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Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings

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  • Diakaki, Christina
  • Grigoroudis, Evangelos
  • Kolokotsa, Dionyssia

Abstract

The improvement of energy efficiency in buildings is among the first priorities worldwide. To this end, several measures are available, and the decision maker faces a decision problem with multiple objectives having to compensate several energy, financial, and other factors in order to make a satisfactory selection. To solve this problem, a decision modelling approach is proposed herein, based upon the principles of multi-objective mathematical programming, thus capturing only these elements, which affect the decisions to be taken. To evaluate its performance under realistic operational conditions in a building, the proposed approach is applied to an existing building for retrofit purposes, and several simulation investigations are performed in order to study and evaluate the quality of the retrofit alternatives proposed by the decision model. The results of these simulation investigations confirm, that despite its reduced precision compared to the corresponding simulation model of the building, the decision model allows for the realistic comparative evaluation of the considered alternatives. The example case study reported herein, demonstrates also the functionality of the proposed approach, exploits its qualities, and highlights its strengths, weaknesses and limitations.

Suggested Citation

  • Diakaki, Christina & Grigoroudis, Evangelos & Kolokotsa, Dionyssia, 2013. "Performance study of a multi-objective mathematical programming modelling approach for energy decision-making in buildings," Energy, Elsevier, vol. 59(C), pages 534-542.
    • Handle: RePEc:eee:energy:v:59:y:2013:i:c:p:534-542
    DOI: 10.1016/j.energy.2013.07.034
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    9. Deng, Qianli & Jiang, Xianglin & Cui, Qingbin & Zhang, Limao, 2015. "Strategic design of cost savings guarantee in energy performance contracting under uncertainty," Applied Energy, Elsevier, vol. 139(C), pages 68-80.
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