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A two-stage stochastic programming model for the optimal design of distributed energy systems

Author

Listed:
  • Zhou, Zhe
  • Zhang, Jianyun
  • Liu, Pei
  • Li, Zheng
  • Georgiadis, Michael C.
  • Pistikopoulos, Efstratios N.

Abstract

A distributed energy system is a multi-input and multi-output energy system with substantial energy, economic and environmental benefits. The optimal design of such a complex system under energy demand and supply uncertainty poses significant challenges in terms of both modelling and corresponding solution strategies. This paper proposes a two-stage stochastic programming model for the optimal design of distributed energy systems. A two-stage decomposition based solution strategy is used to solve the optimization problem with genetic algorithm performing the search on the first stage variables and a Monte Carlo method dealing with uncertainty in the second stage. The model is applied to the planning of a distributed energy system in a hotel. Detailed computational results are presented and compared with those generated by a deterministic model. The impacts of demand and supply uncertainty on the optimal design of distributed energy systems are systematically investigated using proposed modelling framework and solution approach.

Suggested Citation

  • Zhou, Zhe & Zhang, Jianyun & Liu, Pei & Li, Zheng & Georgiadis, Michael C. & Pistikopoulos, Efstratios N., 2013. "A two-stage stochastic programming model for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 103(C), pages 135-144.
    • Handle: RePEc:eee:appene:v:103:y:2013:i:c:p:135-144
    DOI: 10.1016/j.apenergy.2012.09.019
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