摘要
短期电力负荷预测是工程技术人员安排电力调度的重要依据.研究了利用混沌理论与RBF神经网络相结合实现短期电力负荷预测的方法.并用该方法预测湖南某地区的月负荷,预测的数据准确率较好,为短期电力负荷预测提供了一条新的途径.
The short-term load forecasting is an important work as well as the basis for the engineer to distribute the power load. In this paper we discuss a new approach combining chaos theory and RBF neural networks to forecast the short-term power load.Applying it in the month-load forecasting of some area in Hunan,the result is satisfactory.
出处
《长沙理工大学学报(自然科学版)》
CAS
2005年第1期44-48,共5页
Journal of Changsha University of Science and Technology:Natural Science
基金
湖南省自然科学基金资助项目(01JJY2061)