A two-stage stochastic programming model for the optimal design of distributed energy systems Academic Article uri icon

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. © 2012 Elsevier Ltd.

author list (cited authors)

  • Zhou, Z., Zhang, J., Liu, P., Li, Z., Georgiadis, M. C., & Pistikopoulos, E. N.

citation count

  • 167

publication date

  • March 2013