Parameter Estimation of Photovoltaic Cell/Modules Using Bonobo Optimizer

Abdullrahman A. Al-Shamma’a, Hammed O. Omotoso, Fahd A. Alturki, Hassan. M. H. Farh, Abdulaziz Alkuhayli, Khalil Alsharabi and Abdullah M. Noman
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Abdullrahman A. Al-Shamma’a: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Hammed O. Omotoso: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Fahd A. Alturki: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Hassan. M. H. Farh: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Abdulaziz Alkuhayli: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Khalil Alsharabi: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia
Abdullah M. Noman: Electrical Engineering Department, College of Engineering, King Saud University, Riyadh 11421, Saudi Arabia

Energies, 2021, vol. 15, issue 1, 1-22

Abstract: In this paper, a new application of Bonobo (BO) metaheuristic optimizer is presented for PV parameter extraction. Its processes depict a reproductive approach and the social conduct of Bonobos. The BO algorithm is employed to extract the parameters of both the single diode and double diode model. The good performance of the BO is experimentally investigated on three commercial PV modules (STM6-40 and STP6-120/36) and an R.T.C. France silicon solar cell under various operating circumstances. The algorithm is easy to implement with less computational time. BO is extensively compared to other state of the art algorithms, manta ray foraging optimization (MRFO), artificial bee colony (ABO), particle swarm optimization (PSO), flower pollination algorithm (FPA), and supply-demand-based optimization (SDO) algorithms. Throughout the 50 runs, the BO algorithm has the best performance in terms of minimal simulation time for the R.T.C. France silicon, STM6-40/36 and STP6-120/36 modules. The fitness results obtained through root mean square (RMSE), standard deviation (SD), and consistency of solution demonstrate the robustness of BO.

Keywords: photovoltaic; parameter extraction; Bonobo optimizer; renewable energy; optimization algorithms (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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