Abstract
Recently, building an accurate mathematical model with the help of the experimentally measured data of solar cells and Photovoltaic (PV) modules, as a tool for simulation and performance evaluation of the PV systems, has attracted the attention of many researchers. In this work, Coyote Optimization Algorithm (COA) has been applied for extracting the unknown parameters involved in various models for the solar cell and PV modules, namely single diode model, double diode model, and three diode model. The choice of COA algorithm for such an application is made because of its good tracking characteristics and the balance creation between the exploration and exploitation phases. Additionally, it has only two control parameters and such a feature makes it very simple in application. The Root Mean Square Error (RMSE) value between the data based on the optimized parameters for each model and those based on the measured data of the solar cell and PV modules is adopted as the objective function. Parameters' estimation for various types of PV modules (mono-crystalline, thin-film, and multi-crystalline) under different operating scenarios such as a change in intensity of solar radiation and cell temperature is studied. Furthermore, a comprehensive statistical study has been performed to validate the accurateness and stability of the applied COA as a competitor to other optimization algorithms in the optimal design of PV module parameters. Simulation results, as well as the statistical measurement, validate the superiority and the reliability of the COA algorithm not only for parameter extraction of different PV modules but also under different operating scenarios. With the COA, precise PV models have been established with acceptable RMSE of 7.7547×10 -4 , 7.64801×10 -4 , and 7.59756×10 -4 for SDM, DDM, and TDM respectively considering R.T.C. France solar cell.
Highlights
Due to the availability of solar energy (SE) at a very high rate, the exploration and investigation of the solar energy systems are extensively performed to achieve the best exploitation of this kind of renewable energy sources [1]
It can be realized that the studies in the literature with regards to parameters’ estimation accuracy for the solar cells (SC) and PV modules have been limited to the SD and DD models and they were rarely treated with the TD model, and for this purpose, the current paper introduces a comprehensive study about the estimation of the design parameters of SD, DD and TD models for the SC and PV modules using different optimization algorithms
To evaluate the power of the applied optimization method, data from the datasheet of the manufacturer and measured data obtained from the literature for different solar cells and PV modules at various intensities solar radiations and temperature have been used
Summary
Due to the availability of solar energy (SE) at a very high rate, the exploration and investigation of the solar energy systems are extensively performed to achieve the best exploitation of this kind of renewable energy sources [1]. Despite the ability of these modules (SD and DD) to provide better analysis of the SC or PV systems, their utilization had been restricted to the domestic use, which means that their dynamic performance had been tested for a limited number of operating conditions To overcome this shortage, the Three-Diode (TD) model has been presented [12]. Such algorithms possess various advantages such as they do not need anticipated information about the search space, and they have the ability to carry out a multidimensional exploration in the search spaces using different arrangements until the best solution has appeared [23].
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