基于协同过滤算法的电能替代潜力用户挖掘模型研究

Research on Potential User Mining Model of Power Substitution Based on Collaborative Filtering Algorithm

电能等清洁能源的利用有助于推进节能减排工作,优化企业用能结构,提升能源利用效率。试图挖掘提炼客户采集点负荷数据,按不同行业的能源结构、设备类型信息分别分析其负荷特征,并通过K-means算法对已完成电能替代改造的用户进行聚类,运用协同过滤算法构建电能替代潜力用户识别模型,实现对电能替代潜力企业的精准定位,提升电能替代项目的发掘效率。

The use of clean energy such as electricity will promote the development of energy conservation and emission reduction, and improve the energy utilization efficiency and the energy structure optimization in china. This paper attempts to explore and refine customers load data. According to the energy structure of industries and the equipment types, the load characteristics are analyzed. The K-means algorithm is used to cluster the users who have completed the power replacement. The collaborative filtering algorithm is applied to build the user identification model substituting for electric potential identification model, so as to realize the precise location of potential power substitution enterprises and enhance the mining efficiency of power energy substitution project.