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Multi-stakeholder optimal energy supply for multi-family houses under 2021 German market conditions

    Lucas Schmeling Affiliation
    ; Florian Walter Affiliation
    ; Timo Erfurth Affiliation
    ; Peter Klement Affiliation
    ; Benedikt Hanke Affiliation
    ; Karsten von Maydell Affiliation
    ; Carsten Agert Affiliation
    ; Bernd Siebenhüner Affiliation

Abstract

Especially in the energy supply of multi-family houses, a wide variety of stakeholders are involved, from owners, to users, to energy service providers and society. They usually have different requirements and understandings of optimality, but ultimately have to make joint decisions and thus sensible compromises. In Germany in particular, there are a large number of multi-family houses and, at the same time, many government restrictions and subsidies in terms of energy supply. This makes it difficult to make clear recommendations for the choice of an energy supply concept that takes all stakeholder interests into account. We first identify the relevant stakeholders and define their objectives. In order to relate these with one another, we present a methodology based on energy system simulation and TOPSIS to make energy concepts objectively evaluable. A generic multi-family house with 40 residential units is examined, combining different energy technologies and insulation standards. There is no energy concept that satisfies all stakeholders equally and it is difficult to build coalitions between them. The best results are achieved by air-source heat pumps in combination with photovoltaic.

Keyword : energy system optimisation, energy system simulation, distributed generation, multiple-criteria decision analysis, TOPSIS, DIN V 18599

How to Cite
Schmeling, L., Walter, F., Erfurth, T., Klement, P., Hanke, B., von Maydell, K., Agert, C., & Siebenhüner, B. (2024). Multi-stakeholder optimal energy supply for multi-family houses under 2021 German market conditions. Journal of Civil Engineering and Management, 30(6), 481–493. https://doi.org/10.3846/jcem.2024.20924
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Jul 4, 2024
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This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abdullah, M. F., Siraj, S., & Hodgett, R. E. (2021). An overview of multi-criteria decision analysis (MCDA) application in managing water-related disaster events: Analyzing 20 years of literature for flood and drought events. Water, 13(10), Article 1358. https://doi.org/10.3390/w13101358

Baumann, M., Weil, M., Peters, J. F., Chibeles-Martins, N., & Moniz, A. B. (2019). A review of multi-criteria decision making approaches for evaluating energy storage systems for grid applications. Renewable and Sustainable Energy Reviews, 107, 516–534. https://doi.org/10.1016/j.rser.2019.02.016

Behaneck, M. (2018). Vergleichsübersicht: EnEV-Software. TGA Fachplaner, 1, 58–62.

Berendes, S., Bertheau, P., & Blechinger, P. (2018). Sizing and optimization of hybrid mini-grids with micrOgridS – an open-source modelling tool. In Hybrid Power Systems Conference, Tenerife, Spain.

Braeuer, F., Kleinebrahm, M., Naber, E., Scheller, F., & McKenna, R. (2022). Optimal system design for energy communities in multi-family buildings: the case of the German Tenant Electricity Law. Applied Energy, 305, Article 117884. https://doi.org/10.1016/j.apenergy.2021.117884

Brans, J. P., & Mareschal, B. (2005). Promethee methods. In Multiple criteria decision analysis: State of the art surveys. International Series in Operations Research & Management Science (Vol. 78, pp. 163–186). Springer-Verlag. https://doi.org/10.1007/0-387-23081-5_5

Bundesministerium für Wirtschaft und Energie. (2021). Richtlinie für die Bundesförderung für effiziente Gebäude – Wohngebäude (BEG WG). https://www.bundesanzeiger.de/pub/publication/F8BOqbY7wRjLIpG4KnP/content/F8BOqbY7wRjLIpG4KnP/BAnz%20AT%2018.10.2021%20B3.pdf?inline

Bundesministerium für Wohnen, Stadtentwicklung und Bauwesen. (2022). ÖKOBAUDAT. https://www.oekobaudat.de/no_cache.html

Crawley, D. B., Lawrie, L. K., Winkelmann, F. C., Buhl, W. F., Huang, Y., Pedersen, C. O., Strand, R. K., Liesen, R. J., Fisher, D. E., Witte, M. J., & Glazer, J. (2001). EnergyPlus: Creating a new-generation building energy simulation program. Energy and Buildings, 33(4), 319–331. https://doi.org/10.1016/S0378-7788(00)00114-6

DIN V 18599-1:2018-09. Energetische Bewertung von Gebäuden Teil 1. Berlin, Beuth Verlag GmbH.

