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Evaluation of Economically Optimal Retrofit Investment Options for Energy Savings in Buildings

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  • Kumbaroğlu, Gürkan

    (Department of Industrial Engineering, Boğaziçi University)

  • Madlener, Reinhard

    (E.ON Energy Research Center, Institute for Future Energy Consumer Needs and Behavior (FCN), RWTH Aachen University)

Abstract

In this study, a techno-economic evaluation methodology for energy retrofit of buildings is introduced, geared towards finding the economically optimal set of retrofit measures. Split incentives of building owners and users are considered explicitly in a conventional (static) evaluation to identify the investment alternatives maximizing the net present value (NPV). Energy price uncertainty for various distributional assumptions of the stochastic variables is addressed through Monte Carlo simulation. Results from the simulation are used to compute probabilities and expected NPVs. Based on this, a sequential (dynamic) evaluation methodology is developed, featuring a real options investment appraisal. The methodological advancements introduced are applied to an office building, illustrating the model’s performance. The case study results indicate that energy price changes significantly affect the profitability of retrofit investments, and that increased price volatility creates a substantial value of waiting, making it more rational to postpone the investment. Further insight is gained on various aspects of economic decision-making concerning energy retrofit of buildings.

Suggested Citation

  • Kumbaroğlu, Gürkan & Madlener, Reinhard, 2011. "Evaluation of Economically Optimal Retrofit Investment Options for Energy Savings in Buildings," FCN Working Papers 14/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    • Handle: RePEc:ris:fcnwpa:2011_014
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    References listed on IDEAS

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    1. Ghoshray, Atanu & Johnson, Ben, 2010. "Trends in world energy prices," Energy Economics, Elsevier, vol. 32(5), pages 1147-1156, September.
    2. Jakob, Martin, 2006. "Marginal costs and co-benefits of energy efficiency investments: The case of the Swiss residential sector," Energy Policy, Elsevier, vol. 34(2), pages 172-187, January.
    3. Jaffe, Adam B. & Stavins, Robert N., 1994. "The energy-efficiency gap What does it mean?," Energy Policy, Elsevier, vol. 22(10), pages 804-810, October.
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    Cited by:

    1. Heesen, Florian & Madlener, Reinhard, 2021. "Revisiting heat energy consumption modeling: Household production theory applied to field experimental data," Energy Policy, Elsevier, vol. 158(C).
    2. Dergiades, Theologos & Madlener, Reinhard & Christofidou, Georgia, 2018. "The nexus between natural gas spot and futures prices at NYMEX: Do weather shocks and non-linear causality in low frequencies matter?," The Journal of Economic Asymmetries, Elsevier, vol. 18(C), pages 1-1.
    3. Caralis, George & Diakoulaki, Danae & Yang, Peijin & Gao, Zhiqiu & Zervos, Arthouros & Rados, Kostas, 2014. "Profitability of wind energy investments in China using a Monte Carlo approach for the treatment of uncertainties," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 224-236.
    4. Rohlfs, Wilko & Madlener, Reinhard, 2013. "Challenges in the Evaluation of Ultra-Long-Lived Projects: Risk Premia for Projects with Eternal Returns or Costs," FCN Working Papers 13/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    5. Harmsen - van Hout, Marjolein & Ghosh, Gaurav & Madlener, Reinhard, 2013. "The Impact of Green Framing on Consumers’ Valuations of Energy-Saving Measures," FCN Working Papers 7/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    6. Joonrak Kim & Dongmin Son & Bongju Jeong, 2017. "Two-Stage Integer Programing Model for Building Retrofit Planning for Energy Saving in South Korea," Sustainability, MDPI, vol. 9(11), pages 1-18, November.
    7. Vahid Amir & Shahram Jadid & Mehdi Ehsan, 2017. "Probabilistic Optimal Power Dispatch in Multi-Carrier Networked Microgrids under Uncertainties," Energies, MDPI, vol. 10(11), pages 1-21, November.
    8. Rohlfs, Wilko & Madlener, Reinhard, 2011. "Multi-Commodity Real Options Analysis of Power Plant Investments: Discounting Endogenous Risk Structures," FCN Working Papers 22/2011, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    9. Harmsen - van Hout, Marjolein & Ghosh, Gaurav & Madlener, Reinhard, 2013. "An Evaluation of Attribute Anchoring Bias in a Choice Experimental Setting," FCN Working Papers 6/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
    10. Emilio L. Cano & Javier M. Moguerza & Tatiana Ermolieva & Yurii Yermoliev, 2017. "A strategic decision support system framework for energy-efficient technology investments," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 249-270, July.
    11. Arturas Kaklauskas & Gintautas Dzemyda & Laura Tupenaite & Ihar Voitau & Olga Kurasova & Jurga Naimaviciene & Yauheni Rassokha & Loreta Kanapeckiene, 2018. "Artificial Neural Network-Based Decision Support System for Development of an Energy-Efficient Built Environment," Energies, MDPI, vol. 11(8), pages 1-20, August.
    12. Bonde, Magnus & Song, Han-Suck, 2016. "“Green” refurbishments under uncertainty," Working Paper Series 15/11, Royal Institute of Technology, Department of Real Estate and Construction Management & Banking and Finance.
    13. Wang, Xiaotong & Lu, Meijun & Mao, Wei & Ouyang, Jinlong & Zhou, Bo & Yang, Yunkai, 2015. "Improving benefit-cost analysis to overcome financing difficulties in promoting energy-efficient renovation of existing residential buildings in China," Applied Energy, Elsevier, vol. 141(C), pages 119-130.
    14. Gliedt, Travis & Hoicka, Christina E., 2015. "Energy upgrades as financial or strategic investment? Energy Star property owners and managers improving building energy performance," Applied Energy, Elsevier, vol. 147(C), pages 430-443.

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    More about this item

    Keywords

    Building energy efficiency; Energy conservation; Net present value; Real options;
    All these keywords.

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