Title: Performance analysis of grid-connected photovoltaic systems using grey wolf optimisation and genetic algorithm

Authors: Pankaj Negi; Yash Pal; Leena Gopinathan

Addresses: School of Renewable Energy and Efficiency, National Institute of Technology, Kurukshetra, India ' Electrical Engineering Department, National Institute of Technology, Kurukshetra, India ' Electrical Engineering Department, Manav Rachna International Institute of Research and Studies, Faridabad, India

Abstract: This paper deals with a grid connected PV system having LCL filter. The key emphasis is given to the two optimisation methods - grey wolf optimisation (GWO) and genetic algorithm (GA) which are used to optimise proportional-integral (PI) controller parameters. The GWO and GA are used to determine the optimal values of the PI controller parameters, Kp and Ki in real time operation. The main objective is to reduce the transient response, minimise time overshoot, and to obtain low steady state error. The LCL filter has excellent harmonic suppression capability compared to L and LC filters and used to suppress the harmonics introduced by PWM techniques. The simulation results have been analysed under grid-side load variation and during LLG, LLLG, and LG faults conditions. The comparative simulation results indicate that transient stability of grid-connected PV system using GWO and GA shows better response than conventional PI controller.

Keywords: PI controller tuning; genetic algorithm; GA; grey wolf optimisation; GWO; LCL filters; active damping; PV system; faults; grid connected.

DOI: 10.1504/IJPEC.2024.138007

International Journal of Power and Energy Conversion, 2024 Vol.15 No.2, pp.122 - 146

Received: 05 Dec 2023
Accepted: 29 Dec 2023
Published online: 16 Apr 2024 *

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