摘要
用电量预测是电力系统调度、实时控制、运行计划和发展规划的前提,是电力部门最基本的决策信息。文章综合考虑经济状况、气候条件等影响用电量的因素,以湖北省历年的数据(包括GDP、产业结构、人口数量、环境平均温度)为基础,采用主成份分析和神经网络相结合的组合方法对湖北省用电量进行预测,预测精度较单一方法更高,可为该地区电力系统提供参考。
Electricity demand forecasting provides a premise for power system dispatching,real-time control,operation plan and development planning, and is the most basic information for decision-making of power department. This paper considers a variety of factors affecting electricity demand such as the economic situation and climatic conditions, based on historical data of Hubei province, including GDP, industrial structure, population size, mean environmental temperature, forecasts the electricity demand of Hubei province using combination method which combines principal component analysis with neural network. The prediction accuracy of the combination method is higher than a single method.
出处
《陕西电力》
2009年第10期49-53,共5页
Shanxi Electric Power
关键词
主成份分析
神经网络
用电量
预测
principal component analysis
neural network
electricity demand
forecasting
