INTEGRATED ASSESSMENT OF ENERGY EFFICIENCY MEASURES …€¦ · IER University of Stuttgart 15th IAEE European Conference, Vienna, Austria 4th September 2017 1 Integrated assessment

14th September 2017IER University of Stuttgart 15th IAEE European Conference, Vienna, AustriaIntegrated assessment of energy efficiency measures in an industrial energy supply system – A case-study of the German plastic processing industryRoman Flatau and Peter Radgen

Institut für Energiewirtschaft und

Rationelle Energieanwendung (IER)

IER

INTEGRATED ASSESSMENT OF ENERGY EFFICIENCY MEASURES IN AN INDUSTRIAL ENERGY SUPPLY SYSTEM

-A CASE STUDY OF THE GERMANPLASTIC PROCESSING INDUSTRY

4th September 201715th IAEE European ConferenceVienna, Austria

Roman Flatau


Introduction and Objective


Industry

Households

Business/trade & services

Traffic

Process tech.Cross-cutting tech.

Total:2,468 TWh

16 %

29 %

29 %

26 %35 %

65 %

75

100

125

150

175

200

Ind

ex

19

90

= 1

00

Year

Final Energy Productivity Final Energy Consumption

GDP (adjusted) Development Trajectory

Final Energy Productivity (trend)

• … by 2.1 %/a from 2008 until 2050

INCREASING FINAL ENERGY PRODUCTIVITY… FINAL ENERGY CONSUMPTION IN 2015

• Industry: 716 TWh (29 %)


The German industry had a share of 29 % of final energy consumption in 2015.

The German industry is of particular importance when trying to reach the proclaimed energyefficiency goals.

FEP2015 = 148

Goal2020 = 174

Trend2020 = 157

Source: Federal Ministry for Economic Affairs and Energy (2014)

Source: AG Energiebilanzen e. V. (2016)


Industry

Households


Traffic


Total:2,468 TWh

16 %

29 %

29 %

26 %35 %

65 %

75

100

125

150

175

200

Ind

ex

19

90

= 1

00

Year




• … by 2.1 %/a from 2008 until 2050




Industrial decision-makers depend on detailed information about energy efficiency measures.

At this point, there is no method for the holistic assessment of energy efficiency measures considering the dynamic system behavior as well as the interactions between energy efficiency measures.


FEP2015 = 148

Goal2020 = 174

Trend2020 = 157




Industry

Households


Traffic


Total:2,468 TWh

16 %

29 %

29 %

26 %35 %

65 %

75

100

125

150

175

200

Ind

ex

19

90

= 1

00

Year




• … by 2.1 %/a from 2008 until 2050




Interactions between EEM are often neglected when evaluating energy saving potentials.

At this point, there is no method for the holistic assessment of energy efficiency measures considering the dynamic system behavior as well as the interactions between energy efficiency measures.


The main objective of this study is to evaluate the impact of the dynamic system behavior as well asInteractions between energy efficiency measures on the economic energy efficiency potential.

FEP2015 = 148

Goal2020 = 174

Trend2020 = 157




Method


This holistic approach facilitated the consideration of dynamic system behavior & interactions.

Method

Input Model Results

Modeling of an industrial energy supply system

Representative companies • German plastic processing industry• Production process• Production capacity/utilization• Shift model

Energy efficiency measures• Application potential• Costs and lifetime

• Final energy demand• Technology specific (economic and

technical) energy saving potentials• Optimised investment schedule

Model structure• Technology-oriented bottom-up

energy demand model• Modular hierarchy structure

Mathematical model description• Deterministic • Non-linear programming• Heuristic optimisation approach

Implemented cross-cutting technologies• Production: electric motors, pumps, ventilation, compressed

air, process-cooling• Infrastructure: lighting, air conditioning and space heating

Evaluation of final energy consumption• Endogenous calculation of product specific synthetic load

profiles for useful energy.• Technology specific time resolution considering partial as

well as full load operation.• Generic efficiency diagrams for cross-cutting technologies.• Different control concepts (e. g. for a pump: throttle control,

bypass control, on-off control, speed control)0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1,0

