Optimization of PID Controller for Hybrid Renewable Energy System Using Adaptive Sine Cosine Algorithm

Abstract

This paper proposed a new application of an efficient Adaptive Sine Cosine Algorithm (ASCA) to determine the optimal settings of the PID controllers in hybrid renewable energy system (HRES). The ASCA is proposed to enhance the searching capabilities of the traditional Sine Cosine Optimization (SCA) and its stagnation to local optima. The ASCA is based on modifying traditional SCA by applying the Levy flight distribution and adaptive operators. The HRES consists of three sources photovoltaic (PV) source, wind turbine and battery storage. These sources are connected to a DC/DC boost converter for converting the DC voltage to an AC voltage through three-phase inverter. The considered objective function is formulated in terms of the current and voltage errors to enable the HRES to participate effectively within the connected micro-grid via optimal gains of the PID controllers. The results verify that the performance of the HRES is enhanced considerably by optimizing the parameters of the HRES controllers using the ASCA under several operating conditions of solar irradiation, temperature and wind speed.