may suggest that processes wlth more
efficient usage of fossil raw material Input may be developed. It is also important to
note, that for sheet and thln film, the requlrements for fossil flux is lower.
3.2.3.2.3 The point of energy break even
To implement PV Systems, it is necessary to first invest, not only in monetary terms, but
also In energy terms. How the accumulated Investments evoive over time depends on
the selected PV technologles and on the assumed growth rate.
Each of the PV plants installed Starts generating electrlcity, and it is of great interest to
analyse when the Point of Break Even (PBE) Is reached, defined as the accumulated
energy invested divided by the accumulated produced. At thls point, PBE(t) must
comply wlth the following condition:
PBE(t)<l,
where PBE(t) is defined as:
t
J EdecMcdenergylnvestcxA' X"
PBE(t) = y5
J^FVsolaelecl!te11ygen«a1lon'' Xu0
Infact, durlng the start-up phase of the large scale implementation, PV plants do not
breed enough own electricity to be seif sustainable. As long as the PBE(t)>l, the
System needs electricity from the grid. During this phase, it relies on external electricity
generating power plants and emissions would have to be considered, as discussed in
the previous Chapter 3.2.3.1.
But in view of the fact that this is a transition phase and that the total amount Is still small,
therefore considerations of emission from the usage of non PV electricity are not
important.
As soon as PBE(t)<l, the accumulated installed capacity of PV plants generates more
than enough energy to not only to seif sustaln the PV plants already installed, but to
also produce more PV installations and provide a net positive energy to the grid.
Random value, stipulated for the argument.
71
Flgure 3 J2 shows #ie devetopment of ine break even (betör for ff» fhree PV technologlesconsidered crystalllne wafer. sheet and amorphous (ruh film The crystalllne wafer based
technology needs Investments und about the year2010 betöre a positive net energy productionfc reallsed Sheet and amorphous thln film technologles delrver a positive net energy after only afewyears The left-hand flgure shows the PBE(t) für a 60 year Implementation tlme the rlght-handflgure for 30 years
tt is remarkable to note, that the PBE(t) only slightly depends on the Implementationtime Flgure 39 shows two graphs. the left one for a 60 year Implementation tlme, the
right one for 30 years lt concludes that even an enforced Implementation scenano
does not require a large amount of electriclty, which needs to be generated by „non -
PV electriclty generators", over a prolonged time period Table 32 shows the times to
reach break-even for the ditferent PV technologles and Implementation times
PV Technology Time to implement PV scenarlo
60 years_,
30 years
Wafer based 135 155
Sheet based 34 47
Thin film (amorphous) 31 31
Table 33 The elapsed tlme to energy break even As can be seen wafer based PV
technologles require a tlme (tarne of 13 to 16 years where Investment of electriclty are requlredbetöre the Implemented PV plants Start produclng a positive net energy for the grid Note
Faster Implementation schemes do need a sUghtty longer Investment period Sheet and thln film
reach break-even much faster
Smce the actual world wide energy Situation is charactensed by an abundant energysupply, large energy Investments at the begmnmg of the transition to a renewable
energy supply paradigm is. In effect, even favourable The change of the energy
supply paradigm needs not only fmancial but also energy Investments The factor
PBE(t) mdicates how long the Investment period will take place Figures 3 7 and 3 8 givethe absolute values of yearly energy needs
3.3 Electriclty produced for the loads
In order to assess the metabolism of the large Scale Implementation of PV plants in
Swrtzerland, the Swlss gnd wtth rts loads and other energy sources is included in the
model This provldes results on the Overall energy fluxes available to the loads These
are slmply the result of the devetopment of gnd-connected solar energy and on
assumptions of how the other energy sources such as hydro, nuclear, wind, and
bioenergy will evolve This assumptions are outhned in Chapter 2 4 5
72
The results show how much electricity will be avallable by each technology. They are
not driven by the questlon of how much electrlcal energy will (or may) be needed.
They are based on yeariy average values. and therefore do not address technlcal
issues such as energy storage. and dally and/or seasonal fluctuatlons. The load within
the model is given in flux Oi6, shown in Flgure 2.3-
Flgure 3.13. The development of electricity supplled to the loads based on Ihe Implementation of
monocrystalllne technologles and Implementation rate. The phase out of nuclear provokes a
fluctuatlon h 1he supply, wNch elther has to be compensated by energy savlng technologles.
