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Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods

Daixuan Zhou1, Yujin Liu1, Xu Wang2, Fuxing Wang1, Yan Jia2,*

1 College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot, 010051, China
2 College of Electric Power, Inner Mongolia University of Technology, Hohhot, 010080, China

* Corresponding Author: Yan Jia. Email: email

Energy Engineering 2024, 121(12), 3573-3616. https://doi.org/10.32604/ee.2024.055853

Abstract

With the increasing proportion of renewable energy in China’s energy structure, among which photovoltaic power generation is also developing rapidly. As the photovoltaic (PV) power output is highly unstable and subject to a variety of factors, it brings great challenges to the stable operation and dispatch of the power grid. Therefore, accurate short-term PV power prediction is of great significance to ensure the safe grid connection of PV energy. Currently, the short-term prediction of PV power has received extensive attention and research, but the accuracy and precision of the prediction have to be further improved. Therefore, this paper reviews the PV power prediction methods from five aspects: influencing factors, evaluation indexes, prediction status, difficulties and future trends. Then summarizes the current difficulties in prediction based on an in-depth analysis of the current research status of physical methods based on the classification of model features, statistical methods, artificial intelligence methods, and combined methods of prediction. Finally, the development trend of PV power generation prediction technology and possible future research directions are envisioned.

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Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods

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APA Style
Zhou, D., Liu, Y., Wang, X., Wang, F., Jia, Y. (2024). Research progress of photovoltaic power prediction technology based on artificial intelligence methods. Energy Engineering, 121(12), 3573-3616. https://doi.org/10.32604/ee.2024.055853
Vancouver Style
Zhou D, Liu Y, Wang X, Wang F, Jia Y. Research progress of photovoltaic power prediction technology based on artificial intelligence methods. Energ Eng. 2024;121(12):3573-3616 https://doi.org/10.32604/ee.2024.055853
IEEE Style
D. Zhou, Y. Liu, X. Wang, F. Wang, and Y. Jia, “Research Progress of Photovoltaic Power Prediction Technology Based on Artificial Intelligence Methods,” Energ. Eng., vol. 121, no. 12, pp. 3573-3616, 2024. https://doi.org/10.32604/ee.2024.055853



cc Copyright © 2024 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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