Multi-Objective Grasshopper Optimization Based MPPT and VSC Control of Grid-Tied PV-Battery System

This article presents the control of a three-phase three-wire (3P-3W) dual-stage grid-tied PV-battery storage system using multi-objective grass-hopper optimization (MOGHO) algorithm. The voltage source converter (VSC) presented is implemented with adaptive kernel width sixth-order maximum correntropy criteria (AKWSOMCC) and power point tracking (MPPT) accomplished variable step-size incremental conductance (VSS-InC) technique. proposed VSC offers lower mean square error better accuracy, convergence rate speed as compared to peer algorithms, i.e., least (LMS), fourth (LMF), (MCC), etc. Gaussian function signal, which changes accommodate filter non-Gaussian noise signals in each iteration. VSS-InC based MPPT provided MOGHO modulation factor for faster during changing solar irradiation. Similarly, an optimized gain conventional PI controller regulates DC bus improve quality, link stability dynamic conditions. DC-link generates accurate loss component current, further improves capability fundamental load current extraction. designed perform multi-functional operations, harmonics elimination, reactive compensation, balancing at common coupling diverse MOSHO VSS-InC, performance particle swarm (PSO) genetic algorithm (GA). operates satisfactorily per IEEE519 standards MATLAB simulation environment.