Imports or cogeneratlon. (All values are glven In 109 MJ/year).
As can be deduced from Flgure 3.13. there will be a large fluctuatlon In the electricitysupply caused by the assumed phase out of nuclear plants after havlng reached the
end of their predlcted life time of 40 years. The assumed Implementation of
cogeneratlon is outlined in chapter 2.4.5.5.
10»MJ/a
250
200
\^ \Nucle3I_—- Cogeneratlon~
Solar
150Wind and Biomass
HydroenergyI
ioo(-
50
1990 2000 2010 2020 2030 2040 2050
Flgure 3.14. Development of the splltof electricity from dlfferent sources such as hydro. nuclear.
PV. wind biomass and cogeneratlon. The resutt shows how productlon can shlft within two
generatlons towards an new supply paradlgm based on renewables. The study Is driven by the
questlon of how much energy can be made avallable wllh renewables and not driven by the
questlon of how demand may develop.
73
The remedy to this fluctuation -would be to a add large scale of cogeneration to
overcome shortages betöre the PV plants have grown to thelr füll Potential to
contnbute a significant amount of electricity
Any delay In starting the Implementation of PV and other renewable energy sources
will further enhance this Potential shortage, as shown in Figure 3 13 As can be deduced
frorn Figure 3 14, the addmg of cogeneration will have the Potential to smooth out future
fluctuations in electricity supply which may be caused by the phase out of nuclear
It Is a coincidence. that the energy supply in 2050 could nearly be the same as 1990 In
fact, Figure 313 shows the result of having added other electricity sources accordmgto their potential contribution suggested by various experts in Switzerland and as
outlmed in detail in Chapter 2 It is, in fact, questionable whether the addition of other
energy sources is necessary, smce the large potential for savmg energy has not been
addressed in this study, and if realised could lead to a smaller requirement for
electricity (in 0i6)
3.4 Analysis of the plausibility of assumed growth rate
Growth rate assumptions have been analysed with regard to the matenal and energyfluxes The results can also be used to verify other factors such as the availabillty of
tramed installers or the availabillty of electncal Installation matenal The plausibility of
this was checked by two considerations
• How large is the actual installed capacity at its peak value (around 2025), and
• Can this growth be compared with other industnal sectors' This may allow some
conclusive correlation
There are in fact several industnal products which have expenenced large growthrates of 15% and more over longer periods (Fischer, 1970) In the followmg discussion,
assumptions of PV growth rates are compared with the Installation of resistive heaters
in Switzerland for the followings reasons
• The Implementation of resistive heaters in Switzerland follows very nicely the
sigmoidal growth curve which has also been assumed for the growth of PV
mstallations The actual plot of the development of resistive heaters is given in the
Appendix 4 Its growth rate has been 25%
• Resistive heaters are also based on dispersed technology, very much like PV
plants A large number of mstallations account for the total accumulated installed
power
• The hours of füll load Operation (load factor) of resistive heaters are almost
identical to the one's of PVs
Table 34summanses the main charactenstics of the large scale Implementation of
resistive heaters and PV plants in Switzerland
This data may be used to further evaluate assumptions on the growth time PV plantdevelopment with data from other growth patterns which have actually occurred in the
past
74
Items to compare: Resistlve heaters PV Units
Time span 1970-1990 1995-2050 years
Energy level 1 "109 40to60*109 MJ
Hours of füll load
Operation
875 925 hours
Heated area 36.3 *10° m2
Covered area 125" 10° m2
Installed numbers 229.400 1.200.0005 unlts
Growth rate 25 15 %
Table 3.4. Comparlson of actual large scale Implementation ofrestlve heaters andwHh assumed
Implementation of PVplantsln Swltzeriand. The growth rate of 30% for reslsttve heaters Is one of
the Nghest ttgures In hdustrld products (bindh nterature.
As can be deduced from Flgure 3.1 b. the maxlmum material flux of about 215 * 106 kg
occurs around the year 2026. This Is equlvalent to roughly 5.3 * 106 m2 PV plant
area/year. This is 4 times less than the average yearly usage of free land for the built
environment during the last few decades. This PV plant surface corresponds to a 500 to
800 MW maxlmum yearly capacity Increase around 2025, depending on the selected
PV technology6. In the resistive heating industry, the average yearly installed capacitywas about 200 MW In Swltzeriand.
