Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm
Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV ch...
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2023
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my.uniten.dspace-222892023-05-29T14:00:02Z Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. 56728928200 56727852400 31767521400 55568292900 Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms Accurate modeling of photovoltaic (PV) modules is helpful in designing and assessing the energy production of PV systems. A new version of the differential evolution (DE) algorithm, called differential evolution with integrated mutation per iteration (DEIM), is proposed in this study to extract the seven parameters of a double-diode PV module model. This algorithm applies the attraction-repulsion concept of an electromagnetism-like algorithm to boost the mutation operation of the conventional DE algorithm. Moreover, a new adaptive strategy is proposed to tune mutation scaling and crossover rate for each generation. The proposed model is validated through experimental data and other models, which have been proposed in literature using various statistical errors. Results show that DEIM exhibits high accuracy and fast convergence speed compared with other methods. The average root mean square error, mean bias error, and absolute error at maximum power point of the proposed model are 1.713%, 0.149%, and 4.515%, respectively. � 2015 Elsevier Ltd. All rights reserved. Final 2023-05-29T06:00:01Z 2023-05-29T06:00:01Z 2015 Article 10.1016/j.enconman.2015.08.023 2-s2.0-84939782602 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84939782602&doi=10.1016%2fj.enconman.2015.08.023&partnerID=40&md5=75392c2df20fd6e8b46d34fb25edbe73 https://irepository.uniten.edu.my/handle/123456789/22289 105 552 561 Elsevier Ltd Scopus |
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Algorithms; Diodes; Errors; Extraction; Iterative methods; Mean square error; Optimization; Parameter estimation; Parameter extraction; Photovoltaic cells; Differential evolution algorithms; Diode modeling; Electromagnetism-like algorithm; Fast convergence speed; Hybrid evolutionary algorithm; IV characteristics; Photovoltaic model; Root mean square errors; Evolutionary algorithms |
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56728928200 |
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56728928200 Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. |
| format |
Article |
| author |
Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. |
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Muhsen D.H. Ghazali A.B. Khatib T. Abed I.A. Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| author_sort |
Muhsen D.H. |
| title |
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| title_short |
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| title_full |
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| title_fullStr |
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| title_full_unstemmed |
Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| title_sort |
parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm |
| publisher |
Elsevier Ltd |
| publishDate |
2023 |
| _version_ |
1806425825931689984 |