Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

被引：34

作者：

Xia Hua ^{[1
]}

Gang Zhang ^{[2
]}

Jiawei Yang ^{[3
]}

Zhengyuan Li ^{[1
]}

机构：

[1] Gansu Electric Power Research Institute,State Grid Gansu Electric Power Company

[2] Institute of Water Resources and Hydro-Electric Engineering,Xi'an University of Technology

[3] College of International Communications,China Three Gorges University

来源：

ZTE Communications | 2015年 / 13卷 / 03期

关键词：

D O I：

暂无

中图分类号：

TP183 [人工神经网络与计算]; TM715 [电力系统规划];

学科分类号：

080802 [电力系统及其自动化]; 140502 [人工智能];

摘要：

Aiming at the low accuracy problem of power system short-term load forecasting by traditional methods,a back-propagation artificial neural network(BP-ANN) based method for short-term load forecasting is presented in this paper.The forecast points are related to prophase adjacent data as well as the periodical long-term historical load data.Then the short-term load forecasting model of Shanxi Power Grid(China) based on BP-ANN method and correlation analysis is established.The simulation model matches well with practical power system load,indicating the BP-ANN method is simple and with higher precision and practicality.

引用

页码：2 / 5

页数：4