智能电网环境下基于居民电力消费行为特征的需求响应策略研究

项目名称： 智能电网环境下基于居民电力消费行为特征的需求响应策略研究

项目编号： No.71501056

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 管理科学

项目作者： 周开乐

作者单位： 合肥工业大学

项目金额： 18.5万元

中文摘要： 利用价格信号或激励机制等需求响应策略，能够促使终端用户改变原有的一些电力消费行为，提高能源利用效率，促进电力供需平衡和节能减排等。智能电网中部署的智能电表和其它采集终端实时采集到大量居民用户的电力消费数据，从中能够挖掘不同类型居民用户群的电力消费行为特征，这对于制定更有效的差异化需求响应策略具有重要意义。因此，本项目主要研究：（1）大规模居民电力消费数据的预处理、聚类分析和结果评价方法，以发现具有相似电力消费行为特征的居民用户群，并挖掘不同类型用户群的电力消费行为特征；（2）居民电力消费行为与需求响应策略之间的相互作用机理，并对二者的动态关系和相互作用进行综合评价；（3）考虑不同类型居民用户群电力消费行为特征差异性的价格或激励需求响应策略及其评价方法。本项目的研究对于我国智能电网环境下促进电力供需平衡、增强电力系统可靠性、提高能源利用效率和实现节能减排目标等具有一定的理论意义与应用价值。

中文关键词： 居民电力消费；数据分析；行为特征；需求响应；决策支持

英文摘要： Demand response (DR) strategies mainly include dynamic pricing and incentive mechanisms. These DR strategies can promote the change of some normal electricity consumption behaviors of end users, improve the efficiency of energy use, and promote power supply and demand balance as well as energy saving and emission reduction. A large amount of residential electricity consumption data are collected in real-time by the smart meters and other data acquisition terminals deployed in the smart grid. Thus, the electricity consumption behavior characteristics of different residential user groups can be discovered from the data. This knowledge is of great significance for the formulation of more effective differentiated DR strategies. Therefore, the main research contents of this project are as follows. First, data preprocessing, clustering analysis and results evaluation methods of the large scale residential electricity consumption data are studied, so as to identify different groups of residential users that have similar electricity consumption patterns. Then the electricity consumption behavior characteristics of different kinds of residential users are discovered. Second, the interaction mechanisms of residential electricity consumption behaviors and DR strategies are explored. Then the dynamic relationship and the interaction of them are comprehensively evaluated. Third, considering the difference of electricity consumption behavior characteristics of different residential users, the corresponding price-based or incentive-based DR strategies and evaluation methods are designed. This research project has a certain theoretical significance and application value for the promotion of power supply and demand balance, the enhancement of power system reliability, the improvement of energy utilization efficiency, and the realization of energy saving and emission reduction targets in China’s smart grid environment.

英文关键词： Residential Electricity Consumption;Data Analysis;Behavior Characteristics;Demand Response;Decision Support