| 基于RBF神经网络的短期电力负荷预测 |
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| 引用本文： | 曹安照,田丽.基于RBF神经网络的短期电力负荷预测[J].电子科技大学学报（自然科学版）,2006,35(4):507-509. |
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| 作者姓名： | 曹安照 田丽 |
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| 作者单位： | 安徽工程科技学院电气工程系,安徽,芜湖,241000;安徽工程科技学院电气工程系,安徽,芜湖,241000 |
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| 摘 要： | 研究了天气和特殊事件对电力负荷的影响,建立了结合径向基函数神经网络来进行短期负荷预测的模型。将温度、降雨量运用于径向基函数神经网络中,提高了训练的可信度和可靠性。利用该模型编排的实用化软件投入到了实际应用中。结果表明:该方法具有较高的预测精度和较强的实用性。
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| 关 键 词： | 径向基函数神经网络 用电量 GDP 短期负荷预测 |
| 收稿时间： | 2004-05-19 |
| 修稿时间： | 2004-05-19 |
Short-Term Electric Power Load Forecasting Based on Neural Network Model |
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| CAO An-zhao,TIAN Li.Short-Term Electric Power Load Forecasting Based on Neural Network Model[J].Journal of University of Electronic Science and Technology of China,2006,35(4):507-509. |
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| Authors: | CAO An-zhao TIAN Li |
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| Affiliation: | 1.Department of Electrical Engineering,Anhui University of Technology and Science Wuhu Anhui 241000 |
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| Abstract: | The effect of weather factors and special events on electric power load are investigated. A load forecasting model based on Radial Basis Function (RBF)is presented the temperature and precipitation are applied to RBF's training process. This optimizing algorithm can improve the credibility and reliability of network training. A practical software package has been formed and applied, which improves the precision of short-term load forecastin. The effectiveness of the model has been verified by actual operation. |
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| Keywords: | GDP |
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