Frequency Stability of Multi-source Power System using Whale Optimization Algorithm

Abstract

The Whale Optimization Algorithm (WOA), an evolutionary computing approach, is presented in this study and is used to auto regulated frequency of many composed power systems including thermoelectric power station, hydroelectric, and gas power plants. The purpose of this process follows the concept of a hunting mechanism of fish through water bubbles. The WOA is first applied to a single region with a multi-source power system for optimal gain adjustment of proportional integral controllers (PID). This approach is then applied to two areas, each having six generating sources with AC and AC-DC links. The credible achievements of the WOA-based PID controller are compared with previously constructed optimization approaches like Teaching Learning Based Optimization (TLBO), Differential evolution (DE) and Optimal Controller (OC), which is demonstrated in terms of frequency error, settling time and damping ratio. The performance indices of the purposed controller are analyzed through different objective functions like integral square error (ISE), integral time absolute error (ITAE), integral absolute error (IAE) and integral time squared error (ITSE). By using step load agitation, the simulation results indicate that the suggested technique is computationally stable.