Optimal Configuration of the CHP System Using Stochastic Programming

This study presents a reliability-constrained optimization approach to determine the number and size of combined heat and power (CHP) system components, including CHP units, auxiliary boilers, and heat-storage tanks. To this end, the loss-of-load expectation and the expected energy not supplied are considered since the reliability indices ensure the security of operation. The load forecasting inaccuracy and the random outages of CHP system components as well as the loss of mains are modeled as a scenario tree using the Monte Carlo sampling approach. The problem is formulated as two-stage stochastic mixed integer linear programming. A scenario reduction technique is also introduced to reduce the computational burden of the scenario-based planning problem. Finally, the proposed model is applied to a large residential complex in Tehran as a case study.