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

作者：Zhou, Zhe; Zhang, Jianyun; Liu, Pei^*; Li, Zheng; Georgiadis, Michael C.; Pistikopoulos, Efstratios N.

来源：Applied Energy, 2013, 103: 135-144.

DOI：10.1016/j.apenergy.2012.09.019

• Stochastic programming
• Distributed energy system
• Uncertainty
• Genetic algorithm
• The Monte Carlo method

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.

• 出版日期2013-3
• 单位清华大学