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.

随着智能技术越来越多地融入电网，先进计量基础设施 (AMI) 带来的好处已经引起了配电公司的显着关注。 AMI 是一种用于客户电表和公用设施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可以提供实时的用电量数据，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。由于实际系统中的电表数量非常充足，SL&P 与其他公用事业公司类似，通过聚合配电服务的负载来创建虚拟电表数据变压器。尽管此过程有助于运营商轻松分析电网，但它牺牲了 AMI 提供的有价值的信息，并将其应用限制在计费过程中。这种重要的缺陷可以被认为是促使本研究项目进一步深入研究住宅负荷曲线建模并找到可以促进虚拟电表发展的方法的主要因素。萨斯喀彻温大学与SL&P合作的长期目标是找到一种新颖的框架，将客户细分和虚拟电表开发流程结合在一起，使最终结果不仅能够满足运营商的期望，而且能够形成激励其他人的前沿知识。研究人员重点关注这个问题。为了实现这一最终目标，触发参与赠款方面的合作的短期目标是：（i）评估当前用于建模住宅负荷概况的概率方法，并选择一种可以解决高波动性特征问题的方法。实际需要； (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框架。这项研究的成果预计将成为电力系统监测、运行和控制领域的里程碑，并有助于发展更可靠的电网。