基于机器学习的电能替代用户特征分析技术研究

Research on User Feature Analysis Technology for Electricity Substitution Based on Machine Learning

探讨电能替代用户特征分析的技术与应用,以促进电能替代的可持续发展和应用。分析影响电能替代潜力的各种因素,建立对应的评估模型;采用K-means均值分类算法和多层感知机算法,实现了企业电能替代潜力评估和用户行业分类,提升企业电能替代工作的专业化和信息化水平;使用成对分析法和模糊综合评价体系构建电能替代效益评价模型。结果表明,电能替代在外部环境、电网公司盈利和社会贡献上的表现不错,综合评价级别为“较好”,带来的技术经济环境效益比较可观。

Explore the technology and application of analyzing the characteristics of electricity substitution users to promote the sustainable development and application of electricity substitution.Analyze various factors that affect the potential for electricity substitution and establish corresponding evaluation models.By using the K-means mean classification algorithm and multi-layer perceptron algorithm,the potential assessment of enterprise electricity substitution and user industry classification have been achieved,enhancing the professionalism and informatization level of enterprise electricity substitution work.Construct an electricity substitution benefit evaluation model using paired analysis method and fuzzy comprehensive evaluation system.The results indicate that electricity substitution has performed well in the external environment,profitability of power grid companies,and social contribution,with a comprehensive evaluation level of"good",and has brought considerable technological and economic environmental benefits.