Particle swarm optimization with smart inertia factor for combined heat and power economic dispatch

Abstract

In this research, particle swarm optimization with smart inertia factor (PSO-SIF) algorithm is suggested to solve combined heat and power economic dispatch (CHPED) problem. The CHPED problem is one of the most important problems in power systems and a challenging non-convex and non-linear optimization problem. The aim of solving the CHPED problem is to determine optimal heat and power of generating units with the minimized cost of total system and satisfied constraints of the problem. In the proposed algorithm, inertia coefficients are controlled regarding cost function in each population. Thus, each population has unique inertia coefficient and as a result unique velocity in convergent direction for the best group solution. In order to examine the proposed algorithm's capabilities and find optimum solution for CHPED problem, two test systems regarding valve-point effect, system power loss and system constraints are optimized. The obtained results demonstrate the superiority of the proposed method in solving non-convex CHPED problem over compared to the other new and efficient algorithms.