摘要
According to the fact that photovoltaic plants have similar generation power under similar weather conditions, an Ultra-short-term power forecasting method based on NWP similarity analysis is proposed. The proposed method uses the Pearson correlation coefficient to find weather forecast data similar to the predicted time, and estimates the power in the predicted time based on the actual power of the similar time. The proposed method can efficiently forecast the generated power based on the weather forecast data. Compared with the neural network, the proposed method has a better effect, especially in the period of large data fluctuations, which has higher reliability.
| 投稿的翻译标题 | Power forecasting of ultra-short-term photovoltaic station based on NWP similarity analysis |
|---|---|
| 源语言 | 繁体中文 |
| 页（从-至） | 142-147 |
| 页数 | 6 |
| 期刊 | Taiyangneng Xuebao/Acta Energiae Solaris Sinica |
| 卷 | 43 |
| 期 | 4 |
| DOI | |
| 出版状态 | 已出版 - 28 4月 2022 |
关键词
- Numerical weather prediction
- Pearson correlation coefficient
- Photovoltaic station
- Power forecasting
- Similarity analysis
指纹
探究 '基于NWP相似性分析的超短期光伏发电功率预测' 的科研主题。它们共同构成独一无二的指纹。引用此
Zhang, S., Dong, L., Ji, D., Hao, Y., & Zhang, X. (2022). 基于NWP相似性分析的超短期光伏发电功率预测. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 43(4), 142-147. https://doi.org/10.19912/j.0254-0096.tynxb.2020-0717