2024
DOI: 10.1109/access.2024.3398033
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RSMD-RF-BGSkip Based PV Generation Prediction Method

Guomin Xie,
Zhongbao Lin

Abstract: With the increasing use of photovoltaic (PV) power generation, power forecasting has become equally important to maintain stable and economic operation of the power system. However, the high frequency component of the PV power time series reduces the accuracy of the model predictions. Therefore, this paper proposes a short-term prediction model for PV power based on Row Secondary Modal Decomposition (RSMD), Random Forest (RF), and BGSkip neural network. Firstly, modal features with different complexity are obt… Show more

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