IER INTEGRATED ASSESSMENT OF ENERGY EFFICIENCY MEASURES IN AN INDUSTRIAL ENERGY SUPPLY SYSTEM - A CASE STUDY OF THE GERMAN PLASTIC PROCESSING INDUSTRY

Transcription

1 Institut für Energiewirtschaft und Rationelle Energieanwendung (IER) INTEGRATED ASSESSMENT OF ENERGY EFFICIENCY MEASURES IN AN INDUSTRIAL ENERGY SUPPLY SYSTEM - A CASE STUDY OF THE GERMAN PLASTIC PROCESSING INDUSTRY 15 th IAEE European Conference Vienna, Austria Roman Flatau 1 IER

2 Introduction and Objective 2

3 Index 1990 = 100 Introduction and Objective The German industry had a share of 29 % of final energy consumption in INCREASING FINAL ENERGY PRODUCTIVITY FINAL ENERGY CONSUMPTION IN 2015 by 2.1 %/a from 2008 until 2050 Industry: 716 TWh (29 %) Final Energy Productivity GDP (adjusted) Final Energy Productivity (trend) Final Energy Consumption Development Trajectory Source: Federal Ministry for Economic Affairs and Energy (2014) Goal 2020 = 174 FEP 2015 = 148 Trend 2020 = % 29 % Total: 2,468 TWh 26 % 29 % 35 % 65 % Traffic Industry Process tech. Cross-cutting tech. Households Business/trade & services Year Source: AG Energiebilanzen e. V. (2016) The German industry is of particular importance when trying to reach the proclaimed energy efficiency goals. 3

4 Index 1990 = 100 Introduction and Objective Industrial decision-makers depend on detailed information about energy efficiency measures. INCREASING FINAL ENERGY PRODUCTIVITY FINAL ENERGY CONSUMPTION IN 2015 by 2.1 %/a from 2008 until 2050 Industry: 716 TWh (29 %) Final Energy Productivity GDP (adjusted) Final Energy Productivity (trend) Final Energy Consumption Development Trajectory Source: Federal Ministry for Economic Affairs and Energy (2014) Goal 2020 = 174 FEP 2015 = 148 Trend 2020 = % 29 % Total: 2,468 TWh 26 % 29 % 35 % 65 % Traffic Industry Process tech. Cross-cutting tech. Households Business/trade & services Year Source: AG Energiebilanzen e. V. (2016) The German industry is of particular importance when trying to reach the proclaimed energy efficiency goals. 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. 4

5 Index 1990 = 100 Introduction and Objective Interactions between EEM are often neglected when evaluating energy saving potentials. INCREASING FINAL ENERGY PRODUCTIVITY FINAL ENERGY CONSUMPTION IN 2015 by 2.1 %/a from 2008 until 2050 Industry: 716 TWh (29 %) Final Energy Productivity GDP (adjusted) Final Energy Productivity (trend) Final Energy Consumption Development Trajectory Source: Federal Ministry for Economic Affairs and Energy (2014) Goal 2020 = 174 FEP 2015 = 148 Trend 2020 = % 29 % Total: 2,468 TWh 26 % 29 % 35 % 65 % Traffic Industry Process tech. Cross-cutting tech. Households Business/trade & services Year Source: AG Energiebilanzen e. V. (2016) The German industry is of particular importance when trying to reach the proclaimed energy efficiency goals. 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 as Interactions between energy efficiency measures on the economic energy efficiency potential. 5

6 Method 6

7 Relative discharge head (H B /H BP ) Method This holistic approach facilitated the consideration of dynamic system behavior & interactions. Input Model Results Representative companies German plastic processing industry Production process Production capacity/utilization Shift model Energy efficiency measures Application potential Costs and lifetime Model structure Technology-oriented bottom-up energy demand model Modular hierarchy structure Mathematical model description Deterministic Non-linear programming Heuristic optimisation approach Final energy demand Technology specific (economic and technical) energy saving potentials Optimised investment schedule 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) Modeling of an industrial energy supply system 1,5 1,4 1,3 1,2 1,1 1,0 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0,1 system curve operation point pump curve 0,0 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 Relative volume flow (Q B /Q BP ) 7

8 Case-study for the German plastic processing industry 8

9 Case-study for the German plastic processing industry The German plastic processing industry is strongly shaped by medium-sized companies 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). Source: Dispan (2013) 9

