基于时间序列的月度用电量预测算法研究

Research on Monthly Electricity Consumption Forecasting Algorithm Based on Time Series

文章在调研用电量预测需求以及意义基础上,充分研究国内外典型用电量预测模型算法,通过多种算法比较选型,提出基于大数据挖掘技术的用电量预测算法模型,将用电量分为趋势、季节、残差等三个部分,运用ARIMA模型实现用电量精准预测,对电网资金规划、财务预算管理决策和需求侧响应分析具有重要的指导意义。

Based on the investigation of the demand and signifi cance of electricity consumption forecast,this paper fully studies the algorithms of typical electricity consumption prediction models at home and abroad,and puts forward the electricity consumption prediction algorithm model based on big data mining technology through the comparison and selection of various algorithms.The power consumption is divided into three parts:trend,quarterly savings and residual error.ARIMA model is used to realize accurate prediction of power consumption,and the power grid funds are estimated accurately Planning,fi nancial budget management decision and demand side response analysis have important guiding signifi cance.