| 基于极限学习机的光伏发电短期预测校正方法 |
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| 引用本文：周海1，2,李登宣1,尹万思3,尹瑞4,王一峰4,朱想1.基于极限学习机的光伏发电短期预测校正方法[J].电网与清洁能源,2020,36(6):64~69 |
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| 基金项目:国网河北省电力公司科技项目（SGTYHT/17-JS-199） |
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| 中文摘要:光伏发电短期预测在电力系统实时调度中具有重要意义。受诸多因素影响，光伏发电短期预测精度还无法达到光伏电站要求，对光伏并网调度带来较大影响。针对这一问题，提出了基于极限学习机（ELM）的光伏发电短期预测校正方法。说明了光伏发电短期预测中的误差特征，并利用提出的校正方法对原来光伏发电短期预测结果进行了优化。通过与其他方法的对比，验证了此方法的有效性，说明了论文方法能够有效提高光伏发电短期预测精度。 |
| 中文关键词:光伏功率 短期预测 极限学习机 |
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| Short-Term Forecasting Correction Method of Photovoltaic Power Based on Extreme Learning Machine |
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| Abstract:The short-term forecasting of photovoltaic（PV） power is of great significance in real-time dispatching of power systems. Due to many factors， the short-term forecasting accuracy of PV power fails to meet the requirements of the PV power plant， which has great influence on the PV grid-connected dispatching. To this end， this paper proposes a short-term forecasting correction method for PV power based on extreme learning machine（ELM）.The paper explains the characteristic of the error in the short-term forecasting of PV power， and uses the proposed correction method to optimize the original short-term forecasting results of PV power. Compared with other methods， the effectiveness of this method is verified， suggesting that method paper can effectively improve the short-term forecasting accuracy. |
| keywords:PV power short-term forecasting extreme learning machine |
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