Path-Finder Optimization Based Control of Grid-Tied PV Hybrid Energy Storage System

Abstract

This paper presents a path-finder algorithm (PFA) of meta-heuristic optimization for the performance enhancement of the bias compensated normalized maximum correntropy criteria (BCNMCC) based voltage source converter (VSC) control for a three-phase three-wire grid-tied dual-stage PV system. The DC link voltage variations during induced dynamic conditions are minimized by PFA optimized PI controller which also generates an accurate loss component of current for enhancing the VSC control performance. The BCNMCC algorithm effectively performs the system identification and echo cancellation in the presence of Gaussian noises. An accurate improves the VSC ability to accurately extract the fundamental load current component and to produce precise weight signals. The BCNMCC performs multifunctional operations, i.e., reactive power compensation, harmonics elimination, load balancing, and power balancing at point of common coupling during steady-state and various dynamic conditions, i.e., grid-islanding & re-synchronization, irradiation variation, unbalanced load and fixed power mode. The proposed system is capable of operating under grid-tied and isolated mode due to the seamless transition of a VSC control from grid current control (GCC) to voltage control. The seamless transition of VSC control does not induce any major transients at the source and on the load side of the system. The hybrid energy storage system (HESS) with a battery, fuel-cell and ultra-capacitor further improves the reliability of the PV system and the stability of the overall system during both grid-tied and isolated operations. The proposed system performs satisfactorily under steady-state and diverse dynamic states as per IEEE519 standards.