摘要
在东北地区电力供需形势逐渐缓和的情况下 ,电力市场开拓的任务变得十分艰巨 ,正确地预测出地区销售电量的水平 ,对于决策者合理地确定销售总定额 ,分解销售指标 ,搞好电力企业的经营是十分关键的。运用人工神经网络方法中的 BP算法 ,利用长春地区历年来销售电量的数据 ,建立起预测模型 ,并用 2 0 0 3年的实际值与预测值进行校验 ,证明了该方法较之传统的回归预测方法 。
In electricity market, the prediction of kW·h is very important for decision-makers. It is because that the prediction kW·h is the base of total vendition kW·h to be determined, and the base of decomposing the total vendition kW·h into small ones related to individual customers. In this paper, Changchun City, located at the northeast of People's Republic of China, is employed to be studied. Based on historical vendition kW·h data of the city and the theory of Back Propagation Artificial Neural Network, the forecasting model is deduced. Simulation results show that the forecasting precision of ANN is higher than that of regression approach.
出处
《湖南电力》
2004年第5期1-3,共3页
Hunan Electric Power
关键词
电力市场
销售电量
预测模型
ANN回归分析方法
electricity market
vendition kW·h
forecasting model
artificial neural network regression approach
