基于ARIMA-GM组合模型的湖北省电力需求预测研究  

Research on the Forecasting of Electric Power Demand in Hubei Province Based on ARIMA-GM Model

作　　者：王莉琳[1] 张维[1] 赖敏[1] 向铁元[2] 杨再鹤[2] 周波[2] 

机构地区：[1]湖北省电力公司电力经济技术研究院,武汉430072 [2]武汉大学电气工程学院,武汉430072

出　　处：《中国农村水利水电》2013年第4期101-105,共5页China Rural Water and Hydropower

摘　　要：通过分析湖北省历年电力消费量,利用灰色模型(GM)和自回归积分移动平均(ARIMA)模型分别对2012-2020期间的湖北省电力需求量进行了预测,然后通过方差倒数法进行组合预测,得到了精度更高的预测结果。通过分析整个预测过程及结果,该方法易于操作,精度较高,是一种对电力需求预测方法有益的探索。The objective of this paper is to forecast the power electric demand in Hubei Province from 2010 to 2020 by an analysis of power consumption in the past years. Based on the results of gray model（GM） and auto-regressive integrated moving average model （ARIMA） on 2010-2020 prediction of power demand, a new combination model built by the method of Variance Reciprocal Weighting is represented to forecast and analyze Hubei Provincial electricity demands. This combination model can be more precise and easily implemented, which is a useful exploration about electric power demand forecasting.

关 键 词：时间序列 灰色模型 自回归积分移动平均模型 方差倒数法 

分 类 号：TM715[电气工程—电力系统及自动化]