Solar Energy for Industrial Rooftops: An Economic and

Environmental Optimization

School of Mechanical and Manufacturing Engineering

Asia-Pacific Solar Research Conference

Solar Energy for Industrial Rooftops: An Economic and Environmental

Optimization

Bany Mousa Osama1, Taylor, Robert A1.

1University of New South Wales, Sydney, Australia

Energy systems/ Sustainable manufacturing

O.banymousa@student.unsw.edu.au

1

Solar Thermal

ST [2]Photovoltaic

PV [1]

2

Compact linear Fresnel

Collector [3]

PVT Collector [4]

Solar Energy for Industrial Rooftops: An Economic and

Environmental Optimization

Industrial Energy Demand [5,6,7]

3

MY APPLICATION

Heat: 85 EJElectrical: 44 EJ

Low: 25.5 EJMedium: 23 EJHigh: 36.5 EJ

Industrial Processes: 129 EJOther: 110 EJ

Research Question: What is the right mix of technologies for

industrial rooftops?

– Important Factors:

• Medium and high temperatures heat are needed.

• Environmental emissions reductions, (global variation in climate)

• Limited rooftop space

• Economics

Approach: Investigate global trade-offs to find an optimum solar

technology mix using transient performance and life cycle analysis.

– Note: The ratio can be optimized based on many objectives (and there’s no

prior literature to date on this topic)

Research Question and Approach

4

Aims

• The right mix of the solar technologies for industrialapplications– Technologies

• Solar thermal

• Photovoltaic

• Photovoltaic + solar thermal

– Objectives• Annual performance

• Embodied energy

• Embodied emissions

• Economic (levelized cost of energy)

• A comparison between locations that has differentirradiation and beam component.

5

Application - Process

• The annual performance of a sterilization

process that requires steam at 134°C outlet

temperature was modelled using TRNSYS.

• The collector output was maintained at 180°C

to drive a heat recovery steam generator

(HRSG).

6

7

System model (TRNSYS schematic diagram)

Side-by-Side PV and ST Systems

and Geographical Locations

• ST versus PV was varied from 0-1

• Ratio =𝑆𝑜𝑙𝑎𝑟 𝑐𝑜𝑙𝑙𝑒𝑐𝑡𝑜𝑟𝑎𝑟𝑒𝑎

𝑓𝑎𝑐𝑡𝑜𝑟𝑦 𝑎𝑟𝑒𝑎

• 0 presents a stand-alone PV system

1 presents the thermal-only system.

8

Environmental impacts and savings analysis

9

Location Installation

capital cost

ratio [%]

ST

including

Installatio

n ($/m2)

PV panels with installation

$/W

(IRENA

[8]

$/m2 LCOE $/kWhel [8]

Residen

tial

Commerc

ial

China 7.26 370 1.168 201 0.1059 0.084

Australia 43.89 496 1.567 270 0.1026 --

US 50 518 2.678 461 0.1545 0.112

Location Average

interest rate

Minimum

interest rate

Maximum

interest rate

China 5.1 4.4 6

Australia 5.9 5.2 7

US 3.3 3.2 3.5

5 years average interest rates for several

countries with interest variation

Location ST-

Embodied

GHGe

(kg/m2

aperture)

PV-

Embodied

GHGe

(kg/m2

aperture)

CT or ETS ($/tonne)

[9]

Natural

gas

emission

kgCO2eq/

GJth

China 803 556 9 [Beijing ETS] 61.84

Australia 892 595 17.95 [10] 69.72

US 539 461 15.10 66.74

Environmental impacts of solar technologies

Global average annual Natural gas price variation

Solar technologies estimated costs (including Installation)

Objective Functions

1. 𝑆𝐹 =𝐿𝑜𝑎𝑑 𝐺𝐽𝑡ℎ −𝐴𝑢𝑥(𝐺𝐽𝑡ℎ)

𝐿𝑜𝑎𝑑 (𝐺𝐽𝑡ℎ)

2. 𝐸𝐸 𝑃𝐵𝑇 =𝐸𝐸(𝐺𝐽𝑡ℎ)

𝑆𝐹∗𝐿𝑜𝑎𝑑 𝐺𝐽𝑡ℎ/𝑦𝑒𝑎𝑟;

• 𝐸𝐸 = 2.62 𝑆𝑇𝑎𝑟𝑒𝑎 + 2.66 𝑃𝑉𝑎𝑟𝑒𝑎; 𝐸𝐸𝑆𝑇 = 2.62 𝐺𝐽𝑡ℎ/𝑚2, 𝐸𝐸𝑃𝑉 = 2.66 𝐺𝐽𝑡ℎ/𝑚

2

3. 𝐺𝐻𝐺𝑒𝑃𝐵𝑇 =𝐸𝑚𝑏𝑜𝑑𝑖𝑒𝑑 𝐺𝐻𝐺𝑒(𝑘𝑔𝐶𝑂2𝑒𝑞)

