Estimation of Photovoltaic Cell Parameters using the Honey Badger Algorithm
Dieudonné Marcel Djanssou1, Abdouramani Dadjé2, Noël Djongyang3

1Dieudonné Marcel Djanssou*, Department of Renewable Energy, National Advanced School of Engineering of Maroua, University of Maroua, Cameroon. 
2Abdouramani Dadjé, School of Geology and Mining Engineering, University of Ngaoundéré, Cameroon.
3Noël Djongyang, Department of Renewable Energy, National Advanced School of Engineering of Maroua, University of Maroua, Cameroon.
Manuscript received on 30 April 2022. | Revised Manuscript received on 21 May 2022. | Manuscript published on 30 June 2022. | PP: 105-108 | Volume-11 Issue-5, June 2022. | Retrieval Number: 100.1/ijeat.E35520611522 | DOI: 10.35940/ijeat.E3552.0611522
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Abstract: Optimal estimation of the intrinsic parameters of photovoltaic cells requires the use of meta-heuristics to increase their efficiency. This paper highlights the estimation of unknown parameters of a PV cell and module. For this purpose, the meta-heuristic optimization algorithm based on the Honey Badger Algorithm (HBA) principle is used. The simulation results via MATLAB prove that this algorithm has a good convergence. Indeed, the root mean square error (RMSE) is 9.8602×10-4, 9.8602×10-4, 2.4251×10-3, 1.7298×10-3 and 1.6783×10-2 for the single diode, dual diode, Photowatt-PWP201, Schutten Solar STM6-40/36 and the STP6-120/36 module respectively. Furthermore, the curves representing the current-voltage and power-voltage characteristics of the calculated unknown parameters versus those of the practical data measured from a PV cell/module datasheet coincide. The proposed algorithm can therefore be classified in the literature as one of the optimal parameter extraction techniques. 
Keywords: Honey Badger Algorithm; Metaheuristic Algorithms; Photovoltaic Cells; Parameter Estimation
Scope of the Article: Algorithm Engineering