A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems
Integrating artificial intelligence (AI) into photovoltaic (PV) systems has become a revolutionary approach to improving the efficiency, reliability, and predictability of solar power generation. In this paper, we explore the impact of AI technology on PV power generation systems and its application...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tsinghua University Press
2024-12-01
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| Series: | CAAI Artificial Intelligence Research |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/AIR.2024.9150031 |
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| _version_ | 1841550157435371520 |
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| author | Jiaming Hu Boon-Han Lim Xiaoyun Tian Kang Wang Dachuan Xu Feng Zhang Yong Zhang |
| author_facet | Jiaming Hu Boon-Han Lim Xiaoyun Tian Kang Wang Dachuan Xu Feng Zhang Yong Zhang |
| author_sort | Jiaming Hu |
| collection | DOAJ |
| description | Integrating artificial intelligence (AI) into photovoltaic (PV) systems has become a revolutionary approach to improving the efficiency, reliability, and predictability of solar power generation. In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system. On the one hand, the integration with AI technology enables the optimization and improvement of the operational efficiency of PV systems. On the other hand, new challenges have been observed, mainly in the areas of data processing and model management. Moreover, advances in AI technology and hardware upgrades will lead to the rapid global popularization of new energy sources such as solar energy, which is expected to replace traditional energy sources. Finally, we describe forward-looking solutions including transfer learning, few-shot learning, and edge computing, as well as the state of the art. |
| format | Article |
| id | doaj-art-0a71364982d94bbcbfe2c1cc2858507b |
| institution | Kabale University |
| issn | 2097-194X 2097-3691 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | CAAI Artificial Intelligence Research |
| spelling | doaj-art-0a71364982d94bbcbfe2c1cc2858507b2025-01-10T06:44:32ZengTsinghua University PressCAAI Artificial Intelligence Research2097-194X2097-36912024-12-013915003110.26599/AIR.2024.9150031A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic SystemsJiaming Hu0Boon-Han Lim1Xiaoyun Tian2Kang Wang3Dachuan Xu4Feng Zhang5Yong Zhang6Institute of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, ChinaDepartment of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang 43000, MalaysiaInstitute of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, ChinaInstitute of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, ChinaInstitute of Operations Research and Information Engineering, Beijing University of Technology, Beijing 100124, ChinaCollege of Mathematics and Information Science, Hebei University, Baoding 071002, ChinaShenzhen Institutes of Advanced Technology of the Chinese Academy of Science, Shenzhen 518055, ChinaIntegrating artificial intelligence (AI) into photovoltaic (PV) systems has become a revolutionary approach to improving the efficiency, reliability, and predictability of solar power generation. In this paper, we explore the impact of AI technology on PV power generation systems and its applications from a global perspective. Central to the discussion are the pivotal applications of AI in maximum power point tracking (MPPT), power forecasting, and fault detection within the PV system. On the one hand, the integration with AI technology enables the optimization and improvement of the operational efficiency of PV systems. On the other hand, new challenges have been observed, mainly in the areas of data processing and model management. Moreover, advances in AI technology and hardware upgrades will lead to the rapid global popularization of new energy sources such as solar energy, which is expected to replace traditional energy sources. Finally, we describe forward-looking solutions including transfer learning, few-shot learning, and edge computing, as well as the state of the art.https://www.sciopen.com/article/10.26599/AIR.2024.9150031artificial intelligencesolar photovoltaic systemmeta-heuristic algorithmneural networks |
| spellingShingle | Jiaming Hu Boon-Han Lim Xiaoyun Tian Kang Wang Dachuan Xu Feng Zhang Yong Zhang A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems CAAI Artificial Intelligence Research artificial intelligence solar photovoltaic system meta-heuristic algorithm neural networks |
| title | A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems |
| title_full | A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems |
| title_fullStr | A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems |
| title_full_unstemmed | A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems |
| title_short | A Comprehensive Review of Artificial Intelligence Applications in the Photovoltaic Systems |
| title_sort | comprehensive review of artificial intelligence applications in the photovoltaic systems |
| topic | artificial intelligence solar photovoltaic system meta-heuristic algorithm neural networks |
| url | https://www.sciopen.com/article/10.26599/AIR.2024.9150031 |
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