基于模糊逻辑与神经网络的短期负荷预测  

Short-term Load Forecasting System Based on Fuzzy Logic Theory and Neural Network

作　　者：宋人杰[1] 潘智勇[2] 王震宇 

机构地区：[1]东北电力大学,吉林吉林132012 [2]北华大学,吉林吉林132013 [3]烟台龙源电力技术有限公司,山东烟台264006

出　　处：《华北电力技术》2007年第12期17-19,共3页North China Electric Power

摘　　要：针对电力系统受多种因素影响的特点,应用模糊逻辑理论和人工神经网络两种方法,发挥各自优势,设计出一个有效的电力系统短期负荷预测系统。该系统着重考虑温度、日期类型以及特殊日期等因素对负荷的影响,实际测试证明可以提高系统的预测精度,适合在电力系统短期负荷预测中应用。As the electric power system is always influenced by many factors, this paper applies fuzzy logic theory and artificial neural network, with advantages of each one. It designs an efficient short-term load forecasting system which takes elements like temperature and types of dates into special consideration. In particular, the influence of the special date on load is included. Through test, it is proved that it can promote the predicting accuracy of the system and can he applied in the short-term load forecasting system in the electric power system.

关 键 词：模糊逻辑 神经网络 特殊日期 短期负荷预测系统 

分 类 号：TM731[电气工程—电力系统及自动化]