| 朱俊澎,李子钰,李虎军,邓振立,袁 越.基于负荷分解与辨识的短期电力负荷预测[J].电力需求侧管理,2025,27(2):55-61 |
| 基于负荷分解与辨识的短期电力负荷预测 |
| Short-term power load forecasting based on load decomposition and identification |
| 投稿时间：2024-10-28 修订日期：2025-01-09 |
| DOI：10. 3969 / j. issn. 1009-1831. 2025. 02. 009 |
| 中文关键词: 负荷预测 负荷分解 负荷辨识 长短时记忆网络 |
| 英文关键词: load forecasting load decomposition load identification LSTM network |
| 基金项目:江苏省自然科学基金资助项目（BK20221165） |
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| 摘要点击次数: 50 |
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| 中文摘要: |
| 为进一步降低电力负荷数据预测误差,提出一种基于负荷分解与辨识的负荷短期预测方法。首先,针对各行业电力负荷数据,以温度敏感负荷与温度序列的多项式拟合误差为目标函数,将负荷分解转化为数学优化问题,将各行业总负荷分解为周度基荷分量和温度敏感负荷分量；其次,基于长短时记忆网络对温度敏感负荷分量进行短期负荷预测；最后,将温敏负荷预测结果与周度基荷分量叠加得到完整的负荷预测结果。采用某省2022年分行业电力负荷数据进行验证,结果表明提出的基于负荷分解与辨识的短期电力负荷预测方法可有效降低短期负荷预测误差。 |
| 英文摘要: |
| In order to further reduce the forecasting error of electric load data, a short-term power load forecasting method based on load decomposition and identification is proposed. First, for the electric power load data of each industry, the polynomial fitting error of temperature-sensitive load to the temperature series is taken as the objective function, and the load decomposition is transformed into a mathematical optimization problem, and the total load of each industry is decomposed into the weekly load based on load identification component and the temperature-sensitive load component. Second, the short-term load prediction is performed for the temperature-sensitive load component based on the long short-term memory network. Finally, the temperature-sensitive load prediction results are superimposed with the weekly load based on load identification component to obtain the complete load forecast results. The results show that the short-term load forecasting method based on load decomposition and identification proposed can effectively reduce the short-term load forecasting error. |
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