Golden Eagle Optimized Control for a Dual Stage Photovoltaic Residential System with Electric Vehicle Charging Capability

Abstract

ABSTRACT In this article, the control of a grid-connected, single-phase, dual-stage photovoltaic (PV) residential system with electric vehicle (EV)-charging capability is being presented. A residential system faces a lot of dynamic conditions such as changing atmospheric condition or random patterns of load connection or disconnection as well as power failure. In this regard, this article proposes the optimization of proportional and integral gains selection of the bidirectional DC/DC converter (BDC) PI controller through golden eagle optimization (GEO) algorithm to improve the system performance. The system is subjected to various induced dynamic conditions simulated in MATLAB Simulink environment and the performance is compared with particle swarm optimization, genetic algorithm, and gains obtained through hit and trial. In comparison with other techniques, GEO algorithm provides optimum BDC PI gains, as a result, the DC-link voltage achieves 1.5 times shorter settling time. During the non-linear load changes and voltage swell condition, the settling time is 2 times shorter. Settling time of the EV battery power shows 1.7 times reduction. The transient response of the PV power also shows dramatic improvement with 3 times faster settling time during solar insolation changes. During the sudden non-linear load changes, the momentary transients die 1.5 times faster. Moreover, a seamless control is developed to achieve a seamless transition from islanded mode to grid connected mode and vice versa. The proposed system achieves unity power factor and complies with the IEEE -519 power quality standard.