1,1

1,2

1,3

1,4

1,5

0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 1,1 1,2 1,3 1,4 1,5 1,6 1,7 1,8 1,9 2,0 2,1 2,2

Rela

tive d

isch

arg

eh

ea

d(H

B/H

BP)

Relative volume flow (QB/QBP)

operation point

system curve

pump curve


Case-study for theGerman plastic processing

industry


INDUSTRY STRUCTURE

• NACE 22.2 Manufacturing of plastic products

• Companies: 2,845

• Employees: 301,834

• Turnover: 56,121 mio. EUR

• Export share: 35,3 %

• About 92 % of the companies have less than 250

employees (Ø 106 employees per company).

Case-study for the German plastic processing industry

The German plastic processing industry is strongly shaped by medium-sized companies …

Source: Dispan (2013)


INDUSTRY STRUCTURE RELEVANT PRODUCTION PROCESSES


… and four characteristic production processes used for different product characteristics.

Thermoforming

0.71

0.70

0.41

1.51

0.78

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60

Thermoforming

Blow-moulding

Extrusion

Injection moulding

Average

Specific Energy Consumption [kWh/kg]

Average

Injec. moulding

Extrusion

Blow-moulding

Thermoforming

0.00 0.50 1.00 1.50Specific Energy Consumption [kWh/kg]

0.78

1.51

0.41

0.70

0.71

Blow mouldingInjection moulding

Extrusion

• NACE 22.2 Manufacturing of plastic products

• Companies: 2,845

• Employees: 301,834

• Turnover: 56,121 mio. EUR

• Export share: 35,3 %

• About 92 % of the companies have less than 250

employees (Ø 106 employees per company).Source: Dispan (2013)

Source: Own calculations based on Consultic (2015), German Federal Statistical Office (2013), Urbanek, Saal (2011), EUROMAP (2011)


• The overall final energy consumption of an

average injection moulding manufacturer is

8,026 MWh/a (specific energy consumption:

F-SEC: 4.35 kWh/kg).

• Production of 15.57 mio. parts per year (average

component weight: 0.12 kg).

• Electricity price: 15.02 EUR/MWhel

• Gas price: 3.37 EUR/MWhth

• Increase of energy carrier prices: 1.0 %/a

• Interest rate: 15 %

KEY INFORMATION BASE SCENARIO


The generic injection moulding manufacturer produces small components (weight = 0.12 kg).

storage

mixing

drying

transport

injection mouldingperiphery machine

productioninfrastructure

System boundary: factory (F-SEC)

energy carrierelectricity, gas

materialPP, PE, PET, etc.

product


Results


MotorsPumpsVentilationLighting

Compressed airCoolingSpace heating

> 500 EUR/MWh

Economic energy saving potential = 843.9 MWh/a

500

400

300

200

100

0

-100

-200

-300

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]

0 200 400 600 800 1,000Energy Saving Potential [MWh/a]

Technical energy saving potential = 1,144.5 MWh/a

Results

The economic energy saving potential equals 13.8 % of the total final energy consumption.


40353025201510

50

-5-10-15

Temperature (production facility)Outside temperature

hydraulics: 14 °C

moulds: 5 °C

Using free cooling (EEM 5.4) saves 40.1 % of final energy consumption for process cooling.

ResultsTe

mp

era

ture

[°C

]

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000Time [h]

• The demand for cooling the injection moulds as well as the hydraulics is nearly constant.

• The process cooling is supplied at an average energy efficient ratio (EER) of 1.4 using compression

refrigeration machines.

• Average EER of free cooling is nearly eight times higher than the EER of the compression refrigeration

machines. Thus 40.1 % of final energy consumption for process cooling can be saved using free cooling.

• This complies with estimations of manufacturers for refrigeration systems who indicate savings of up to

80 % (depending on the temperature).


