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Energy efficiency and risk management in public buildings: strategic model for robust planning

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  • Emilio Cano
  • Javier Moguerza
  • Tatiana Ermolieva
  • Yuri Ermoliev

Abstract

Due to deregulations of the energy sector and the setting of targets such as the 20/20/20 in the EU, operators of public buildings are now more exposed to instantaneous (short-term) market conditions. On the other hand, they have gained the opportunity to play a more active role in securing long-term supply, managing demand, and hedging against risk while improving existing buildings’ infrastructures. Therefore, there are incentives for the operators to develop and use a Decision Support System to manage their energy sub-systems in a more robust energy-efficient and cost-effective manner. In this paper, a two-stage stochastic model is proposed, where some decisions (so-called first-stage decisions) regarding investments in new energy technologies have to be taken before uncertainties are resolved, and some others (so-called second-stage decisions) on how to use the installed technologies will be taken once values for uncertain parameters become known, thereby providing a trade-off between long- and short-term decisions. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Emilio Cano & Javier Moguerza & Tatiana Ermolieva & Yuri Ermoliev, 2014. "Energy efficiency and risk management in public buildings: strategic model for robust planning," Computational Management Science, Springer, vol. 11(1), pages 25-44, January.
    • Handle: RePEc:spr:comgts:v:11:y:2014:i:1:p:25-44
    DOI: 10.1007/s10287-013-0177-3
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    References listed on IDEAS

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    Cited by:

    1. Bei, Xiaoqiang & Zhu, Xiaoyan & Coit, David W., 2019. "A risk-averse stochastic program for integrated system design and preventive maintenance planning," European Journal of Operational Research, Elsevier, vol. 276(2), pages 536-548.
    2. 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.
    3. Tatiana Ermolieva & Petr Havlik & Yuri Ermoliev & Nikolay Khabarov & Michael Obersteiner, 2021. "Robust Management of Systemic Risks and Food-Water-Energy-Environmental Security: Two-Stage Strategic-Adaptive GLOBIOM Model," Sustainability, MDPI, vol. 13(2), pages 1-16, January.

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