Coyote optimization algorithm for parameters extraction of three-diode photovoltaic models of photovoltaic modules. (15th November 2019)

• Record Type: Journal Article
• Authors: Qais, Mohammed H.; Hasanien, Hany M.; Alghuwainem, Saad; Nouh, Adnan S.
• Is Part Of: Energy. Volume 187(2019)
• Publication Date: 2019-11-15
• Subjects: Optimization methods -- Photovoltaic power systems -- Power system modeling; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2019.116001
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: This paper exhibits a novel application of the coyote optimization algorithm (COA) in order to extract the nine unknown parameters of the three-diode photovoltaic (PV) model of PV modules. The main target of this study is to obtain a very highly precise PV model, which can be efficiently applied to represent the PV system in the simulation of dynamic power systems. The optimization problem is formulated to take into consideration the root mean squared current error between the calculated model current and the experimental current of the PV module. The COA is applied to minimize this fitness function. In this study, the COA-PV model is validated by the numerical results which are performed at different environmental conditions such as temperature and irradiation variation conditions. Moreover, its effectiveness is executed by making a comparison between its numerical and experimental results for some commercial PV modules in the market like the KC200GT and MSX-60 modules. With the adoption of the COA, a highly precise three-diode PV model can be established. This represents a novel contribution to the field of PV systems and its modeling. Highlights: This paper presents a novel application of the COA to extract PV model parameters. Three-diode PV (TDPV) model is used in this paper. Parameters of COA-TDPV model are compared with other optimization based models. COA-TDPV model is verified by comparing its results with the experimental results. Two commercial PV modules are used in the paper (KC200GT and MSX-60).