Mahlberg, Bernhard and Frank-Stocker, Andrea and Koller, Wolfgang and Ramerstorfer, Christian (2023): Cost efficiency of renewable district heating systems: the case of Austria.
Preview |
PDF
Cost efficiency paper_WP.pdf Download (1MB) | Preview |
Abstract
Heat generation based on conventional fossil fuels is considered to be the cause of a significant proportion of greenhouse gas emissions. Achieving the climate protection goals therefore requires a transition to renewable energy sources such as biomass. Establishing renewable district heating (DH) systems is considered as an important cornerstone of a decarbonized energy system. This study estimates the cost efficiency of biomass-based DH systems. It expands the benchmarking currently used in Austria which relies on simple key performance indicators by a new type of multi-variate approach based on efficiency estimates from Data Envelopment Analysis (DEA). The performance indicator calculated in this way considers all essential factors of production simultaneously and estimates the cost saving potentials of each individual system examined. By decomposing cost efficiency into a technical and allocative component, the causes of inefficiency are revealed. A subsequent regression analysis examines how system-specific technical, structural features and the regional environmental conditions of the respective systems influence their performance. Finally, the results of the regression analysis are used to calculate the managerial inefficiency purged of the influence of structural peculiarities and operating environment. This part of the overall inefficiency is caused by the operator's decisions and can therefore be reduced by changing the operator's behaviour. The applicability of the approach developed here is shown empirically using a sample of biomass-based DH systems from Austria.
Item Type: | MPRA Paper |
---|---|
Original Title: | Cost efficiency of renewable district heating systems: the case of Austria |
English Title: | Cost efficiency of renewable district heating systems: the case of Austria |
Language: | English |
Keywords: | sustainable heat generation; energy transition; biomass; climate protection; Data Envelopment Analysis |
Subjects: | D - Microeconomics > D2 - Production and Organizations > D24 - Production ; Cost ; Capital ; Capital, Total Factor, and Multifactor Productivity ; Capacity Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q41 - Demand and Supply ; Prices Q - Agricultural and Natural Resource Economics ; Environmental and Ecological Economics > Q4 - Energy > Q42 - Alternative Energy Sources |
Item ID: | 118595 |
Depositing User: | Bernhard Mahlberg |
Date Deposited: | 14 Sep 2023 23:26 |
Last Modified: | 14 Sep 2023 23:26 |
References: | Agrell, P., Bogetoft, P. (2005). Economic and environmental efficiency of district heating plants. Energy Policy. 33. 1351-1362. https://doi.org/10.1016/j.enpol.2003.12.011. Agrell, P., Bogetoft, P. (2016). Endogenous Common Weights as a Collusive Instrument in Frontier-Based Regulation, International Series in Operations Research & Management Science, in: Juan Aparicio, C. A. Knox Lovell, Jesus T. Pastor (ed.), Advances in Efficiency and Productivity, chapter 0, pages 181-194, https://doi.org/10.1007/978-3-319-48461-7_8 Agrell, P. J., Bogetoft, P. (2017). Regulatory Benchmarking: Models, Analyses and Applications. Data Envelopment Analysis Journal 3, 49–91. https://doi.org/10.1561/103.00000017 Bogetoft, P., Otto, L. (2011). Benchmarking with DEA, SFA, and R. Springer Science+Business Media, New York. https://doi.org/10.1007/978-1-4419-7961-2 Banker, R., Charnes, A., Cooper, W.W. (1984). Some models for estimating technical scale inefficiencies in data envelopment analysis. Management Science 30, 1078–1092. https://www.jstor.org/stable/2631725 Banker, R.D., Morey, R.C. (1986). Efficiency analysis for exogenously fixed inputs and outputs. Operations Research 34, 513–521. https://doi.org/10.1287/opre.34.4.513 Banker, R., Natarajan, R., Zhang, D. (2019). Two-Stage Estimation of the Impact of Contextual Variables in Stochastic Frontier Production Function Models Using Data Envelopment Analysis: Second Stage OLS versus Bootstrap Approaches, European Journal of Operational Research 278, 368-384. https://doi.org/10.1016/j.ejor.2018.10.050. BMLFUW (2015). Efficient Biomass District Heating. Quality Management for Heating Plants, 1st edition, Federal Ministry for Agriculture, Forestry, Environment and Water Management (Bundesministerium für Land- und Forstwirtschaft, Umwelt und Wasserwirtschaft). https://www.klimaaktiv.at/dam/jcr:5542785f-6ed2-499e-ae11-65eedf32072a/Efficient%20Biomass%20District%20Heating.pdf BMNT (2019). klimaaktiv the Austrian Climate Protection Initiative. 