Optimal sizing of CHP for residential complexes by two-stage stochastic programming

Combined heat and power (CHP) is a well-known technique for producing heat and power simultaneously onsite. Since it has high energy efficiency, low installation time and high reliability, it is an appropriate approach in energy management of residential complexes. In this paper, two-stage stochastic programming is proposed to manage uncertainties in the optimal sizing and operation of CHP for residential complexes. Monte Carlo approach is used to model electrical and thermal load forecasting errors. Maximizing net present value considering the probability of each scenario obtained from the scenario reduction algorithm is the objective function. The proposed method has been applied on a hospital and the results for different scenarios are presented.