| 基于改进FLN的短期电力负荷预测算法 |
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| 引用本文： | 张海涛,陈宗海,朱六璋. 基于改进FLN的短期电力负荷预测算法[J]. 电工技术学报, 2004, 19(5): 92-96 |
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| 作者姓名： | 张海涛 陈宗海 朱六璋 |
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| 作者单位： | 中国科学技术大学自动化系,合肥,2300272;安徽省电力公司调度通信中心,合肥,230061 |
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| 基金项目： | 面向21世纪教育振兴行动计划(985计划)，中国科技大学校科研和教改项目，安徽省合肥市重点科技基金 |
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| 摘 要： | 短期电力负荷的预测对电力系统具有重要的意义.利用剪枝和附加动量法对标准函数连接神经网络(FLN)进行改进,并将电力负荷的机理和先验知识有机融入,构成了改进的FLN预测网络.对安徽电网电力总负荷的实际预测结果证明了该算法的有效性和优越性.
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| 关 键 词： | 函数连接神经网络 短期电力负荷 剪枝 附加动量 |
| 修稿时间： | 2003-10-13 |
Forecasting Algorithm of Short-Term Electric Power Load Based on Improved FLN |
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| Zhang Haitao Chen Zonghai Zhu Liuzhang. Forecasting Algorithm of Short-Term Electric Power Load Based on Improved FLN[J]. Transactions of China Electrotechnical Society, 2004, 19(5): 92-96 |
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| Authors: | Zhang Haitao Chen Zonghai Zhu Liuzhang |
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| Affiliation: | 1.University of Science and Technology of China Hefei 230027 China 2.Dispatching Center Anhui Electric Power Corporation Hefei 230061 China |
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| Abstract: | Short-term load forecasting is of great importance for electric power systems. Pruning and affixation momentum algorithms are used to improve standard functional link network (FLN), meanwhile, the mechanism and the transcendental knowledge of electrical power load are imported to structure the novel FLN forecasting network as well. The actual forecast results of Anhui Provinces total electric power load indicate that this improved FLN based load forecasting system produces more robust and more accurate load forecasting in comparison with traditional approaches such as decision tree based algorithm and ARMA-wavelet model based algorithm. |
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| Keywords: | Functional link network short-term electric power load pruning affixation momentum |
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