基于BP人工神经网络电力负荷预测  

Short-term Electric Load Prediction Based on BP Artificial Neural Network

作　　者：郭龙钢[1] 

机构地区：[1]洛阳理工学院电气工程与自动化系,河南洛阳471023

出　　处：《洛阳理工学院学报（自然科学版）》2013年第1期62-64,共3页Journal of Luoyang Institute of Science and Technology：Natural Science Edition

摘　　要：由于影响电力负荷的因素之间存在着非线性,所以采用神经网络方案来进行短期电力负荷预测。对应用于实际的神经网络算法进行了具体处理,如数据的归一化,输入向量和输出向量的选择。仿真结果表明其有较好的预测精度。该模型具有网络结构较小、训练时间短、易于实现的优点。Owing to the nonlinearity of the factors affecting power load, the neural network has been applied to the short-term load forecast. The neural network algorithm has been processed in application, including the normalization of data, and the choice of input and output vectors. Results of simulation prove that it has a better forecast accuracy, for this model possesses the advantages of smaller network structure, shorter training time and more convenience to realize, etc..

关 键 词：神经网络 负荷预报 训练样本 

分 类 号：TM715[电气工程—电力系统及自动化]