Installed PV-plant power
10» Watt*
15
10
5
0
1990 2000 2010 2020 2030 2040 2050
Flgure 3.15. The development of Installed PV capacity for the three technologles: wafer. sheet
and thh Ulm. The power tevete are dependent on cot efficlency. Values are glven h AC Outputpower and consider a future oversizing of thePV fteld to Inverter rating. A value of 75% of DC
power rating has been assumed.
Figure 3.15 shows the development of installed PV plant capacity. Values are given in
AC, based on a DC Output power which Is oversized to the inverter power rating. This Is
roughly 25% less than the Installed DC power. The installed DC power Is in fact a value
which is used today for PV plant rating, but does not reflect the actual power usable by
Assumed average power of 15 kW per PV plant and per installation of resistive heater.
For comparison: in Germany the wind energy market has grown from almost zero in 1988
to over 500 MW/a in the last 3 years. Projections for 1998 are roughly a 600 MW/a increase
in installed capacity (Dewi, 1998).
75
the grid (Schalkwijk, 1997)7 It is assumed, that in the near tuture, gnd connected PV
plant ratings will eventually shift from DC to AC. and away from a peak value ratingtowards a power rating which represents the actual Situation in Switzerland8
This analysis suggests that there should be no bottlenecks In terms of industnal and
labour capacity The mduced matenal and energy fluxes are relatively small and the
PV array surfaces are minor compared to orher activrfies, and labour and technologyto install PV are available, when comparing wrth slmilar industnal sectors in the
electrical field. such as the large scale Implementation of resistive heaters
3.4 Analysis of the impact of assumed lifetime distributions
As outlmed in chapter 2 3 3 1, it is assumed that the average PV plant lifetime will be 30
years Since some PV plants will fail earlier, and others will last longer. a Gaussian
distribution of lifetime probabillty has been assumed, with a Standard deviation of 10
years It has been argued by some experrs. that the results of simulations will be the
same if the average lifetime value will be applied Instead of a distribution of lifetime
values This research has determined that it will not In fact, the results may even lead to
a completely incorrect Interpretation In Rgure 3 15. the results of the simulations are
shown for both cases. one wrth an assumed distribution of lifetimes and the other with a
fixed constant value for the lifetime of all PV plants
Flgure 3 15 On 1he left graph the materiell fiux Is calculated for PV plant lifetimes of 30 years
assumlng a Gaussian distribution with a Standard deviation of 10 years On the rlght graph results
are shown assumlng tat al PV plants will faä after exactly 30 years of Operation For Short
transttlon tlmes (30 yeors) flucfuafions of materlal fluxes osclllate unrealistlcally
As can be deduced from the companson of the two Simulation runs in Rgure 3 15 the
Introductlon of a distribution of PV plant lifetimes is essential In fact, simulations with
fixed lifetime values provide results which are incorrect and will lead to incorrect
conclusions
Schalkwijk has calculated that fhe inverter AC Output power has an optimal value ot 76%
of the DC PV array Output power level This value of course depends on the developmentof the costs of different components A value of 75% has been used for this study
In the USA, PV plant power rating already takes these points into consideration AC
values are used and fest conditions refer to PVUSA and not to IEC Standard Test
Conditions which more represent operational conditions
76
It can be shown that the dlfferences in the simulations will become significant when the
time for the Standard devlation has values similar to the time span for the assumed
growth In the example shown In Figure 3 15. the value for the Standard devlation is 10
years, and it has been assumed that Implementation will take place m 30 respectivelyin 60 years For the first case, the 30 year growth time means that the real significant
growth of PV plants will occur within 10 to 15 years It is obvious, that a distnbution of
assumed life times for the PV plants will dampen the Induced flux required to replacethe old PV plants with new ones, once the initially instalied plants reach the end of their
Irfe cycle and need replacement With the 60 year implementation time, the effect of
assumed uncertamties for PV plant lifetimes are still important, however they are less
stnking In the case of the Simulation of the large scale Implementation of PV plants,
neglectmg a Standard distnbution (of 10 years In the example) has a dramatic effect
on the induced matenal flux
In the real world, PV plants will have different life times before they are dismantled, and