European Union. (2002). Directive 2002/91/EC of the European Parliament and of the Council of 16 December 2002 on the energy performance of buildings. https://eur-lex.europa.eu/eli/dir/2002/91/oj

Figueira, J. R., Mousseau, V., & Roy, B. (2016). ELECTRE methods. In S. Greco, M. Ehrgott, & J. Figueira (Eds.), Multiple criteria decision analysis. International Series in Operations Research & Management Science (Vol. 233, pp. 155–185). Springer. https://doi.org/10.1007/978-1-4939-3094-4_5

Hancock, C., Klement, P., Schmeling, L., Hanke, B., & von Maydell, K. (2023). Optimization of the refurbishment of German single family homes based on construction era. Energy Strategy Reviews, 49, Article 101156. https://doi.org/10.1016/j.esr.2023.101156

Hettinga, S., Nijkamp, P., & Scholten, H. (2018). A multi-stakeholder decision support system for local neighbourhood energy planning. Energy Policy, 116, 277–288. https://doi.org/10.1016/j.enpol.2018.02.015

Hottgenroth Energieberater 18599 3D PLUS. https://www.hottgenroth.de/M/SOFTWARE/EnergieNachweise/Energieberater-18599-3D/Seite.html,73274,80422

Kelly, S., & Pollitt, M. G. (2011). The local dimension of energy. In T. Jamasb, & M. G. Pollitt (Eds.), The future of electricity demand: Customers, citizens, and loads (Department of applied economics occasional papers, Vol. 69, pp. 249–279). Cambridge University Press. https://doi.org/10.1017/CBO9780511996191.016

Kirppu, H., Lahdelma, R., & Salminen, P. (2018). Multicriteria evaluation of carbon-neutral heat-only production technologies for district heating. Applied Thermal Engineering, 130, 466–476. https://doi.org/10.1016/j.applthermaleng.2017.10.161

Klauß, S., & Maas, A. (2010). Entwicklung einer Datenbank mit Modellgebäuden für energiebezogene Untersuchungen, insbesondere der Wirtschaftlichkeit. https://www.bbsr.bund.de/BBSR/DE/forschung/programme/zb/Auftragsforschung/5EnergieKlimaBauen/2010/DatenbankModellgebaeude/DL_Endbericht.pdf;jsessionid=DAF871984D9E311F561C5758FC5F7742.live11311?__blob=publicationFile&v=1

Lindberg, K. B., Fischer, D., Doorman, G., Korpås, M., & Sartori, I. (2016). Cost-optimal energy system design in Zero Energy Buildings with resulting grid impact: A case study of a German multi-family house. Energy and Buildings, 127, 830–845. https://doi.org/10.1016/j.enbuild.2016.05.063

Løken, E. (2005). Use of multicriteria decision analysis methods for energy planning problems. Renewable and Sustainable Energy Reviews, 11(7), 1584–1595. https://doi.org/10.1016/j.rser.2005.11.005

Mailach, B., & Oschatz, B. (2021). BDEW-Heizkostenvergleich Neubau 2021: Ein Vergleich der Gesamtkosten verschiedener Systeme zur Heizung und Warmwasserbereitung in Neubauten.

