An efficient stochastic programming for optimal allocation of combined heat and power systems for commercial buildings using

Advantages of combined heat and power system such as high efficiency, low environmental pollution, reliability and controllable output result in its widely application in commercial and residential buildings. Finding the optimal number and capacity of combined heat and power (CHP) units in commercial buildings is a challengeable issue. In this paper, an optimization method based on constrained index of reliability is used for optimal allocation of these systems. Hence, the value of lost load is considered as the reliability index. The random prediction errors of load and energy in CHP systems are modelled as a scenario based on Monte Carlo sampling procedure. Optimization is formulated by using a two-stage stochastic integer linear programming. To reduce the computation time, the number of scenarios has been reduced. Finally, the proposed model is used in a commercial building as a case study.