基于大数据平台的电采暖用电量预测分析

Forecast and analysis of electric heating consumption based on big data platform

基于大数据平台,通过实时采集每一用户的传感器大量的采暖数据、用户行为数据以及天气数据和房屋数据,通过对数据的关联分析、针对采暖用电量的BP神经网络预测,研究用户的用电行为,进而深入研究用户端最佳的"煤改电"配套的节能环保方案。该研究对于降低用户采暖成本以及完善配电网建设和用户用电负荷配置提供数据支撑,在实际的"煤改电"工程中有显著意义。

This paper proposed a“coal-to-electricity”energy saving system,which collects a large amount of heating data,users′behavior data,weather data and houses′data of each user′s sensor in real time,and applies the BP(Back-Propagation Network)to analyze heating power consumption.The system could support data management and analysis easily,and could improve the distribution network construction and users′configurations,which has significant positive significance in the“coal-to-electricity”project.