10 Case-study for the German plastic processing industry and four characteristic production processes used for different product characteristics. 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). Source: Dispan (2013) Injection moulding Blow moulding RELEVANT PRODUCTION PROCESSES Average Injec. moulding Injection Extrusion Blow-moulding Thermoforming Thermoforming Specific Energy Consumption [kwh/kg] Specific Energy Consumption [kwh/kg] Thermoforming Source: Own calculations based on Consultic (2015), German Federal Statistical Office (2013), Urbanek, Saal (2011), EUROMAP (2011) Extrusion 10

11 Case-study for the German plastic processing industry The generic injection moulding manufacturer produces small components (weight = 0.12 kg). KEY INFORMATION 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 mio. parts per year (average component weight: 0.12 kg). BASE SCENARIO Electricity price: EUR/MWh el Gas price: 3.37 EUR/MWh th Increase of energy carrier prices: 1.0 %/a Interest rate: 15 % System boundary: factory (F-SEC) energy carrier electricity, gas material PP, PE, PET, etc. infrastructure production periphery storage mixing drying transport machine injection moulding product 11

12 Results 12

13 Marginal Energy Conservation Costs [EUR/MWh] Results The economic energy saving potential equals 13.8 % of the total final energy consumption Motors Pumps Ventilation Lighting Compressed air Cooling Space heating > 500 EUR/MWh 300 Economic energy saving potential = MWh/a Technical energy saving potential = 1,144.5 MWh/a ,000 Energy Saving Potential [MWh/a] 13

14 Temperature [ C] Results Using free cooling (EEM 5.4) saves 40.1 % of final energy consumption for process cooling. 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) Temperature (production facility) Outside temperature hydraulics: 14 C moulds: 5 C 0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 9,000 Time [h] 14

15 Results Interactions between EEM significantly influence the (economic) energy saving potential. Interactions on a factory level The 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 no interactions between them. M Interactions on a technology-system level When 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 level The 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. 15

16 Marginal Energy Conservation Costs [EUR/MWh] Results Changes in the interest rate have the highest impact on the economic energy saving potential Base scenario Energy carrier prices: + 15 % Energy carrier prices: - 15 % Development of energy carrier prices: 2 %/a Development of energy carrier prices: 0 %/a Interest rate: 30 % Interest rate: 5 % 100 Interest rate 30 % Interest rate 5 % Energy Saving Potential [MWh/a] 16

17 Marginal Energy Conservation Costs [EUR/MWh] Results There is a strong correlation between the economic ESP an the changed parameters Correlation Interest rate: Energy carrier prices: Development of energy carrier prices: Results Brunke, Blesl (2014) Energy Saving Potential [MWh/a] 17

18 Marginal Energy Conservation Costs [EUR/MWh] Results A variation of the input parameters does not lead to a parallel shift of the MECC-Curve ,000 Energy Saving Potential [MWh/a] 18

19 Marginal Energy Conservation Costs [EUR/MWh] Results Extrapolating the results onto the national level leads to an economic ESP of 11.9 to 15.4 %. 500 > 500 EUR/MWh Worst-case: GWh/a Best-case: GWh/a ,000 Energy Saving Potential [GWh/a] 19

20 Conclusion 20

21 Conclusion Impact of interactions between energy efficiency measures The impact of interactions differs significantly when looking at a factory compared to an individual energy efficiency measure. When evaluating individual energy efficiency measures the changes of the energy saving potential due to interactions amounts for up to 50 %. Energy efficiency potential in the German plastic processing industry The results from the conducted case-study (injection moulding manufacturer producing small parts) show, that there is still a significant economic energy saving potential of % for the evaluated cross-cutting technologies. Almost 74 % of the identified technical energy saving potential is cost-effective. Further research With regard to the German plastic processing industry further research is necessary to evaluate the impact of different product sizes ( different injection cycling times). Furthermore additional research is recommended to evaluate the economic energy saving potential for other production processes (extrusion, blow-moulding, thermoforming) in a similar way. 21

22 M.Sc. Roman Flatau Telefon +49 (0) Prof. Dr.-Ing. Peter Radgen Telefon +49 (0) Universität Stuttgart Institute of Energy Economics and Rational Energy Use Department of Energy Efficiency (EE) Heßbrühlstr. 49a D Stuttgart 22