3rd revised edition, Federal Ministry for Sustainability and Tourism (Bundesministerium für Nachhaltigkeit und Tourismus), Vienna. https://www.klimaaktiv.at/dam/jcr:d1a110bf-7d61-4c98-b419-a3492ac67d72/klimaaktiv%20the%20Austrian%20Climate%20Protection%20Initiative_2019_bf.pdf Borsche, R., Eimer, M., Garavello, M., Rossi, E. (2023). Analysis of District Heating Networks. Applied Mathematics & Optimization 87. https://doi.org/10.1007/s00245-022-09952-2 Büchele, R., Fallahnejad, M., Felber, B., Hasani, J., Kranzl, L., Themeß, N., Habiger, J., Hummel, M., Müller, A., Schmidinger, D. (2021). Potential for efficient heating and cooling. TU Wien commissioned by: Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology. https://energy.ec.europa.eu/system/files/2021-10/at_ca_2020_en.pdf Camanho, A.S., Dyson, R.G. (2008). A generalisation of the Farrell cost efficiency measure applicable to non-fully competitive settings. Omega 36, 147–162. https://doi.org/10.1016/j.omega.2005.12.004 CARMEN (2022). Planning Handbook. Developed by the Working Group QM for Biomass DH Plants. 3rd completely revised edition, C.A.R.M.E.N. e.V. Straubing 2022. https://programme2014-20.interreg-central.eu/Content.Node/ENTRAIN/QM-Planning-Handbook-3rd-edition-EN-220830.PDF Cucchiella, F., Gastaldi, M. (2014). Data Envelopment Analysis to Compare Renewable Energy Efficiency in the Italian Regions. In Advanced Materials Research (Vols. 912–914, pp. 1607–1611). Trans Tech Publications, Ltd. https://doi.org/10.4028/www.scientific.net/amr.912-914.1607 Daugavietis, J.E., Soloha, R., Dace, E., Ziemele, J. (2022). A Comparison of Multi-Criteria Decision Analysis Methods for Sustainability Assessment of District Heating Systems. Energies. 15, 2411. https://doi.org/10.3390/en15072411 Deutsches Umweltbundesamt (2007). Potenziale von Nah- und Fernwärmenetzen für den Klimaschutz bis zum Jahr 2020. https://www.umweltbundesamt.de/sites/default/files/medien/publikation/long/3501.pdf Dochev, I., Peters, I., Seller, H., Schuchardt, G. K. (2018). Analysing district heating potential with linear heat density. A case study from Hamburg. Energy Procedia 149, 410-419. https://doi.org/10.1016/j.egypro.2018.08.205 Eder, A., Mahlberg, B. (2018). Size, Subsidies and Technical Efficiency in Renewable Energy Production: The Case of Austrian Biogas Plants, The Energy Journal 39, 185-2010. https://doi.org/10.5547/01956574.39.1.aede Eder, A., Mahlberg, B., Stürmer, B. (2021). Measuring and explaining productivity growth of renewable energy producers: An empirical study of Austrian biogas plants. Empirica 48, 37–63 (2021). https://doi.org/10.1007/s10663-020-09498-y Elementenergy (2022). The Consumer Costs of Decarbonised Heat in Austria. Executive summary for Mutter Erde and GLOBAL 2000 September 2022, Element Energy Limited. https://www.global2000.at/sites/global/files/consumer-cost-of-heating-austria-executive-summary.pdf Farrell, M.J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society. Series A (General), 120, 253-290. https://doi.org/10.2307/23431 FMST – Federal Ministry for Sustainability and Tourism (2019). Integrated National Energy and Climate Plan for Austria 2021-2030 pursuant to Regulation (EU) 2018/1999 of the European Parliament and of the Council on the Governance of the Energy Union and Climate Action. https://energy.ec.europa.eu/system/files/2020-03/at_final_necp_main_en_0.pdf FGW – Fachverband der Gas- und Wärmeversorgungsunternehmungen (2021). Zahlenspiegel - Gas und Fernwärme in Österreich,“. https://www.fernwaerme.at/wp-content/uploads/2021/12/zasp21_hi.pdf Greene, W. (1980). Maximum Likelihood Estimation of Econometric Frontier Functions. Journal of Econometrics 13, 27-56. https://doi.org/10.1016/0304-4076(80)90041-X Good, J., Nussbaumer, T. (2004). Optimisation of biomass heating plants. 