Title: Performance analysis and comparison of jelly-fish optimisation-based maximum power point tracking controller for partial shading condition

Authors: Dilip Yadav; Nidhi Singh

Addresses: School of Electrical Engineering, Gautam Buddha University, Greater Noida, Uttar Pradesh, 201312, India ' School of Electrical Engineering, Gautam Buddha University, Greater Noida, Uttar Pradesh, 201312, India

Abstract: This paper addresses the critical challenge of partial shading condition (PSC) in photovoltaic systems, which significantly affect the efficiency of PV panels. Conventional methods often fail to optimise output under partial shading condition, prompting the need for innovative approaches. The study proposes the jelly-fish optimisation algorithm for maximum power point tracking, comparing its effectiveness with various existing MPPT controllers including incremental conductance, modified incremental conductance, perturb and observation, particle swarm optimisation, cuckoo search algorithm, grey wolf optimisation, and whale search optimisation techniques. The study reveals the limitations of conventional techniques in optimising power output under PSC. The findings highlight the superiority of the jelly fish-based MPPT, achieving an impressive efficiency of 99.89% with a minimal tracking time of 0.14 seconds, surpassing other MPPT controllers. This work advances the field by highlighting the jelly-fish algorithm's effectiveness and guiding future research toward more efficient MPPT methods.

Keywords: cuckoo search; jelly-fish optimisation algorithm; maximum power point tracking; MPPT; partial shading condition; PSC; particle swarm optimisation; PSO.

DOI: 10.1504/IJCSE.2025.147611

International Journal of Computational Science and Engineering, 2025 Vol.28 No.4, pp.401 - 418

Received: 20 Nov 2023
Accepted: 09 Jun 2024
Published online: 24 Jul 2025 *

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