1 system analysis of biomass based value chains by prof dr frank schultmann

KIT – University of the State of Baden-Wuerttemberg and National Research Center of the Helmholtz Association

INSTITUTE FOR INDUSTRIAL PRODUCTION (IIP)

www.kit.edu

System Analysis of biomass-based value chains: Important aspects

International Renewable Energy Asia Conference 2015, Bangkok, 03 June 2015

F. Schultmann, M. Fröhling, S. Radloff, A. Rudi, K. Schuhmacher

2 Schultmann et al.: System Analysis of biomass-‐based value chains: Important aspects, Bangkok, 03 June 2015

Agenda

  Background: value chain-orientated evaluation of biomass conversion technology

Aspects of a value chain orientation in the evaluation of biomass conversion technologies

Conclusions


Background

  A plethora of material and energetic utilisations for biogeneous raw materials is currently under discussion and in development

  Expected advantages   Reduction of climate relevant emissions   Substitution of fossil raw materials   Further positive effects along the value chain


Relevance of assessments in this context ►  Research questions

  Are the new process chains in terms of sustainability advantageous (in comparison to existing bio-based supply chains based on fossil and renewable raw materials)?

  How can sustainability of the process chains be achieved?   Which process chains are promising?

►  Assessment   To support concept and process development   As a basis for decisions about funding policies   As an objective basis for communication and discussion of the utilisation concepts

►  Need for suitable techno-economic and ecological assessment methodologies


Stakeholder framework

Preparation and

conditioning Primary

conversion Secondary conversion

Product upgrading

Biomass conversion technologies have to be assessed as biomass-based value chains

  Technical conversion processes

  Technical conversion as one step in a biomass-based value chain

Raw material

production Conversion Use End-of-life


Agenda

  Background: value chain-orientated biomass conversion technology evaluation


Raw material production aspects Logistical aspects Uncertainties

  Stakeholder acceptance

Conclusions


Assessment of raw materials for a vegetable oil biorefinery Dragonhead oil, coriander oil, linseed oil, crambe and canola seed oil

Conversion of „new“ locally grown vegetable oils to new products

interm. intermediate Further reactions products

Reac%on 1

Reac%on 2

Reac%on 3

Reac%on 4

Oil mill (p

ressing,

extrac%o

n)

Transesterfica%

on,

Hydra%

on

•  Polymers •  Lubricants •  …

feedstock

Dragon‘s head seeds

Coriander seeds

Crambe seeds

Canola seeds (Erucic)

… …

System boundaries of value chain steps

System boundaries of total regarded value chain


…

1.30

2.44

1.37

0.69

…

Dragon‘s head seeds

Coriander seeds

Crambe seeds

Canola seeds (Erucic)

Oil price (min.) EUR/kg

963

1010

1100

1280

…

Field produc8on costs EUR/ha

25

25

25

40

…

Yields dt/ha

(Thüringer Landesanstalt für Landwirtschaft and KIT)

2.89

4.05

2.97

2.28

…

Reac8on 1 with Product 1, produc8on costs EUR/kg



2,20 2,38 2,87 1,71 1,87

0 1 2 3 4

frei Anlage, eigene Schätzung

frei Anlage, LCI Daten aus ecoinvent

15,5 16,0 11,7

6,7 5,8

0 5

10 15 20

frei Anlage, eigene Schätzung frei Anlage, LCI Daten aus ecoinvent

  Estimation of life cycle impacts

  Conclusions   Economic and ecological disadvantages of alternative raw materials are

caused mainly by lower yields   Open questions:

  can lower yields be compensated through breeding and / or   better raw material properties, e.g. other fatty acid patterns

Land use Global warming potential

[kg

CO

2-Eq

./kg

oil]


Free plant (lci data: ecoinvent)

Free plant (own calculations) Free plant (lci data: ecoinvent)

Linseed Crambe Erucic canola 00-canola Dragon head Linseed Crambe Erucic canola 00-canola Dragon head

(Meyer et al., 2011)

[m²a

/kg

oil]


