| 运用样本更新的实时神经网络进行短期电力负荷预测 |
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| 引用本文： | 王雪峰,邬建华,冯英浚,王建元.运用样本更新的实时神经网络进行短期电力负荷预测[J].系统工程理论与实践,2003,23(4):95-99. |
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| 作者姓名： | 王雪峰 邬建华 冯英浚 王建元 |
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| 作者单位： | 哈尔滨工业大学数学系 |
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| 基金项目： | 国家自然科学基金 (699740 13 ) |
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| 摘 要： | 用多层神经网络模型解决短期电力负荷预测问题 ,提出了运用基于非梯度的单参数动态搜索(SPDS)算法训练网络 .这种学习算法可以克服 BP学习算法对规模大、特征多的问题难以收敛的困难 .根据预测日的天气信息进行样本集的动态构造和网络的实时训练 .计算结果表明 ,文中提出的模型可以较好地进行短期电力负荷预测 ,也验证了 SPDS学习算法的有效性.
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| 关 键 词： | 短期负荷预测 多层神经网络 单参数动态搜索 |
| 文章编号： | 1000-6788(2003)04-0095-05 |
| 修稿时间： | 2001年8月2日 |
The Samples Updated Real-time Neural Network and Its Application in Short Term Load Forecasting |
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| WANG Xue-feng,WU Jian-hua,FENG Ying-jun,WANG Jian-yuan.The Samples Updated Real-time Neural Network and Its Application in Short Term Load Forecasting[J].Systems Engineering —Theory & Practice,2003,23(4):95-99. |
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| Authors: | WANG Xue-feng WU Jian-hua FENG Ying-jun WANG Jian-yuan |
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| Institution: | Harbin Institute of Technology |
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| Abstract: | A multi-layer neural network based on Single Parameter Dynamic Search Algorithm (SPDS) is proposed for short term load forecasting in this paper. The model proposed can overcome BP algorithm's dissatisfied convergence for large-scale problem,training samples is dynamically built according to the information of the weather forecast. The calculations show that the method is efficient for short term load forecasting. |
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| Keywords: | short term load forecasting multi-layer neural networks SPDS algorithm |
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