Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm
The substantial volatility of photovoltaic (PV) power output presents challenges to the stable operation of power grids. To improve the accuracy and stability of PV power prediction, this study proposes a PV power prediction system based on a dual-layer decomposition strategy and a dynamic grouping...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-05-01
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| Series: | International Journal of Electrical Power & Energy Systems |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525001139 |
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| _version_ | 1850060708429955072 |
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| author | Xiaole Tang Hao Lu Yanting Kang Wenjun Zhao |
| author_facet | Xiaole Tang Hao Lu Yanting Kang Wenjun Zhao |
| author_sort | Xiaole Tang |
| collection | DOAJ |
| description | The substantial volatility of photovoltaic (PV) power output presents challenges to the stable operation of power grids. To improve the accuracy and stability of PV power prediction, this study proposes a PV power prediction system based on a dual-layer decomposition strategy and a dynamic grouping multi-objective Coati optimization algorithm (DGMOCOA). This system includes three core modules: data preprocessing, optimization, and prediction. The dual-layer decomposition strategy effectively utilizes high-frequency signal information, overcoming the limitations of single-layer methods. Additionally, the DGMOCOA employs a dynamic grouping strategy to balance exploration and exploitation, enhancing the system’s accuracy and stability. To validate the proposed strategy and hybrid model, extensive experiments were conducted. The results show that, compared to 11 benchmark models, the proposed model achieves higher prediction accuracy and greater stability. In interval prediction, it also demonstrates higher coverage and narrower intervals. |
| format | Article |
| id | doaj-art-db9b6f8c2b5c443fb39147a1fe737d1c |
| institution | DOAJ |
| issn | 0142-0615 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Electrical Power & Energy Systems |
| spelling | doaj-art-db9b6f8c2b5c443fb39147a1fe737d1c2025-08-20T02:50:29ZengElsevierInternational Journal of Electrical Power & Energy Systems0142-06152025-05-0116611056210.1016/j.ijepes.2025.110562Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithmXiaole Tang0Hao Lu1Yanting Kang2Wenjun Zhao3Laboratory of Energy Carbon Neutrality, School of Electrical Engineering, Xinjiang University, Urumqi 830047, China; School of Intelligence Science and Technology, Xinjiang University, Urumqi 830047, ChinaLaboratory of Energy Carbon Neutrality, School of Electrical Engineering, Xinjiang University, Urumqi 830047, China; Ruoqiang Energy Industry Research Institute, Engineering Research Center of Northwest Energy Carbon Neutrality, Ministry of Education, Urumqi & Ruoqiang 830047 & 841800, China; School of Intelligence Science and Technology, Xinjiang University, Urumqi 830047, China; Corresponding author at: Laboratory of Energy Carbon Neutrality, School of Electrical Engineering, Xinjiang University, Urumqi 830047, China.School of Intelligence Science and Technology, Xinjiang University, Urumqi 830047, ChinaDepartment of Architecture and Built Environment, Faculty of Engineering, University of Nottingham, University Park, Nottingham NG7 2RD, United KingdomThe substantial volatility of photovoltaic (PV) power output presents challenges to the stable operation of power grids. To improve the accuracy and stability of PV power prediction, this study proposes a PV power prediction system based on a dual-layer decomposition strategy and a dynamic grouping multi-objective Coati optimization algorithm (DGMOCOA). This system includes three core modules: data preprocessing, optimization, and prediction. The dual-layer decomposition strategy effectively utilizes high-frequency signal information, overcoming the limitations of single-layer methods. Additionally, the DGMOCOA employs a dynamic grouping strategy to balance exploration and exploitation, enhancing the system’s accuracy and stability. To validate the proposed strategy and hybrid model, extensive experiments were conducted. The results show that, compared to 11 benchmark models, the proposed model achieves higher prediction accuracy and greater stability. In interval prediction, it also demonstrates higher coverage and narrower intervals.http://www.sciencedirect.com/science/article/pii/S0142061525001139Photovoltaic power prediction systemDynamic grouping multi-objective coati optimization algorithmDual decomposition strategyInterval prediction |
| spellingShingle | Xiaole Tang Hao Lu Yanting Kang Wenjun Zhao Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm International Journal of Electrical Power & Energy Systems Photovoltaic power prediction system Dynamic grouping multi-objective coati optimization algorithm Dual decomposition strategy Interval prediction |
| title | Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm |
| title_full | Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm |
| title_fullStr | Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm |
| title_full_unstemmed | Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm |
| title_short | Photovoltaic power prediction system based on dual-layer decomposition strategy and a novel dynamic grouping multi-objective coati optimization algorithm |
| title_sort | photovoltaic power prediction system based on dual layer decomposition strategy and a novel dynamic grouping multi objective coati optimization algorithm |
| topic | Photovoltaic power prediction system Dynamic grouping multi-objective coati optimization algorithm Dual decomposition strategy Interval prediction |
| url | http://www.sciencedirect.com/science/article/pii/S0142061525001139 |
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