CUSTOMER SEGMENTATION AND VIRTUAL METER DEVELOPMENT BASED ON PROBABILISTIC MODELING OF RESIDENTIAL LOAD PROFILES THROUGH AMI

通过 AMI 对住宅负荷曲线进行概率建模的客户细分和虚拟仪表开发

• 批准号: 521306-2017
• 负责人: Chung, ChiYung
• 金额: $ 1.82万
• 依托单位: University of Saskatchewan
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640651
• 关键词: CUSTOMER; SEGMENTATION; VIRTUAL; METER; DEVELOPMENT

Along with the growing inclusion of smart technologies into the electrical power grids, benefits, which can beoriginated from advanced metering infrastructure (AMI), have grabbed noticeable attention from distributionutilities. AMI is an architecture for automated, two-way communication between customers' meters and theutility; from the utility company point of view, AMI can provide real-time data of power consumption whichcan be efficiently used for several tasks such as network monitoring. Saskatoon Light & Power (SL&P) whichis a distribution utility in Saskatchewan has been operating the AMI system since July 2016. As the number ofmeters are severely ample in practical systems, SL&P, similar to other utilities, creates virtual meter data byaggregating loads served by distribution transformers. Although this process helps the operators to analyze thegrid with ease, it sacrifices valuable information provided by the AMI and confines their applications to thebilling process. Such an important deficiency can be considered as the main factor which motivates thisresearch program to delve more into the residential load profile modeling and find approaches which can yieldto the enhanced development of virtual meters. The long-term goal of collaboration between University ofSaskatchewan and SL&P is to find a novel framework that combines customer segmentation and virtual meterdevelopment processes together so that the end result not only can meet the operators expectations, but also canform a cutting-edge knowledge motivating other researchers to focus on this problem. To achieve this ultimategoal, the short-term goals which triggers starting a collaboration in terms of an engage grant are: (i) to assesscurrent probabilistic methods for modeling residential load profiles and select a method which can address theissue of highly volatile characteristics with respect to the practical needs; and (ii) to develop a framework forcustomer segmentation and virtual meter development based on both machine learning techniques and theprobabilistic modeling conducted in (i). The outcomes of this research are expected to constitute milestones inpower system monitoring, operation and control, and contribute to the development of a more reliable grid.

沿着智能技术越来越多地应用于电网，先进计量基础设施（AMI）带来的好处引起了配电公用事业公司的注意。AMI是一种用于客户仪表和公用事业之间自动化双向通信的架构;从公用事业公司的角度来看，AMI可以提供实时的功耗数据，这些数据可以有效地用于网络监控等多项任务。萨斯卡通电力公司（SL&P）是萨斯喀彻温省的一家配电公司，自2016年7月以来一直在运营AMI系统。由于在实际系统中电表的数量非常充足，SL&P类似于其他公用事业，通过聚合配电变压器所服务的负载来创建虚拟电表数据。虽然这一过程有助于运营商轻松分析电网，但它牺牲了AMI提供的宝贵信息，并将其应用限制在计费过程中。这样一个重要的不足可以被认为是主要因素，促使本研究计划深入到住宅负荷曲线建模，并找到方法，可以yieldto虚拟电表的增强发展。萨斯喀彻温大学和SL&P之间合作的长期目标是找到一个新的框架，将客户细分和虚拟电表开发过程结合在一起，使最终结果不仅可以满足运营商的期望，而且还可以形成一个尖端的知识，激励其他研究人员关注这个问题。为了实现这一最终目标，触发在参与补助金方面开始合作的短期目标是：（i）评估当前用于建模住宅负荷分布的概率方法，并选择能够针对实际需要解决高度波动特性问题的方法;以及（ii）基于机器学习技术和（i）中进行的概率建模，开发客户细分和虚拟电表开发的框架。这项研究的成果有望成为电力系统监测、运行和控制的里程碑，并有助于发展更可靠的电网。