Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization
The output stability of the photovoltaic (PV) system is directly affected by temperature change of PV panels. In this paper, a novel temperature prediction method of PV panels with support vector machine (SVM) is proposed, which can solve the temperature prediction problem in a complex environment....
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/9278162 |
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| _version_ | 1832554584434802688 |
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| author | Siyuan Fan Shengxian Cao Yanhui Zhang |
| author_facet | Siyuan Fan Shengxian Cao Yanhui Zhang |
| author_sort | Siyuan Fan |
| collection | DOAJ |
| description | The output stability of the photovoltaic (PV) system is directly affected by temperature change of PV panels. In this paper, a novel temperature prediction method of PV panels with support vector machine (SVM) is proposed, which can solve the temperature prediction problem in a complex environment. In order to optimize parameters of SVM, a Pigeon-Inspired Optimization (PIO) method is given. Meanwhile, the delay factor (DF) is added to improve the PIO algorithm for avoiding the problem of local optimum. Moreover, a multisensor monitoring system of PV is established, and the collected data of temperature are used to train and verify the accuracy of the model. Finally, the proposed method is evaluated using synthetic and actual data sets. Simulation results show that the DFPIO-SVM can obtain better predictive performance. |
| format | Article |
| id | doaj-art-a68820e039fd4f6c95ab3bbbe337f2bd |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-a68820e039fd4f6c95ab3bbbe337f2bd2025-02-03T05:51:11ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/92781629278162Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired OptimizationSiyuan Fan0Shengxian Cao1Yanhui Zhang2School of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Automation Engineering, Northeast Electric Power University, Jilin 132012, ChinaShenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaThe output stability of the photovoltaic (PV) system is directly affected by temperature change of PV panels. In this paper, a novel temperature prediction method of PV panels with support vector machine (SVM) is proposed, which can solve the temperature prediction problem in a complex environment. In order to optimize parameters of SVM, a Pigeon-Inspired Optimization (PIO) method is given. Meanwhile, the delay factor (DF) is added to improve the PIO algorithm for avoiding the problem of local optimum. Moreover, a multisensor monitoring system of PV is established, and the collected data of temperature are used to train and verify the accuracy of the model. Finally, the proposed method is evaluated using synthetic and actual data sets. Simulation results show that the DFPIO-SVM can obtain better predictive performance.http://dx.doi.org/10.1155/2020/9278162 |
| spellingShingle | Siyuan Fan Shengxian Cao Yanhui Zhang Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization Complexity |
| title | Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization |
| title_full | Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization |
| title_fullStr | Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization |
| title_full_unstemmed | Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization |
| title_short | Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization |
| title_sort | temperature prediction of photovoltaic panels based on support vector machine with pigeon inspired optimization |
| url | http://dx.doi.org/10.1155/2020/9278162 |
| work_keys_str_mv | AT siyuanfan temperaturepredictionofphotovoltaicpanelsbasedonsupportvectormachinewithpigeoninspiredoptimization AT shengxiancao temperaturepredictionofphotovoltaicpanelsbasedonsupportvectormachinewithpigeoninspiredoptimization AT yanhuizhang temperaturepredictionofphotovoltaicpanelsbasedonsupportvectormachinewithpigeoninspiredoptimization |