An Improved Artificial Jellyfish Search Optimizer for Parameter Identification of Photovoltaic Models

Abstract

The optimization of photovoltaic (PV) systems relies on the development of an accurate model of the parameter values for the solar/PV generating units. This work proposes a modified artificial jellyfish search optimizer (MJSO) with a novel premature convergence strategy (PCS) to define effectively the unknown parameters of PV systems. The PCS works on preserving the diversity among the members of the population while accelerating the convergence toward the best solution based on two motions: (i) moving the current solution between two particles selected randomly from the population, and (ii) searching for better solutions between the best-so-far one and a random one from the population. To confirm its efficacy, the proposed method is validated on three different PV technologies and is being compared with some of the latest competitive computational frameworks. The numerical simulations and results confirm the dominance of the proposed algorithm in terms of the accuracy of the final results and convergence rate. In addition, to assess the performance of the proposed approach under different operation conditions for the solar cells, two additional PV modules (multi-crystalline and thin-film) are investigated, and the demonstrated scenarios highlight the utility of the proposed MJSO-based methodology.

WITHDRAWN: A Novel Approach for Mitigating Power Quality Issues in a PV Integrated Microgrid System Using an Improved Jelly Fish Algorithm

“…Traditional approaches such as Incremental Conductance (IC) [2], Hill Climbing (HC), Perturb and Obserb (P&O) [3], etc., is incapable of tracking MPP under Partial Shading Conditions (PSC). Many metaheuristic strategies, including Particle Swarm Optimization (PSO) [4], Jaya algorithm [5], Whale Optimization Algorithm (WOA) [6], Grey Wolf Optimization (GWO) [7], and Jelly Search Algorithm (JSA) [8][9][10][11], have been utilised to overcome the challenges produced by PSC. To address this problem, a hybrid Improved Jelly Fish Algorithm integrated Perturb and Obserb (IJFA-PO) method was proposed, which combines the benefits of both traditional and innovative methods.…”

Jellyfish Search Optimization Algorithm for MPP Tracking of PV System

“…A time control mechanism is employed to determine the type of motion performed by jellyfish [32]. The time component regulates both movements, i.e., the movement of jellyfish within the swarm (i.e., type A and type B motion) and towards the ocean flow [33]. The schematic diagram of the time control mechanism is shown in Figure 11.…”

Three Steps to Improve Jellyfish Search Optimiser

“…In 2021, Abdel-Basset et al employed an enhanced variant of JS to identify parameters of Photovoltaic models [1]. The authors applied a new Premature convergence strategy to increase JS exploitation capability.…”