首页 | 本学科首页   官方微博 | 高级检索  
     

采用神经网络与模糊曲线相结合的短期电力负荷预测方法
引用本文:刘盛松,王正风,王敏. 采用神经网络与模糊曲线相结合的短期电力负荷预测方法[J]. 安徽水利水电职业技术学院学报, 2001, 1(1): 44-48
作者姓名:刘盛松  王正风  王敏
作者单位:1. 上海交通大学电力学院,上海,200240
2. 安徽省电力试验研究所,安徽,合肥,230022
3. 合肥工业大学电气与自动化工程学院,安徽,合肥,230009
摘    要:文章提出了一种神经网络(ANN)与模糊曲线(Fuzzy Curve)有机结合的短期负荷预测方法,该方法采用ANN作为基本负荷预测,再用模糊曲线考虑影响负荷变化的因素(如天气的迅速变化、重大节假日等),对基本负荷预测做出修正,从而得到最终的负荷预测值。同时,针对传统BP学习算法的缺点,将BP算法和模拟退火算法的优点相结合以提高网络的学习性能。实例表明,该ANN—FC模型实用有效、精度高。

关 键 词:电力系统短期负荷预测  人工神经网络  模糊曲线  模拟退火算法
文章编号:34-1240(2001)01-0044-05
修稿时间:2001-10-18

Hybrid short term load forecasting method using neural networks and fuzzy curve
LIU Sheng-song,WANG Zheng-feng,WANG Min. Hybrid short term load forecasting method using neural networks and fuzzy curve[J]. Journal of Anhui Technical College of Water Resources and Hydroelectric Power, 2001, 1(1): 44-48
Authors:LIU Sheng-song  WANG Zheng-feng  WANG Min
Abstract:This paper proposes a hybrid short term load forecasting method which combines neural networks with fuzzy curve. The basic load forecasting is done by ANN. Factors, which have influences on load, are considered and the basic load forecasts are updated with fuzzy curve. As back-propagation learning algorithm has some drawbacks , BP&SA hybrid learning algorithm , which combines the property of BP with the property of SA algorithm , is presented to improve the learning property. Numerical tests showed the efficiency and accuracy of the ANN-FC method.
Keywords:short term load forecasting  artificial neural network  fuzzy curve  simulated annealing algorithm
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号