| 基于均匀设计混合算法的短期负荷预测 |
| |
| 引用本文： | 赵宇红,李兰君,刘冲,曾金. 基于均匀设计混合算法的短期负荷预测[J]. 电力需求侧管理, 2006, 8(4): 8-11 |
| |
| 作者姓名： | 赵宇红 李兰君 刘冲 曾金 |
| |
| 作者单位： | 南华大学,电气工程学院,湖南,衡阳,421001;湖南省电力勘测设计院,湖南,长沙,410007 |
| |
| 摘 要： | 提高电力系统短期负荷预测精度有助于提高电网运行的安全性和经济性,改善供电质量。将均匀设计、改进遗传算法和误差反向传播算法相结合构成混合算法,并将其用于短期负荷预测。数据样本训练和实际预测结果表明,该模型不仅可避免陷入局部极小点,而且可提高预测精度和网络训练速度。
|
| 关 键 词： | 短期负荷预测 均匀设计 改进遗传算法 误差反向传播算法 |
| 文章编号： | 1009-1831（2006）04-0008-04 |
| 收稿时间： | 2005-11-02 |
| 修稿时间： | 2005-11-02 |
Uniform design hybrid algorithm in short-term load forecasting |
| |
| ZHAO Yu-hong,LI Lan-jun,LIU Chong,ZENG Jin. Uniform design hybrid algorithm in short-term load forecasting[J]. Power Demand Side Management, 2006, 8(4): 8-11 |
| |
| Authors: | ZHAO Yu-hong LI Lan-jun LIU Chong ZENG Jin |
| |
| Affiliation: | 1.Nanhua University ,Hengyang 421001 China;2.Hunan Electric Power Survey Designing Institute, Changsha 410007, China |
| |
| Abstract: | Improving the precision of electric power system load forecasting can enhace the security and economy of network and improve supply quality. The hybrid algorithm that combines uniform design, improved genetic algorithm and error back-propagagation algorithm is used to short-term load forecasting. The training and testing results show that this model can not only avoid convergence to local minium but also improve the training speed of neural network and accuracy of load forecasting. |
| |
| Keywords: | short-term load forecasting uniform design improved genetic algorithm BP algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
