需求响应业务系统数据分析模型及应用

结合国内智能电网用户接口标准化现状,分析了用电侧的数据标准体系。在IEC PC 118的基础上扩展了支撑需求响应(demand response,DR)业务的信息交换接口及信息模型,以支撑DR执行效果的大数据评估方法的实现。从行业类属维度、时间维度、响应维度等方面分析了DR业务动态运行指标,通过在传统的数据关联分析方法中引入知识挖掘(knowledge discovery in database,KDD),构建了不同置信区间下的弱关联分析,为了降低系统的计算开销,在分析过程中采用剪枝技术以提高运算性能。最后,结合典型用能企业的负荷模型,对所提出的方法进行了验证,并实现了DR系统执行效果的潜在关键性因素分析,为未来智能电网用户侧能源管理、配网调度、第三方能源聚合商管理提供必要的技术支撑。

Data Analysis Model for Demand Response System and Its Application

According to the latest evolution of domestic smart grid user interface, this paper analyzes the information standardization of demand side data.The information exchange interface and information model are extended based on IEC PC 118 to support demand response (DR) business and realize the big data evaluation method for supporting DR implementation effect.We analyze the DR dynamic operating index from aspects of industry category dimension, time dimension, response dimensions, etc.Through introducing the knowledge discovery in database (KDD) discover in traditional data correlation analysis, we construct the weak association under different confidence intervals.Besides, in order to reduce the practical computation requirement, we adopt pruning techniques in analysis process to improve the running performance.Finally, we verify the proposed model through the load model of typical energy enterprises, and analyze the potential key factors of DR system implementation effect, which can provide the necessary technical support for the use-side energy management, distribution network scheduling and hird-party energy aggregator management of future smart grid.