𝑆𝐹∗𝐿𝑜𝑎𝑑 𝐺𝐽𝑡ℎ/𝑦𝑒𝑎𝑟 ∗𝑁𝐺𝑒[𝑘𝑔𝐶𝑜2𝑒𝑞

𝐺𝐽𝑡ℎ]

• 𝐸𝐺𝐻𝐺𝑒 = 𝑃𝑉𝐶𝑂2𝑒𝑞𝑘𝑔𝐶𝑂2𝑒𝑞

𝑚2 ∗ 𝑃𝑉𝑎𝑟𝑒𝑎 + 𝑆𝑇𝐶𝑂2𝑒𝑞𝑘𝑔𝐶𝑂2𝑒𝑞

𝑚2 ∗ 𝑆𝑇𝑎𝑟𝑒𝑎

4. 𝐿𝐶𝑂𝐸($/(𝑘𝑊ℎ𝑡ℎ) =𝑆𝑦𝑠𝑡𝑒𝑚 𝑐𝑜𝑠𝑡

𝑡=1𝐿𝑇 𝑆𝐹∗𝐿𝑜𝑎𝑑 𝐺𝐽𝑡ℎ / 1+𝑖

𝑡

5. 𝐿𝐶𝐶𝐿𝐶𝑂𝐸($/(𝑘𝑊ℎ𝑡ℎ) =𝐿𝐶𝐶

𝑡=1𝐿𝑇 0.0036∗𝑆𝐹∗𝐿𝑜𝑎𝑑 𝐺𝐽𝑡ℎ / 1+𝑖

𝑡

• 𝑆𝑦𝑠𝑡𝑒𝑚 𝐶𝑜𝑠𝑡 = 𝑃𝑉𝑎𝑟𝑒𝑎𝐶𝑜𝑠𝑡𝑃𝑉 + 𝑆𝑇𝑎𝑟𝑒𝑎 ∗ 𝐶𝑜𝑠𝑡𝑆𝑇

• 𝐿𝐶𝐶 = 𝐸𝐸 𝐺𝐽𝑡ℎ ∗ 𝑁𝐺$

𝐺𝐽𝑡ℎ+ 𝐸𝐺𝐻𝐺𝑒 𝐾𝑔𝐶𝑜2𝑒𝑞 ∗ 𝐶𝑇

$

𝐾𝑔𝐶𝑂2𝑒𝑞+

𝑠𝑦𝑠𝑡𝑒𝑚 𝐶𝑜𝑠𝑡 ($)

10

11

Optimization Flow Chart

TRNSYS

Environment

Genopt

Environment

Industrial

Load

Weather

Data

Key

Inputs

System Energy

Simulation

Design Parameters

Output Parameters

Technical Function

Cost Function

Environmnetal Function

Select Optimization algorithm

Stopping Criteria

Satisfied?

End

Yes

No

Update d

esign v

ariables

Optimization Results

12

Optimum solar technology mix in various locations

based on the performance objective function

Optimum solar technology mix in various locations based on the embodied objective

functions: (A) Embodied energy function; (B) Embodied emission function

Optimization Results

13Optimum solar technology mix in various locations based on cost functions:

(A) Levelized cost of energy; (B) Life cycle levelized cost of energy

14

Optimization Results – Cost variation

Economical objective function optimum distribution with ST to PV cost variation

15

Worldwide Profiling

16

System model (flow diagram)

FU: Heat output per unit area

17

18

Multi-objective Optimization Results

Fig 7. Optimum solar mix using several criteria Pareto frontier in Alice Springs/ Australia, Andir/ China and

Santiago/ Chile A: Economical – environmental criteria B: Economical – Technical criteria C: Environmental –

Technical criteria D: Economical – Technical – Environmental criteria

19

Worldwide Profiling

20

Multi-objective Optimization Results

Optimization summary- Ratio of ST area to mixed solar system area

1. https://au.pinterest.com/pin/555209460286792472/

2. http://www.newmexicosolarandwind.com/Solar%20Thermal.htm

3. http://products.newformenergy.ie/photovoltaic-thermal-pvt.php

4. Zhang, X., et al., Review of R&D progress and practical application of the solar photovoltaic/thermal

(PV/T) technologies. Renewable and Sustainable Energy Reviews, 2012. 16(1): p. 599-617.

5. U.S. Energy Information Administration. International 126 Energy Outlook 2016. Available from:

http://www.eia.gov/forecasts/ieo/industrial.cfm.

6. Institute, Environmental and Energy Study. solar thermal energy for industrial uses. 2011; Available from:

http://www.eesi.org/files/solar_thermal_120111.pdf.

