摘要
提出了电力系统短期负荷预报基于模糊集的神经网络方法 .该方法计及了天气和日期特征量 ,具有训练时间短预测精度高的特点 .采用两种学习算法 ,依据模糊集概念用某地区电网实际数据建立样本集后 ,对ANN进行了训练 ,通过分析比较得出了优化模型 .
A short_term load forecasting approach using artificial neural network based on fuzzy set is presented. The weather variables and date variables are considered; therefore the approach is better at respects of training time and forecasting accuracy. After training specimen set is established based on actual data of a region, two algorithms are used to train ANN in order to acquire more better results. The calculation results show that this approach is practical and effective.
出处
《武汉大学学报（工学版）》
CAS
CSCD
北大核心
2002年第4期68-71,共4页
Engineering Journal of Wuhan University
关键词
模糊集
神经网络
短期负荷预报
电力系统
BP算法
fuzzy set
artificial neural network
short_term load forecasting
power system
BP algorithm