this has a smoothmg effect on the matenal flux needed for replacement If the
Simulation applies a method whlch does not allow the use of uncertainty values, results
of dynamic simulations will be unreallstic The error introduced by just uslng fixed
lifetime values mstead of a distnbution of uncertainties of assumed lifetimes will
depend on the fraction of the growth time and the value of the Standard deviotion of
the uncertainty distnbution
4. Conclusion
From the work performed. it can be concluded that
1 Dynamic modellmg of matenal and energy households, based on the
methodology of Baccmi and Bader (1996) provldes good insight into the long term
System behaviour of the large scale Implementation of renewables such as PV
technologies The results can be used for energy resource plannmg and earlyrecognrtion of cntical paths for potentlal material or energy flux requirements as
exemplified by the large scale Implementation of grid connected PV plants in
Switzerland
2 The new metrics with regard to the breedlng Potential of renewables and the time
span to reach energy break-even are helpful for plannlng energy strategies The
method developed is based on the capacity for dynamic simulations, includmgfeed back and the Simulation of separate electrical and fossil fluxes
3 Within the time span of 60 years, the Swlss electriclty system can be transformed
into a supply System which is based on renewable sources such as hydro, PV, wind
and biomass The assumed time penod of roughly two generations allows a
smooth Implementation without a large overshootmg of the instalied industnal
manufactunng capacity Induced material fluxes are minor with the exceptlon of (Dfloat glass, which reaches almost the same level as in the bullding mdustry, and (n)
punfied Silicon, if PV plants are based on wafer solar cell technology Other optlonsare feasible and are discussed in detail
4 The final instalied power is large and in fact exceeds the Instalied hydro power
capacity, although the energy production from hydro is still higher than from solar
Values are given as Statistical yearly data Special issues such as daily and
seasonal fluctuations in energy production must be addressed and will require a
different control strategy for the grid, its dispatch of generators and its loads None
of these issues has been addressed In this analysls
77
5 If. for an intermedlate time period of two to three decades. substantial electrical
energy production from cogeneration is assumed, then no supply shortage will
occur when shifting the generation paradigm to technologies which are based on
renewables
6 If Implementation tlmes faster than 60 years are envisaged, then two cntical issues
need to be faced
• The glass flux becomes significant, and
• Fast Implementation based on Silicon wafer technologies may lead to largerequirements for purrfied Silicon and for electricity for PV plant production The
remedy may be to envisage a larger time frame for Implementation or the
replacement of wafer-based PV technologies by other manufactunng optionssuch as sheet or thln films
7 To perform correct dynamic simulations. a model must be able to mtroduce
uncertainties If not. dynamic modelling may lead to incorrect results, as has been
demonstrated In the case of an assumed Gaussian distribution of PV plant lifetimes
versus an assumed fixed, constant lifetime for all PV plants
8 Electricity from other sources such as wind or biomass have been based on
Potential assessments The Implementation of these energy forms should be
analysed in the same depths as have been done with PV
78
Glossary/Definitions
BOS"
Balance of System' - the components needed to comblne wlth the
PV modules to comprlse a complete PV plant (kg).
Cogeneratlon A method of produclng electriclty and heat at the same tlme.
Electrlcal energy The aggregate of high, medium and low voltage dlstrlbutlon llnes,
dlstrlbutlon subsystem Including transformers. swItch gear. and control devlces. Although thb
represents the grld spread out all over Switzerland, wlthln the model It
Is symbollsed wlth one process box.
Electrlcal energy flux Electriclty (MJ).
Electriclty for BOS The amount of electriclty needed to manufacture the BOS, whlch
also Includes all pre combustlon Steps.
Electriclty for fossil The electriclty needed for pre combustlon. transport and fossil
energy energy dlstrlbutlon. as needed for PV manufacturtng. Implementationand dlsposal (MJ).
Electriclty for glass The electriclty used to power the glass recycllng process. The maln
recycling portlon Is used for grlndlng and smashlng scrap and recycllng front
glass.
Electriclty for solar cell The electriclty needed to process clean electronic or solar grade
productlon Silicon and manufacture the photo-sensItlve actlve layer (wafer,
crystalllne sheet or amorphous thln fllms).
