Optimal power flow with integrated wind power using chaotic moth swarm algorithm

Optimal power flow is a nonlinear and non-convex optimization problem. The aim of the problem is to find the best control parameters while providing the equality and inequality constraints. In general, thermal generators are used in power systems for solving the optimal power flow problem. Besides, in recent years, renewable energy resources come into use in power system to reduce the environmental pollution and increase the productivity of the systems. One of the most popular renewable energy resources is wind power which can be used in optimization of power systems. Nowadays, the optimization process is performed by evolutionary algorithms. One of the newest evolutionary algorithm is the moth swarm algorithm which is an effective method for solving the optimization problems. In this thesis, Lévy flight method in moth swarm algorithm is improved by using different types of chaotic maps and presented as Chaotic Moth Swarm Algorithm. Chaotic moth swarm algorithm is applied on the wind integrated power system to solve optimal power flow problem. The proposed algorithm applied on IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems with various objective functions. The results are compared with particle swarm algorithm, genetic algorithm and moth swarm algorithm. Simulation outcomes show that the developed method gives better and efficient results than the compared algorithms.