2nd World Conference / 13th European Conference and Technology Exhibition on Biomass for Energy, Industry and Climate Protection, Rome, 10–14 May 2004. (https://www.researchgate.net/publication/311846780_OPTIMISATION_OF_BIOMASS_HEATING_PLANTS) Graubner-Müller, C. (2018). Literaturrecherche. Numerische Simulationsmodelle und analytische Ansätze von Nah- und Fernwärmenetzen. München, GRIN Verlag. https://www.grin.com/document/438379 Harrison, J., Rouse, P. (2016). DEA and Accounting Performance Measurement, in: Hwang, S.-N., Lee H.-S., Zhu, J. (ed.), Handbook of Operations Analytics Using Data Envelopment Analysis, chapter 15, pp. 385-412, Springer. https://doi.org/10.1007/978-1-4899-7705-2_15 Henningsen, G., Henningsen, A., Schröder, S., Bolwig, S. (2015). The Development of Environmental Productivity: the Case of Danish Energy Plants. International Journal of Sustainable Energy Planning and Management 7. https://doi.org/10.5278/ijsepm.2015.7.7 Huber, P.J. (1981). Robust Statistics. New York: John Wiley and Sons. Hulten, C.R. (1990). The Measurement of Capital, in Berndt, E.R., Triplett, J.E. (eds.). Fifty Years of Economic Measurement, Studies in Income and Wealth, Chicago University Press for the National Bureau of Economic Research, 119–152. https://doi.org/10.7208/9780226044316-006 Hulten, C.R., Wykoff, F.W. (1996). Issues in the measurement of economic depreciation introductory remarks. Economic Inquiry 34, 10-23. https://doi.org/10.1111/j.1465-7295.1996.tb01361.x IEA – International Energy Agency (2020). Austria 2020. Energy Policy Review. https://iea.blob.core.windows.net/assets/ea419c67-4847-4a22-905a-d3ef66b848ba/Austria_2020_Energy_Policy_Review.pdf Jorgenson, D.W. (1973). The Economic Theory of Replacement and Depreciation. In: Sellekaerts, W. (eds) Econometrics and Economic Theory. Palgrave Macmillan, London, 189-221. https://doi.org/10.1007/978-1-349-01936-6_10 Kaisermayer, V., Binder, J., Muschick, D., Beck Gü, Rosegger, W., Horn, M., Gölles M., Kelz J., Leusbrock, I. (2022). Smart control of interconnected district heating networks on the example of “100% Renewable District Heating Leibnitz”, Smart Energy (2022), doi: https://doi.org/10.1016/j.segy.2022.100069 Kelz J., Leusbrock I., Binder, J., Schrammel, H. (2020). Flexibility as a main influencing parameter for a sustainable and renewable driven district heating sector. SCIENCE.RESEARCH.PANNONIA. Department Energie-Umweltmanagement (Hg.), ISBN 978-3-7011-0460-4 Lee, A.H.I, Kang, H.-Y., Lin, C.-Y., Shen, K.-C. (2015). An integrated decision-making model for the location of a PV solar plant. Sustainability 7, 13522–13541. https://doi.org/10.3390/su71013522 Liu, Y, Ren, L., Li, Y., Zhao, X-G. (2015). The industrial performance of wind power industry in China. Renewable and Sustainable Energy Review 43, 644–655. https://doi.org/10.1016/j.rser.2014.11.003 Longo, L., Colantoni, A., Castellucci, S., Carlini, M., Vecchione, L., Savuto, E., Pallozzi,V., Di Carlo, A., Bocci, E., Moneti, M., Cocchi, S., Boubaker, K. (2015). DEA (data envelopment analysis)-assisted supporting measures for ground coupled heat pumps implementing in Italy: a case study. Energy 90, 1967–1972. http://dx.doi.org/10.1016/j.energy.2015.07.024 Luptacik, M. (2010). Data Envelopment Analysis. In: Mathematical Optimization and Economic Analysis. Springer Optimization and Its Applications, vol 36. Springer, New York, NY. https://doi.org/10.1007/978-0-387-89552-9_5 Lygnerud, K., Peltola-Ojala, P. (2010). Factors impacting district heating companies’ decision to provide small house customers with heat, Applied Energy 87, 185-190. https://doi.org/10.1016/j.apenergy.2009.05.007 Mendelová, V. (2021), Decomposition of cost efficiency with adjustable prices: an application of data envelopment analysis, Operational Research 21, 2739–2770. https://doi.org/10.1007/s12351-019-00525-w Metz, S., Schrammel, H. (2019). Benchmarking and Evaluation of Austrian Biomass District Heating Plants and Networks, Proceedings of the 27th European Biomass Conference and Exhibition, 1545 – 1548. https://doi.org/10.5071/27thEUBCE2019-4CO.4.2 Munksgaard, J., Pade, L., Fristrup, P. (2005). Efficiency gains in Danish district heating. Is there anything to learn from benchmarking?. Energy Policy 33. 