A novel way of parameter estimation of solar photovoltaic system. Issue 1 (31st December 2021)

• Record Type: Journal Article
• Authors: Bisht, Rahul; Sikander, Afzal
• Is Part Of: Compel. Volume 41:Issue 1(2022)
• Page Start: 471
• Page End: 498
• Publication Date: 2021-12-31
• Subjects: Control systems -- Optimal control -- Power systems simulation -- Photovoltaic (PV) cell -- Newton Raphson (NR) -- Simulated annealing (SA) -- Particle swarm algorithm (PSO) -- Jellyfish search optimizer (JSO) -- Root mean square error (RMSE) -- Mean absolute error (MAE) -- Normalized mean absolute error (NMAE); Electrical engineering -- Data Processing -- Periodicals; Electrical engineering -- Mathematics -- Periodicals; Electrical engineering -- Periodicals; Electronics -- Data Processing -- Periodicals; Electronics -- Mathematics -- Periodicals; 621.3
• DOI: 10.1108/COMPEL-05-2021-0166
• Languages: English
• ISSNs: 0332-1649

Abstract

Abstract : Purpose: This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV. Design/methodology/approach: To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically. Findings: In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature. Originality/value: The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.