Parameter Identification of Solar Photovoltaic Systems Using an Augmented Subtraction-Average-Based Optimizer

Abstract

Solar photovoltaic system parameter identification is crucial for effective performance management, design, and modeling of solar panel systems. This work presents the Subtraction-Average-Based Algorithm (SABA), a unique, enhanced evolutionary approach for solving optimization problems. The conventional SABA works by subtracting the mean of searching solutions from the position of those in the population in the area of search. In order to increase the search capabilities, this work proposes an Augmented SABA (ASABA) that incorporates a method of collaborative learning based on the best solution. In accordance with manufacturing, the suggested ASABA is used to effectively estimate Photovoltaic (PV) characteristics for two distinct solar PV modules, RTC France and Kyocera KC200GT PV modules. Through the adoption of the ASABA approach, the simulation findings improve the electrical characteristics of PV systems. The suggested ASABA outperforms the regular SABA in terms of efficiency and effectiveness. For the R.T.C France PV system, the suggested ASABA approach outperforms the traditional SABA technique by 90.1% and 87.8 for the single- and double-diode models, respectively. Also, for the Kyocera KC200GT PV systems, the suggested ASABA approach outperforms the traditional SABA technique by 99.1% and 99.6 for the single- and double-diode models, respectively. Furthermore, the suggested ASABA method is quantitatively superior to different current optimization algorithms.

Comparative analysis of the hybrid gazelle‐Nelder–Mead algorithm for parameter extraction and optimization of solar photovoltaic systems

“…The algorithm was evaluated using various PV modules and solar cells, including three commercially used modules, and the results confirmed its robustness and high performance in estimating parameters for different irradiance and temperature conditions. Apart from the above examples, different metaheuristic structures have also been employed to tackle the estimation of PV parameters [25][26][27][28][29][30][31][32][33][34].…”

Hybrid Sparrow Search-Exponential Distribution Optimization with Differential Evolution for Parameter Prediction of Solar Photovoltaic Models

“…To utilize a PV system effectively, at first, current-voltage (I-V) characteristics of the system should be well determined both theoretically and practically, and this requires good mathematical modeling for the system. In the most prevalent iterations, solar PV systems may simply be represented by using a current source paralleled with a diode and two resistors of which one is shunt and the other is connected in series [6].…”

“…Certain scavengers engage in continuous surveillance of producers and compete for resources, strategically positioning themselves to enhance their own survival rate. 6.…”

“…The spatial distribution of these sparrows is generated randomly within the population. The mathematical model can be represented as follows, in accordance with Rule (6).…”