1986-1997. https://doi.org/10.1016/j.enpol.2004.03.019 Nussbaumer, T., Thalmann, S. (2014). Sensitivity of System Design on Heat Distribution Cost in District Heating IEA Bioenergy Task 32, Swiss Federal Office of Energy, and Verenum, Zürich 2014 ISBN 3-908705-27-4 (https://nachhaltigwirtschaften.at/resources/iea_pdf/reports/iea_bioenergy_task32_cost_analysis_district_heating.pdf) Österreichischer Biomasse-Verband (2023). Bioenergie Atlas Österreich. Wien. https://www.biomasseverband.at/wp-content/uploads/Bioenergie-Atlas-Oesterreich-2023.pdf Park, S., Lee, K., Yoo, S. (2016). Economies of scale in the Korean district heating system: A variable cost function approach, Energy Policy, 197-203. https://doi.org/10.1016/j.enpol.2015.10.026 Portela, M.C.S., Thanassoulis, E. (2014). Economic efficiency when prices are not fixed: disentangling quantity and price efficiency, Omega 47, 36–44. https://doi.org/10.1016/j.omega.2014.03.005 Ra̧czka, J. (2001). Explaining the performance of heat plants in Poland. Energy Economics 23, 355-370. https://doi.org/10.1016/S0140-9883(00)00076-1 Ransikarbum, K., Pitakaso, R. (2021). Relative Efficiency Analysis of Biomass Agricultural Plants using Data Envelopment Analysis. E3S Web of Conferences 302, 0100. https://doi.org/10.1051/e3sconf/202130201003 Ray, S.C. (1991). Resource-Use Efficiency in Public Schools: A Study of Connecticut Data. Management Science 37, 1620-1628. https://www.jstor.org/stable/2632732 Ray, S.C. (2004). Data Envelopment Analysis. Theory and Techniques for Economics and Operations Research. Cambridge University Press, Cambridge. Ray, S.C. (2020). Data Envelopment Analysis: A Nonparametric Method of Production Analysis. In: Ray, S.C., Chambers, R., Kumbhakar, S. (eds) Handbook of Production Economics. Springer, Singapore, pp. 1–62. https://doi.org/10.1007/978-981-10-3450-3_24-1 Ruggiero, J. (2019). The Choice of Comparable DMUs and Environmental Variables. In: ten Raa, T., Greene, W. (eds) The Palgrave Handbook of Economic Performance Analysis. Palgrave Macmillan, Cham, pp. 123-144. https://doi.org/10.1007/978-3-030-23727-1_5 Schreyer, P., Pilat, D. (2001). Measuring Productivity. OECD Economic Studies No. 33, 2001/II. https://www.oecd.org/employment/labour/1959006.pdf Simar, L., Wilson, P.W. (2002). Nonparametric tests of returns to scale. European Journal of Operational Research 139, 115–132. https://doi.org/10.1016/S0377-2217(01)00167-9 Sjödin, J., Henning, D. (2004). Calculating the marginal costs of a district-heating utility, Applied Energy 78, 1-18. https://doi.org/10.1016/S0306-2619(03)00120-X Strimitzer, L. (2021). Biomasseheizungen in Österreich – Energieholz Marktentwicklung 2021; Österreichische Energieagentur, Wien, 2021. https://www.klimaaktiv.at/dam/jcr:155fe8e0-9281-44ba-9de0-506f9232a870/Marktinformation_Biomasseheizungen_16062021.pdf Sueyoshi, T., Yuan, Y., Goto, M. (2017). A literature study for DEA applied to energy and environment, Energy Economics 62, 104-124. http://dx.doi.org/10.1016/j.eneco.2016.11.006 Tone, K. (2002). A strange case of the cost and allocative efficiencies in DEA. The Journal of the Operational Research Society 53, 1225–1231. https://www.jstor.org/stable/822808 Tone, K., Tsutsui, M. (2007). Decomposition of cost efficiency and its application to Japan-US electric utility comparisons. Socio-Economic Planning Science 41, 91–106. https://doi.org/10.1016/j.seps.2005.10.007 Werner, S. (2017). International review of district heating and cooling, Energy, Volume 137, 617-631. https://doi.org/10.1016/j.energy.2017.04.045 Xu, T., Jianxin, Y., Hui, L., Luning, S. (2020). Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review. Energies 13, 3548. https://doi.org/10.3390/en13143548 Zhou, P., Ang, B., Poh, K. (2008). A survey of data envelopment analysis in energy and environmental study. European Journal of Operational Research. 189. 1-18. https://doi.org/10.1016/j.ejor.2007.04.042 Ziemele, J., Gravelsins, A., Blumberga, A., Blumberga, D. (2017). Sustainability of heat energy tariff in district heating system: Statistic and dynamic methodologies, Energy 137, 834-845. https://doi.org/10.1016/j.energy.2017.04.130 |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/118595 |