Agenda





Conclusions


Logistical aspects

  Decoupling of supply chains   Spatially   Temporal

  Location and network strategy   Integration in existing production

sites or networks   Upstream, e.g. saw mills   Downstream, e.g. integrated

chemical production sites

  New production sites and networks

Preparation and

conditioningPrimary

conversionSecondaryconversion

Productupgrading

Rawmaterial

productionConversion Use End-of-life

Site

bou

ndar

yWaste

Disposal

River Saale

Laboratory

Site coordination

Security and emergency management

Medical Service

Communication

Site development

Facility management

Production units and service provider on site

Power plants

Road

Terminals

Rail

Stations

Vehicle cleaning service

Logistic service

RailRoad

Pipe racks

Energy production and distribution

National grid

Water supply

Road

Fire brigade

Security

Waste water

ZAB

Waste Disposal

River Saale

Laboratory

Site coordination


Medical Service

Communication

Site development

Facility management

Laboratory

Site coordination


Medical Service

Communication

Site development

Facility management

Production units and service provider on site

Power plantsPower plants

Road

Terminals

Rail

Stations

Road

Terminals

Rail

Stations

Vehicle cleaning service

Logistic service

RailRoad

Pipe racks

Energy production and distribution

National grid

Water supply

Road

Fire brigade

Security

Road

Fire brigade

Security

Waste water

ZAB

(VDI 6310)


Trade-off between transportation costs and economies of scale

  Feedstock provision   Biogenic raw materials accrue spread over large areas

  Transport   Transport over large distances is often uneconomic and

causes climate relevant emissions due to high water contents and low material densities

  Increase of transport costs with increasing amounts

  Due to economies of scale large plants are envisaged

I: Investment at capacity [monetary units] I0: Investment at capacity 0 [monetary units] n: scaling factor [-]

00

n

I I κκ⎛ ⎞

= ⎜ ⎟⎝ ⎠

κκ

κ

I


Solution approach   Biomass Value Chain

modelling   MILP model   Multiple biomass,

technologies and output products

  Integrated location-, capacity- and transportation planning B

iom

ass

type

Biomass technology

Regional

National

Global Anaerobic digestion

Combustion Gasification

Forestry

Agricultural cropping

Residues and wastes

Manure

BtL

Etc.

Etc.

Ø Electrical energy

Ø Thermal energy

Ø Biogas

Ø Biofuel

Objective function: Max Profit = Max (Revenue – Cost)

Input data   Biomass potentials   Potential facility locations   Transportation network   Techno-economic parameters   Product demand and prices   Etc.

Output data   Conversion technologies   Facility locations   Capacities to install   Transport loads   Material and energy

output   Etc.

Integrated location, capacity and

technology choice model

  Multiple biomass, technology, product approach

  Economies of scale

Consideration of economies of scale using a linearization   Approximation of the concave

investment function   Formulation of a piece-wise

linear investment function based on segments and point of support weightings

  Implementation as Special ordered Sets of Type 2 (SOS2)

Inve

stm

ent I

I II III IV

κCapacity


18

4

36 35 34

31

26 28 27

29 30 33

25

23 22

21 20 19

17 16 14

15 13 12

11 10

9 6

5

3

2

1

32

Model output

Example: Application within the OUI Biomass project (preliminary results)

  Scenario   Scope: Trinational Upper Rhine Region   Straw potential approx.: 930.000 t/a   3 combustion and gasification technologies   Final product: Electric and thermal energy

  Results   100 plants in 15 districts   Capacity: 327 MW (200 MWel, 127 MWth)   Utilisation of 857.150 t/a of straw

  Effects of economies of scale on the size of conversion plants

  22 FBG* plants: 1-2.5 MW (avg. 1.8 MW)   63 combustion plants: 1.5-6 MW (avg. 3.3 MW)   15 BIGCC** plants: 4.3-8 MW (avg. 5 MW)

Source Plant

*Fluidised Bed Gasifier (FBG), **Biomass Integrated Gasification Combined Cycle (BIGCC)


