Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm
The rapid and accurate acquisition of model parameters of photovoltaic (PV) modules is of great significance for the efficient operation and maintenance of photovoltaic power plants under the background of the development of new power systems. To solve the problems of poor accuracy and slow velocity...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-11-01
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| Series: | Energy Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352484722017802 |
| _version_ | 1797901872769531904 |
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| author | Jian Dang Gaoming Wang Chaohao Xia Rong Jia Peihang Li |
| author_facet | Jian Dang Gaoming Wang Chaohao Xia Rong Jia Peihang Li |
| author_sort | Jian Dang |
| collection | DOAJ |
| description | The rapid and accurate acquisition of model parameters of photovoltaic (PV) modules is of great significance for the efficient operation and maintenance of photovoltaic power plants under the background of the development of new power systems. To solve the problems of poor accuracy and slow velocity of identification of traditional PV modules model parameters, this paper proposed an identification of parameter method based on fuzzy adaptive differential evolution algorithm (FADE). In the proposed method, based on the I–V output characteristics of PV modules, a DE/current-to-SP-best/1 variation strategy is constructed to increase the local search capability of module model parameter identification; In addition, fuzzy selection strategy and an adaptive parameter adjustment strategy are introduced to effectively control the crossover probability and mutation factors to avoid the discrimination into local optimum while improving the convergence of the algorithm. The performance of the proposed method has been verified by extracting classical polycrystalline and monocrystalline modules parameters, The solution results of the polycrystalline module Photowatt-PWP201 (2.42507E−3), STP6-120/36 (1.66006E−2) and monocrystalline module STM6-40/36 (1.72981E−3) comprehensively show that FADE has better accuracy and robustness compared with other algorithms. |
| first_indexed | 2024-04-10T09:08:50Z |
| format | Article |
| id | doaj.art-7613e67eafaa4a53a2baf71c00084450 |
| institution | Directory Open Access Journal |
| issn | 2352-4847 |
| language | English |
| last_indexed | 2024-04-10T09:08:50Z |
| publishDate | 2022-11-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Reports |
| spelling | doaj.art-7613e67eafaa4a53a2baf71c000844502023-02-21T05:13:32ZengElsevierEnergy Reports2352-48472022-11-0181208112091Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithmJian Dang0Gaoming Wang1Chaohao Xia2Rong Jia3Peihang Li4Institute for Electrical Power & Integrated Energy of Shaanxi Province, Xi’an University of Technology, Xi’an 710048, China; School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China; Corresponding author at: Institute for Electrical Power & Integrated Energy of Shaanxi Province, Xi’an University of Technology, Xi’an 710048, China.School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaInstitute for Electrical Power & Integrated Energy of Shaanxi Province, Xi’an University of Technology, Xi’an 710048, China; School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaThe rapid and accurate acquisition of model parameters of photovoltaic (PV) modules is of great significance for the efficient operation and maintenance of photovoltaic power plants under the background of the development of new power systems. To solve the problems of poor accuracy and slow velocity of identification of traditional PV modules model parameters, this paper proposed an identification of parameter method based on fuzzy adaptive differential evolution algorithm (FADE). In the proposed method, based on the I–V output characteristics of PV modules, a DE/current-to-SP-best/1 variation strategy is constructed to increase the local search capability of module model parameter identification; In addition, fuzzy selection strategy and an adaptive parameter adjustment strategy are introduced to effectively control the crossover probability and mutation factors to avoid the discrimination into local optimum while improving the convergence of the algorithm. The performance of the proposed method has been verified by extracting classical polycrystalline and monocrystalline modules parameters, The solution results of the polycrystalline module Photowatt-PWP201 (2.42507E−3), STP6-120/36 (1.66006E−2) and monocrystalline module STM6-40/36 (1.72981E−3) comprehensively show that FADE has better accuracy and robustness compared with other algorithms.http://www.sciencedirect.com/science/article/pii/S2352484722017802Photovoltaic modelsParameter extractionFuzzy adaptive differential evolutionOptimization algorithm |
| spellingShingle | Jian Dang Gaoming Wang Chaohao Xia Rong Jia Peihang Li Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm Energy Reports Photovoltaic models Parameter extraction Fuzzy adaptive differential evolution Optimization algorithm |
| title | Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm |
| title_full | Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm |
| title_fullStr | Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm |
| title_full_unstemmed | Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm |
| title_short | Research on the parameter identification of PV module based on fuzzy adaptive differential evolution algorithm |
| title_sort | research on the parameter identification of pv module based on fuzzy adaptive differential evolution algorithm |
| topic | Photovoltaic models Parameter extraction Fuzzy adaptive differential evolution Optimization algorithm |
| url | http://www.sciencedirect.com/science/article/pii/S2352484722017802 |
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