Daily Hydrothermal Scheduling Using Particle Swarm Optimization with Smart Inertia Factor

Daily hydrothermal scheduling problem is one of the critical issues in power systems, playing a key role in economic performance of the system. Hydrothermal Scheduling problem with system's constraints is a challenging and non-linear optimization problem and evolutionary algorithms are used to solve this problem. This paper proposes particle swarm optimization method with smart inertia factor for solving hydrothermal scheduling problem.
The proposed algorithm is a smart and powerful version of particle swarm optimization algorithm in which each particle has unique inertia coefficient and unique velocity for extracting global point. In the proposed algorithm inertia coefficients are controlled with respect to cost function in each population. In order to examine the proposed algorithm's capabilities and find optimum solution for hydrothermal scheduling problem, proposed algorithm is implemented on two test systems. The obtained results have shown high capability of proposed algorithm in extracting optimal points of hydrothermal scheduling problem.