摘要
提出一种基于人工神经网络的电力负荷预测方法 ,该方法充分吸收了神经网络非线性逼近能力的优点。在神经网络结构设计中充分考虑了电力负荷的特点 ,并用神经网络加权最小方差模型(NNWLS)对样本进行训练。在实际预测中 。
The paper put forward a new load forecasting method based on Neural Network. It takes advantages of nonlinear approximating capability of Neural Network. In the architectural design of the Neural Network, the authors take into full consideration the characteristics of electric load and adopt the Neural Network Weighted Least Square (NNWLS) to train the sample sets. In practice, the method shows the high load_forecasting precision.
出处
《浙江电力》
2004年第4期10-13,共4页
Zhejiang Electric Power