7. Vannoni, Battisti, and Drigo, Potential for Solar Heating Industrial Processes. Report within IEA SHC

Task33/IV. 2008: Rome,Italy.

8. I. Staffell, A review of domestic heat pump coefficient of performance (2009)

References

2121

Cost Analysis

22

𝑋𝑒𝑞_𝑃𝐵𝑇 = 1 −𝑥

𝑆𝐹

𝑥 =𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡 ∗ 𝑖 %

𝑇𝑜𝑡𝑎𝑙 𝑠𝑎𝑣𝑖𝑛𝑔𝑠 ($)

23

Cost Analysis

𝑋𝑒𝑞_𝐼𝑅𝑅 =𝐴𝑛𝑛𝑢𝑎𝑙 𝑠𝑎𝑣𝑖𝑛𝑔𝑠

𝑇𝑜𝑡𝑎𝑙 𝑐𝑜𝑠𝑡

Initial Work-1st Year

Solar thermal circuit flow diagram

2424

Model validation/Tolerance

0.00%

0.10%

0.20%

0.30%

0.40%

0.50%

0.60%

0.70%

0.80%

0.90%

0.00E+00

2.00E+07

4.00E+07

6.00E+07

8.00E+07

1.00E+08

1.20E+08

1.40E+08

1.60E+08

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tole

ran

ce %

En

erg

y (

J)

Gains Losses Tolerance

2525

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55 0.6 0.65

Eff

icie

ncy

'

∆T/G

FPC

TVP

ETC

PTC

MUSIC

MCT

G =1000 W/m2

instantaneous efficiency comparison

Ƞ = 𝐹’ 𝜏𝛼 ∗ 𝐼𝐴𝑀 – c1 ( Tavg−Ta

Gt) – c2 (

(Tavg−Ta)2

Gt) ; (

𝐺𝑏

𝐺𝑡)

2626

Annual efficiency comparison

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 50 100 150 200 250 300 350 400 450 500An

nu

al

effi

cien

cy

Tout when Tin = 20

TVP

ETC

PTC

MUSIC

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 10 20 30 40 50 60 70 80 90

Inci

den

t a

ng

le m

od

ifie

r

Angle (degree)

TVP IAM PTC transverse IAM ETC transverse IAM MUSIC transverse IAM

Incident angle modifier

2727

Parametric Study

The annual performance of a sterilization process that requires steam at

134°C outlet temperature was compared using TRNSYS software :

The collector output was maintained at 180°C to drive a heat recovery

steam generator (HRSG).

1) Four different solar collectors for.

2) Six different transient load profiles.

3) Two tank configurations

4) Two controller methods.

Finally, all (4x6x2x2 = 96) systems were compared for two Australian

locations, Sydney and Alice Springs (96x2 = 192).

2828

2nd year: Beam split PVT system

Beam splitting strategy- from

• Technology purpose

• PV performance

• Thermal collector performance

• Operating temperature

• Available literature (four filter designs)

Wavelength

range (nm)

Ratio- ST

absorbed

radiation

PV cell

efficiency

rise

Crisostomo et al. 732-1067 71.5% 9%

Sabry et al. 450-920 41% 6%

Liu et al. 590-1082 51% 12.5%

Kandilli 400-800 46% 10%

2929

Beam splitting PVT filters

Filter bandwidth effect on ‘uncoupled’ PV/T splitting collector output (bars, which

correspond to the left y-axis) and solar contribution (lines, with correspond to the

right y-axis) for two PV cell types (White background- Alice Springs, black

background- Santiago)

DNI ratio and system contribution for

different beam split technologies

3030

0

2

4

6

8

10

12

14

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Req

uir

ed e

ner

gy

(G

J/m

2)

Case study [N°]

Equipment maufacturing

Overhead operations

Cell,module processing

subtrate and encapsulation

Cell material

Frame

Module Assembly

Cell Production

Wafer Process

CZ Process

MG-Si

Si Feedstock

Mono Si Poly Si a-Si

Embodied energy requirements

for solar silicon PV panels processes

3131

Some of the industrial processes required temperature range

3232

Industry Process Temperature (°C)

Food & Beverage Evaporating

Sterilisation

Drying

Cooking

40 – 130

100 – 140

40 – 200

70 – 120

Tinned food Sterilization 110 – 120

Textile Colouring 40 – 130

Paper Bleaching

Drying

130 – 150

95 – 200

Metal Drying 60 – 200

Bricks curing Curing 60 – 140

Plastics Separation

Drying

200 – 220

50 – 150

Chemical Soups

Distillation

Cooking

Compression

200 – 260

100 – 200

85 – 110

110 – 170

Boundaries-System Level

3333

PV manufacturing and inventory data

3434

3

5

Methods/Approaches