摘要
提出用于电力短期负荷预测 (STLF)的一种模糊神经网络 (FNN)方法 ,该方法针对BP网络收敛速度慢、易导致局部极小值的缺点 ,将考虑气候、温度、星期类型等影响因素的模糊技术与快速二阶BP网络相结合 ,并以南方电网负荷预测为例 ,应用MATLAB语言对系统进行仿真训练 ,测试结果表明 ,该方法具有较高的预测精度。
The fuzzy neural network used for power system short-term load forecasting is put forward.This method aims at overcoming the shortcomings of BP neural networks such as slow convergence and local minimization and working with fuzzy technology which take the weather,the temperature and the day type into account.To demonstrate the effectiveness of the proposed approach,short-term load forecasting is performed on the south power system with the help of MATLAB.The result shows the efficiency and accuracy of the proposed method.
出处
《自动化技术与应用》
2003年第8期23-26,45,共5页
Techniques of Automation and Applications
