Abstract
Photovoltaic power generation is affected by complex and changeable weather conditions, which has the characteristics of volatility and intermittence, resulting in difficulties in photovoltaic grid connection. In order to ensure the stable operation of power system after large-scale photovoltaic grid connection, it is necessary to accurately predict the photovoltaic power in advance. Different weather conditions will lead to great differences in the irradiance actually received by photovoltaic arrays, so a single prediction model is not enough to cope with the prediction of photovoltaic power generation under various complex weather changes. The precision of photovoltaic data clustering is not the key to improve the precision of photovoltaic data classification. To solve the above problems, this paper proposes a matrix algorithm based on solar photovoltaic power prediction.
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Acknowledgements
2021 Innovation fund project of Gansu Provincial Department of Education (Item No: 2021B-429) ; 2021 General project of Gansu Academy of Educational Sciences(Item No: GS[2021]GHB1768) ; 2020 drought Meteorological Science Research Fund Project(Item No: IAM202009).
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Yang, W. (2023). Power Prediction of Solar Photovoltaic Power Generation Based on Matrix Algorithm. In: Hung, J.C., Chang, JW., Pei, Y. (eds) Innovative Computing Vol 2 - Emerging Topics in Future Internet. IC 2023. Lecture Notes in Electrical Engineering, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-99-2287-1_53
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DOI: https://doi.org/10.1007/978-981-99-2287-1_53
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