Research on regional photovoltaic (PV) power output forecasting method based on weather pattern clustering

Fang Liu; Fang Cui

doi:10.1117/12.2627307

22 April 2022 Research on regional photovoltaic (PV) power output forecasting method based on weather pattern clustering

Fang Liu, Fang Cui

Author Affiliations +

Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 121632I (2022) https://doi.org/10.1117/12.2627307
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China

Abstract

Prediction technology can overcome the shortcomings of random and intermittent of photovoltaic power, which is of importance for the large-scale PV integration and grid scheduling. Firstly, the mathematical description of output wave momentum of photovoltaic power stations is obtained based on satellite data, and then the cluster analysis of photovoltaic power stations in provincial power grid is carried out, and the spatial correlation characteristics of photovoltaic power stations are summarized. Then, the regional photovoltaic power forecasting model based on K-means clustering and long short-term memory model is proposed.

Citation Download Citation

Fang Liu and Fang Cui "Research on regional photovoltaic (PV) power output forecasting method based on weather pattern clustering", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 121632I (22 April 2022); https://doi.org/10.1117/12.2627307

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