摘要
根据电力系统短期负荷变化的特性,提出BP模型在实际负荷预测应用中的方法和步骤.对BP网络结构、样本空间、收敛性等作了有针对性的研究.结果表明:多层神经网络应用于电力系统短期负荷预测是可行和有效的.其预报结果比传统的负荷预测方法更准确、经济、效果更好.
Based on the characteristics of the short-term load changes of power system, this paper put forward the method and procedures of BP Model in the practical load forecasting application. Through research on BP network structure, sample space, contractibility and so on, the results showed that it was viable and effective to use multilayer ANN to forecast the short-term load of power system, and its forecasting result was more accurate, more economical and better than traditional load forecasting methods.
出处
《湖南大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2004年第5期51-53,共3页
Journal of Hunan University:Natural Sciences
基金
湖南省自然科学基金资助项目(01JJY2089)
关键词
多层神经网络
BP模型
负荷预测
multilayer neural networks
BP model
load forecasting
