Temperature dependent optimal power flow using chaotic whale optimization algorithm

Abstract

This work presents a novel, nature inspired evolutionary based approach, the chaotic whale optimization algorithm, to solve a temperature dependent optimal power flow problem of a power system. Whale optimization is inspired by the bubble-net hunting strategy of the humpback whales; logistic chaotic maps are used to improve its performance. Whale optimization and our proposal are evaluated on three test systems namely, the IEEE 30-bus test power system, the 2383-bus Winter Peak Polish system and the 2736-bus Summer Peak Polish system to give a solution to the temperature dependant optimal power flow of the power systems where control of generator bus voltages, transformer tap ratios and reactive power sources are involved. Minimization of total fuel cost is considered here as the objective function for this problem. The superiority and the effectiveness of the proposed algorithm technique have been exhibited in comparison to the other evolutionary optimization techniques identified in the recent literature.