Interactions between EEM significantly influence the (economic) energy saving potential.

Results

Interactions on a factory levelThe economic energy saving potential of the whole factory is reduced by 8.3 % compared to the assumption, that all energy efficiency measures are mutually exclusive and there are nointeractions between them.

Interactions on a technology-system levelWhen evaluating individual technology-systems the impact of interactions increases. For example, the economic energy saving potential for the compressed air system is reduced by 17.1 % due to interactions.

Interactions on a energy efficiency measure levelThe impact of interactions is even larger when looking at individual EEM. For example the energy saving potential of an IE4 motor in the air-cooled condenser (liquefier) of the compression refrigeration unit is reduced by 57.7 %.

Neglecting interactions when evaluating EEM might lead to a significant overestimation of the energy saving potential and thereby can lead to disappointments with energy saving investments.

M


Changes in the interest rate have the highest impact on the economic energy saving potential.

Results

Interest rate 5 %

Interest rate 30 %

Base scenarioEnergy carrier prices: + 15 %Energy carrier prices: - 15 %Development of energy carrier prices: 2 %/aDevelopment of energy carrier prices: 0 %/aInterest rate: 30 %Interest rate: 5 %

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]

0 200 400 600 800 1000Energy Saving Potential [MWh/a]

500

400

300

200

100

0

-100

-200

-300


Results

There is a strong correlation between the economic ESP an the changed parameters.

0 200 400 600 800 1000Energy Saving Potential [MWh/a]

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]500

400

300

200

100

0

-100

-200

-300

Correlation

Interest rate:Energy carrier prices:Development of energy carrier prices:

Brunke, Blesl (2014)Results

-0.98+0.89+0.88

-0.95+0.89

-


Results

A variation of the input parameters does not lead to a parallel shift of the MECC-Curve.

0 200 400 600 800 1,000Energy Saving Potential [MWh/a]

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]500

400

300

200

100

0

-100

-200

-300


Extrapolating the results onto the national level leads to an economic ESP of 11.9 to 15.4 %.

Results

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]> 500 EUR/MWh

Best-case: 808.8 GWh/a

Worst-case: 724.1 GWh/a

Mar

gin

al E

ne

rgy

Co

nse

rvat

ion

Co

sts

[EU

R/M

Wh

]

0 100 200 300 400 500 600 700 800 900 1,000 Energy Saving Potential [GWh/a]

500

400

300

200

100

0

-100

-200

-300


Conclusion


Conclusion

Impact of interactions between energy efficiency measuresThe impact of interactions differs significantly when looking at a factory compared to an individual energy efficiency measure. When evaluating individual energy efficiency measuresthe changes of the energy saving potential due to interactions amounts for up to 50 %.

Energy efficiency potential in the German plastic processing industryThe results from the conducted case-study (injection moulding manufacturer producing smallparts) show, that there is still a significant economic energy saving potential of 11.9-15.4 % for the evaluated cross-cutting technologies. Almost 74 % of the identified technical energy savingpotential is cost-effective.

Further researchWith regard to the German plastic processing industry further research is necessary to evaluatethe impact of different product sizes ( different injection cycling times). Furthermore additional research is recommended to evaluate the economic energy saving potential forother production processes (extrusion, blow-moulding, thermoforming) in a similar way.


E-Mail

Telefon +49 (0) 711 685-

Universität Stuttgart

E-Mail

Telefon +49 (0) 711 685-

Department of Energy Efficiency (EE)

Heßbrühlstr. 49a

D-70565 Stuttgart

Prof. Dr.-Ing. Peter Radgen

878 01

Institute of Energy Economics and Rational Energy Use

[email protected]

M.Sc. Roman Flatau

878 26

[email protected]

INTEGRATED ASSESSMENT OF ENERGY EFFICIENCY MEASURES …€¦ · IER University of Stuttgart 15th IAEE European Conference, Vienna, Austria 4th September 2017 1 Integrated assessment

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