Power prediction of photovoltaic power plant based on double-loop distributed gradient boosting algorithm

Hai Wang; Lin Xu; Zheng He; Huanhuan Dong

doi:10.1117/12.2675342

25 May 2023 Power prediction of photovoltaic power plant based on double-loop distributed gradient boosting algorithm

Hai Wang, Lin Xu, Zheng He, Huanhuan Dong

Proceedings Volume 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022); 1263625 (2023) https://doi.org/10.1117/12.2675342
Event: Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 2022, Shenyang, China

Abstract

With the increasingly prominent problems of energy carbon emissions, environmental pollution, and climate change, China has further accelerated the construction of new energy sources to deal with a series of ecological problems. China's new energy structure mainly relies on photovoltaic and wind power generation. In addition, wind and solar power generation also has problems such as instability and strong randomness, so existing big data and artificial intelligence can be used to solve this problem and improve wind and solar forecasting. In this paper, a double-loop distributed gradient enhancement algorithm is used to improve the power prediction accuracy of photovoltaic power plants, which effectively solves the shortcomings of slow speed and poor prediction stability in photovoltaic power prediction, and ensures the power dispatching problem based on new power systems.

Citation Download Citation

Hai Wang, Lin Xu, Zheng He, and Huanhuan Dong "Power prediction of photovoltaic power plant based on double-loop distributed gradient boosting algorithm", Proc. SPIE 12636, Third International Conference on Machine Learning and Computer Application (ICMLCA 2022), 1263625 (25 May 2023); https://doi.org/10.1117/12.2675342

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