Golden Jackal Optimization for Parameters Estimation of Photovoltaic Models


  • Widi Aribowo Faculty of Vocational, Department of Electrical Engineering, Universitas Negeri Surabaya, Kode Pos 60231, Indonesia


Golden jackal optimization, Metaheuristic, Optimization algorithm, Parameter estimation, Solar cell


This article presents the determination of PV parameters using the Golden jackal optimization (GJO) method. Photovoltaic (PV) generation systems play a major role in the sustainable use of solar energy. Precise and reliable simulation and optimization techniques for PV systems are urgently needed. A reliable algorithm is needed to determine good PV parameters. GJO is an optimization method based on the behavior of Canis aureus in foraging. This method has three important steps, namely seeking, approaching and attacking prey. The research was conducted using Matlab software. To get the performance of the GJO method, this article presents the whale optimization algorithm (WOA), hunger game search (HGS) and aquilla optimizer (AO) methods for comparison. The benchmark is the root mean square error (RMSE) function. From the simulation results, the GJO method has a better RMSE than the AO method of 77.28%.


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How to Cite

Aribowo, W. (2023). Golden Jackal Optimization for Parameters Estimation of Photovoltaic Models. Science & Technology Asia, 28(3), 198–209. Retrieved from