A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model
Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovol...
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2023
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my.uniten.dspace-226522023-05-29T14:11:30Z A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. 56728928200 56727852400 31767521400 55568292900 Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system This paper proposes different evolutionary algorithms, such as differential evolution and electromagnetism-like algorithms, to extract the five parameters of a single-diode photovoltaic module's model. Hybrid evolutionary algorithms are proposed with integrated and adaptive mutation per iteration schemes. In addition, a new formula to adjust the mutation scaling factor and crossover rate for each generation is proposed. Analyses are performed based on experimental data points under different weather conditions to explain the robustness and reliability of the proposed methods. Results show that the proposed hybrid algorithms, namely, evolutionary algorithm with integrated mutation per iteration and evolutionary algorithm with adaptive mutation per iteration, exhibit better performance than electromagnetism-like algorithm and other methods in terms of accuracy, CPU execution time, and convergence. The proposed hybrid algorithms offer a root mean square error, mean bias error, coefficient of determination and CPU execution time around 0.062, 0.006 and 0.992, and less than 20 s respectively. Furthermore, the feasibility of the proposed methods is validated by comparing the obtained results with those of other methods under various statistical errors. As a conclusion, the proposed hybrid algorithms offer root mean square error and mean bias error less than other methods by 14% at least. � 2016 Elsevier Ltd. Final 2023-05-29T06:11:29Z 2023-05-29T06:11:29Z 2016 Article 10.1016/j.renene.2016.04.072 2-s2.0-84964949903 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84964949903&doi=10.1016%2fj.renene.2016.04.072&partnerID=40&md5=3e851b14217f91267a191eefaea19a76 https://irepository.uniten.edu.my/handle/123456789/22652 96 377 389 Elsevier Ltd Scopus |
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Algorithms; Diodes; Errors; Iterative methods; Least squares approximations; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Coefficient of determination; Differential Evolution; Electromagnetism-like algorithm; Hybrid evolutionary algorithm; Photovoltaic; Photovoltaic modules; Root mean square errors; Single-diode models; Evolutionary algorithms; algorithm; comparative study; electromagnetic method; estimation method; experimental design; numerical method; parameterization; performance assessment; photovoltaic system |
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56728928200 |
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56728928200 Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. |
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Article |
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Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. |
| spellingShingle |
Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| author_sort |
Muhsen D.H. |
| title |
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| title_short |
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| title_full |
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| title_fullStr |
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| title_full_unstemmed |
A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| title_sort |
comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806428288705363968 |
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13.222552 |