Electriclty for The electriclty needed to transport modules and BOS components
transportatlon by rall (MJ).
Electriclty from co- The electriclty produced by the entlre set of co-generators Installed
generation In Switzerland.
Energy yleld Parameter The ratio between the actual and the maximum possible annual
EYP energy productlon by a PV plant. EYP depends on the azlmuth,
elevatlon angle and shading of the PV array. EYP Is 1 for optimal south
orlentatlon, 30 degree elevatlon angle and no shading.
Fossil Energy for BOS The fossil energy flow requlred for manufacturtng BOS components,
Including all pre combustlon Steps whlch are requlred to explolt raw
materlal and transform It into BOS components (MJ).
Fossil energy for The amount of fossil energy assumed to be used for cogeneratlon.
cogeneratlon Wlthln the scope of the study, only the electrlcal Output has beenconsldered. The heat of cogeneratlon is used as a valuable by-
product to make cogeneratlon economlcally vlable. In the model,
heat is handled as Output 014. Cogeneratlon may be achleved wlth
gas turblnes, IC englne sets or. In the future, fuel cells.
Fossil energy for float The fossil energy requlred to manufacture float glass (MJ).
glass productlon
Fossil energy for module The fossil energy requlred to manufacture the modules, Including all
productlon pre combustlon steps as well as the amount of fossil requlred to
make any raw materlal for module productlon such as polymers etc.
(MJ).
Fossil energy for solar The fossil energy needed to process clean electronic or solar gradecell productlon Silicon and manufacture the photc-sensltlve actlve layer (wafer,
crystalllne sheet or amorphous thln fllms).
79
Fossil energy for
transportatlon
Fossil multlpller factor
Front glass
Goods
The fossil ©nergy requlred to transport modules and BOS
components to the slte. Includlng all Steps to bulld the Infrastructure.
the means of transportatlon and the transportatlon of the raw materlal
from the Site of exploltatlon to the manufacturlng plant and at the end
of its llfetlme to the recyc llng plant or landflll
The fossil multlpller factor Mpffl b deflned as th© amount of electrlcity
generated In cogeneration per fossil ©nergy hput compared to the
amount of solar electrlcity generated If the same amount of fossil
Input b Invested In Implementlng PV plants
The glass used to mak© PV modules
Conslsts of a materlal or materlal mlxtures and has a deflned functlon
and value
Grld
Irradlance
Irradiation
LCA
Load, loads
Metabollsm
MFA
Modules, also PV
Modules
Nuclear energy
Processes
Technical Installation to distrlbut© electrlcity, Includlng high and low
power transmlsslon lines, transformers and control devlces
Solar Irradlance, measured In W/m2, IEC/ISO Symbol G
Solar Irradiation, measured In J, IEC/ISO Symbol H
Life Cycle Assessment
Tha tetm load Stands for an ©lectricol consumer, powered by the
grld Th© loads, as referred to wlthln thls work, Is the accumulate of all
loads powered by the grld
Th© notlon .metabollsm" comprlses the physiologlcal turnover of
©nergy and matter h a IMng organlsm Anthropogenlc Systems are
scclo-cultural Systems and have also a physlologlcally deflned
Subsystem (a metabollc Subsystem) wtlh a larg© varlety of energycarrlers and of materlals flowlng through these Systems
Material flux Analyst, a method descrlbed In Bacclnl and Bader
(1996).
The unlt whlch comblnes th© front glass, photon absorbing materlal,
back sheet It Is ready for fleld Installation to generate solar electrlcity
sometlmes referred to as the" lamlnate" If a structural frame Is absent
Th© total amount of electrlcity produced by nuclear power plants
Transport, transformatlon or storage of goods, materlals, energy
and/or Information Mathematlcally a process Is a balance volume
In the Model they are represented by Boxes
PV plant Th© complete Installation whlch converts solar energy directly Into
grid-connected electrlcity Offen referred to as a PV System h this
study, however, th© term 'System' Is used In a broader sense
Solar cell Photon-sensitive absorber layer Wlthln thls study thls term Is limited to
th© us© of Silicon
Solar electrlcity Electrlcity generated by PV plants Wlthln the scopeof thls study, thls
applles to grld connected Systems only (MJ)
Surface potential The surface used for Implementlng PV Systems from the overall
utllbatlon surface potential Identlfled Wlthln th© System boundarles of
Swltzerland, only potential surfaces whlch ar© related to bulldingroofs and facades have been consldered as potential sltes for PV
plants.