Matsatsinis, N. F., & Samaras, A. P. (2001). MCDA and preference disaggregation in group decision support systems. European Journal of Operational Research, 130(2), 414–429. https://doi.org/10.1016/S0377-2217(00)00038-2

Mela, K., Tiainen, T., & Heinisuo, M. (2012). Comparative study of multiple criteria decision making methods for building design. Advanced Engineering Informatics, 26(4), 716–726. https://doi.org/10.1016/j.aei.2012.03.001

Opricovic, S., & Tzeng, G.-H. (2004). The compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156(2), 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1

Pavić, Z., & Novoselac, V. (2013). Notes on TOPSIS method. International Journal of Research in Engineering and Science, 1(2), 5–12.

Roloff, J. (2008). Learning from multi-stakeholder networks: Issue-focussed stakeholder management. Journal of Business Ethics, 82(1), 233–250. https://doi.org/10.1007/s10551-007-9573-3

Saaty, T. L. (2004). Decision making – The Analytic Hierarchy and Network Processes (AHP/ANP). Journal of Systems Science and Systems Engineering, 13(1), 1–35. https://doi.org/10.1007/s11518-006-0151-5

Schmeling, L., Schönfeldt, P., Klement, P., Vorspel, L., Hanke, B., von Maydell, K., & Agert, C. (2022). A generalised optimal design methodology for distributed energy systems. Renewable Energy, 200, 1223–1239. https://doi.org/10.1016/j.renene.2022.10.029

Schöndube, T., Carrigan, S., Kornadt, O., Schoch, T., Hartner, M., Schilly, T., Weber, D., & Wilhelm, J. (2018). Niedrigstenergiegebäude – Entwicklung eines Standards und einer Berechnungsmethode für die Gebäudeenergieeffizienz. Abschlussbericht. Forschungsinitiative Zukunft Bau. Fraunhofer IRB Verlag.

Shekhovstov, A., & Sałabun, W. (2020). A comparative case study of the VIKOR and TOPSIS rankings similarity. Procedia Computer Science, 176, 3730–3740. https://doi.org/10.1016/j.procs.2020.09.014

Si, S.-L., You, X.-Y., Liu, H.-C., Zhang, P. (2018). DEMATEL technique: A systematic review of the state-of-the-art literature on methodologies and applications. Mathematical Problems in Engineering, 2018, Article 3696457. https://doi.org/10.1155/2018/3696457

Stamford, L., & Azapagic, A. (2018). Environmental impacts of photovoltaics: The effects of technological improvements and transfer of manufacturing from Europe to China. Energy Technology, 6(6), 1148–1160. https://doi.org/10.1002/ente.201800037

Statistisches Bundesamt. (2019a). Haushalte nach Haus- und Grundbesitz am 1.1. in den Gebietsständen. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Einkommen-Konsum-Lebensbedingungen/Vermoegen-Schulden/Tabellen/haus-grundbbesitz-evs.html

Statistisches Bundesamt. (2019b). Wohnverhältnisse privater Haushalte – Fachserie 15 Sonderheft 1 – 2018. https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Wohnen/Publikationen/Downloads-Wohnen/evs-wohnverhaeltnis-haushalte-2152591189004.pdf

Statistisches Bundesamt. (2021). Baugenehmigungen und Baufertigstellungen von Wohn- und Nichtwohngebäuden (Neubau) nach Art der Beheizung und Art der verwendeten Heizenergie – Lange Reihen ab 1980 – 2020. https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Bauen/Publikationen/Downloads-Bautaetigkeit/baugenehmigungen-heizenergie-pdf-5311001.html

Umweltbundesamt. (2022). ProBas – Prozessorientierte Basisdaten für Umweltmanagementsysteme. https://www.probas.umweltbundesamt.de/php/index.php

Venzmer, R. (Ed.). (2011). Praxis Energieberatung. Energieberatung – Software für den Energieberater (1. Aufl.). Beuth.

Wegener, M., Malmquist, A., Isalgue, A., Martin, A., Arranz, P., Camara, O., & Velo, E. (2020). A techno-economic optimization model of a biomass-based CCHP/heat pump system under evolving climate conditions. Energy Conversion and Management, 223, Article 113256. https://doi.org/10.1016/j.enconman.2020.113256