A prediction model of dust accumulation on photovoltaic modules considering rainfall washing
Abstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfal...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-12-01
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| Series: | Electronics Letters |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/ell2.13060 |
| _version_ | 1797362168439504896 |
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| author | Shuangbin Ma FeiTing Huang Jinxin Chen Weiyun Tong Lin Wang Qiping Xu |
| author_facet | Shuangbin Ma FeiTing Huang Jinxin Chen Weiyun Tong Lin Wang Qiping Xu |
| author_sort | Shuangbin Ma |
| collection | DOAJ |
| description | Abstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfall concentration in the current region. On the basis of particle swarm optimization (PSO) and the least‐squares support vector machine (LSSVM), the density of dust on photovoltaic modules was estimated. The authors proposed that the inertia weight decreased as a concave function to improve the efficiency of optimization and let the two positive constants change dynamically to improve convergence performance. The dust accumulation prediction model was established considering natural rainfall and the authors obtained the attenuation rate of the photovoltaic power output. Finally, the experiments in Hangzhou showed that the model can predict the density of accumulated dust quickly, which provides a theory for predicting PV power generation and managing the cleaning frequency. |
| first_indexed | 2024-03-08T16:04:30Z |
| format | Article |
| id | doaj.art-7b785b2ca1e04986be4ccb15befb165d |
| institution | Directory Open Access Journal |
| issn | 0013-5194 1350-911X |
| language | English |
| last_indexed | 2024-03-08T16:04:30Z |
| publishDate | 2023-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | Electronics Letters |
| spelling | doaj.art-7b785b2ca1e04986be4ccb15befb165d2024-01-08T08:30:54ZengWileyElectronics Letters0013-51941350-911X2023-12-015924n/an/a10.1049/ell2.13060A prediction model of dust accumulation on photovoltaic modules considering rainfall washingShuangbin Ma0FeiTing Huang1Jinxin Chen2Weiyun Tong3Lin Wang4Qiping Xu5College of Engineering Zhejiang Normal University Jinhua, Zhejiang ChinaZhejiang HOOEASY Smart Technology Co., Ltd Jinhua, Zhejiang ChinaCollege of Engineering Zhejiang Normal University Jinhua, Zhejiang ChinaZhejiang HOOEASY Smart Technology Co., Ltd Jinhua, Zhejiang ChinaZhejiang HOOEASY Smart Technology Co., Ltd Jinhua, Zhejiang ChinaCollege of Engineering Zhejiang Normal University Jinhua, Zhejiang ChinaAbstract The power generation of the photovoltaic plant is related to the cleanliness of the photovoltaic modules. The accumulation of natural dust is the main source of pollution, which is affected by human activities and meteorological factors such as temperature, humidity, wind speed, and rainfall concentration in the current region. On the basis of particle swarm optimization (PSO) and the least‐squares support vector machine (LSSVM), the density of dust on photovoltaic modules was estimated. The authors proposed that the inertia weight decreased as a concave function to improve the efficiency of optimization and let the two positive constants change dynamically to improve convergence performance. The dust accumulation prediction model was established considering natural rainfall and the authors obtained the attenuation rate of the photovoltaic power output. Finally, the experiments in Hangzhou showed that the model can predict the density of accumulated dust quickly, which provides a theory for predicting PV power generation and managing the cleaning frequency.https://doi.org/10.1049/ell2.13060distributed power generationparticle swarm optimisationsolar powersupport vector machines |
| spellingShingle | Shuangbin Ma FeiTing Huang Jinxin Chen Weiyun Tong Lin Wang Qiping Xu A prediction model of dust accumulation on photovoltaic modules considering rainfall washing Electronics Letters distributed power generation particle swarm optimisation solar power support vector machines |
| title | A prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| title_full | A prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| title_fullStr | A prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| title_full_unstemmed | A prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| title_short | A prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| title_sort | prediction model of dust accumulation on photovoltaic modules considering rainfall washing |
| topic | distributed power generation particle swarm optimisation solar power support vector machines |
| url | https://doi.org/10.1049/ell2.13060 |
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