Window glass The float glass used for Windows In the bullding sector (It does not
Include the market for facades and Inferior appllcatlons)
80
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World Commlsslon on Environment and Development: Our CommonFuture, Oxford Universlty Press, Oxford, 1987.
Worldwatch Institute 1996, Annual Report.
85
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A3 Growth curve for resistive heaters in Switzerland
In Switzerland, the growth of resistive heaters has almost followed a sigmoidal curve
Figure A3.1 shows the yearly development of installed resistive heating Systems for
buildings
QUO
72 74 76 78 82 84 86 88 90
Flgure A3.1 The development of resistive heaters h Switzerland. Thls growth took place over a
pertod of two decades Source: Amsteln und Walthert, Study for the Swlss Mlnlstry of EnergyErsatz von Elektroheizungen durch Wärmepumpen, October 1993.
The development of resistive heaters in Switzerland is one of many examples which
can be used to analyse growth rates and the growth pattern of an industnal product.The development of resistive heaters is well suited to be used as an analogy with PV
plants because many very similar characteristics: average power level of each
Installation, yearly hours of füll load. low power density per surface area covered,controls and interconnection to the grid, etc. It also requires the same skills of
electrlclans, although af the present time this work Is performed by specialised PV
companies.
Numbers of installations / year
250'OfJO'
Sigmoldal growth of
resitive heaters in Switzerland
1970 1975 1980 1985 1990 1995 2000 2005
Flgure A3.2. The Interpolated Httlng of the growth curve The growth rate of sigmoldal growlh Is
25%, much more than assumed for the Implementation of PV plants, if Implementation takes
place In two generatlons.
The growth has been interpolated by the followmg equations:
257129Installed resistive heater (t):
1 + e'-0 2456-(t-1982)
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Markus G. Real
President of Alpha Real AG
Born 10.9.1949. Citizen of Schwyz
Education
1975 Completed Gymnasium. Type C. Schwyz1969-1975 Federal Institute of Technology, ETHZ. HIB
1973 Intermediate year. various stays abroad to improve English,French, Spanish, Portuguese
1974-75 Assistant to Prof. Baggenstoss1975 Diploma in Electronics at the ETHZ
1975-76 Interdisciplinary study on the Problems related between
developed and underdeveloped countries.
Professional acfivity
1975 Founder of 'Real Tour", a travel agency specialised on sail
charter.
1975-1976 Analysis of local production of agricultural machinery in Paraguayfor the World Bank and for Helvetas.
1977 -1982 Federal Institute for Nuclear Reactor Research. Manager of the
deportment for solar power Station. Various research project and
co-ordination.
1980 Co-founder of the Company "Real-Snozzi-Witta". with its main
activities in the thermal energy saving programs.1982 to present Chairman of the IEC/TC82/WG 3 group. responsible for elaborating
Standards on PV Systems.1982-1983 Various projects such as large windpower Systems, solar pond
control Systems for a project in the middle east.
1983 to present Chairman of the national committee responsible for Standards for
PV Systems.1984 Founder of the Company Alpha Real AG .
1985 to present Lectures at the Unlversity of Zürich and Fachhochschule Muttenz In
the field of renewables.
1986 Transferring Alpha Real to a public Company.1991 Marketing research for renewables in South America for Dr. S.
Schmidheiny.1991 Participatlon at the preparation for the Rio 92 UN-Conference.1991 -1992 Sabbatical for 7 month in the USA. Studies of various production
technologies for solar cells and modules. Consulting octivity for
Mobil Solar Energy Corporation. Electric Power Research Institute
(EPRI). Sacramento Municipal Utitliy District (SMUD).1992 to present Board Member of the Foundation Technopark Zürich".
1992 Elected to join the orgonisation committee of the IEEE PV SpecialistConference.
1997 to present Member of the Swiss Academy Engineering Sciences.
1997 to present Board Member of the Global Approval Program (GAP). GAP has
been established under the leddership of the three PV industryassociation in Japan, the USA and Europe to promote quality seals
and accreditation for PV Systems.