Agenda





Conclusions


  Data of the technical processes

  Investment and cost estimations

  Raw material and utility prices

  Demand and revenues for products

  Further parameters

Uncertainties


Example: Utilisation of sugar industry residues in Australia

  Design and evaluation of value chains for the utilisation of lignocellulosic residues from the sugar industry

  Ca. 3 Mio. t. Bagasse / a (Australia)   Ca. 360 Mio. t Bagasse / a (globally)

  Solution approach I.  Aim and scope definition II.  Modelling and balancing of the value chain III.  Planning & Assessment

•  Supply Chain Design heuristic •  Uncertainty analysis

Modified from (ASMC, 2011)



Nested Monte Carlo Simulation

Simulation steps: Parameters constant over the life-time are drawn SMC times

S1

S2

S3

SMC

…

…

…

…

t1 t2 t3 T

Life-time of the bio-commodity production plant: Parameters subject to variability over the life-time are drawn T times per

simulation step



(in Townsville)

Results: distribution function for the minimum selling prices for FT fuel and Ethanol


Deterministic solution

95% confidence level


Agenda





Conclusions


Relevance of public acceptance for sustainable biomass utilization

http://www.envitec-biogas.de/fileadmin/Images/PressPictures/Guestrow_300dpi.jpg

Resistance against centralized, industrial projects

“Food for fuel” debate

Concerns regarding mono-cropping

and landscape transformation

http://www.bund.net/index.php?id=17849

http://www.niederelbe.de/ostemarsch/mais.htm

http://gas2.org/2011/10/17/americans-now-use-more-corn-for-fuel-than-food/ simcoereformer.ca


Consideration of factors influencing stakeholder acceptance

Approval/ endorsement

Support/ Commitment

Rejection Resistance

Active Acceptance

active passive

positive

negative

Appraisal

Action

Source: based on Rau et al. (2012)

Definition of acceptance: Dimensions of acceptance


Goals Method Key player analysis Identification of key players

within the bioenergy value chain in the Upper Rhine Region (URR) to identify motives, strategies and fields of actions

Exploratory semi-standardized interviews with ~100 actors in the URR

Decision analysis Identification of acceptance criteria of stakeholders of bioenergy projects to identify group- and country-specific differences

Standardized online questionnaire with ~50 bioenergy experts in the URR based on a Multi-Criteria Group Decision Analysis

Local acceptance Analysis of the local acceptance of biogas plants in the trinational URR

Standardized questionnaire survey of residents living in a 1km radius around biogas plants in 10 communities in the URR (~500 respondents)

Example: Consideration of acceptance issues within the OUI Biomasse project (1/2)


Preliminary results Key player analysis

Drivers: financial incentives and political framework conditions Barriers: substrate availability, logistics, efficiency of bioenergy plants Success factors: projects must be embedded in local actors networks and value chains

Decision analysis Roles of the stakeholders are more decisive for their evaluation of acceptance criteria than nationality. Predominating criteria for a high acceptance stated by the experts: Competitive plants, biomass provision, local impacts

Local acceptance Substantial differences in acceptance levels between countries and individual communities Acceptance depends on a row of factors such as the type of feedstock (e.g. energy plants or household waste), direct impacts (smell), information and participation possibilities.

Example: Consideration of acceptance issues within the OUI Biomasse project (2/2)


Agenda





Conclusions


Conclusions

Biomass conversion technology assessment requires the consideration of the value chain context

Recent and ongoing works give examples for the consideration of Raw material production Logistics Uncertainties Acceptance issues

Ongoing works need to be continued and further elaborated

  Integration of the mutliple aspects and approaches required including also the use and the end-of-life phase


Thank you for your attention.

Prof. Dr. Frank Schultmann Karlsruhe Institute of Technology (KIT) Institute for Industrial Production (IIP) French-German Institute for Environmental Research (DFIU) Hertzstraße 16 D-76187 Karlsruhe Germany T: +49 721 608 4 4569 E: [email protected] Web: www.iip.kit.edu

1 system analysis of biomass based value chains by prof dr frank schultmann

Documents