Tumininu Lawanson, Roozbeh Karandeh, V. Cecchi, Z. Wartell, Isaac Cho
{"title":"Improving Power Distribution System Situational Awareness Using Visual Analytics","authors":"Tumininu Lawanson, Roozbeh Karandeh, V. Cecchi, Z. Wartell, Isaac Cho","doi":"10.1109/SECON.2018.8479204","DOIUrl":null,"url":null,"abstract":"Traditionally, distribution system operators had limited visibility beyond distribution system substations. It was not unusual for electric utilities to have insufficient information about the network and phase connectivity model for the distribution system. This resulted in limited situational awareness at the distribution system level. In this paper, a visual analytics approach to gleaning intelligence from the vast amounts of data accumulated in the distribution system is proposed. The web-based visual analytics interface integrates data from heterogeneous datasets such as AMI, GIS and SCADA. The interface is designed to enable distribution system operators visualize and analyze the state of the distribution system over time. This paper presents the use of the visual analytics system to identify mismatched meter-to-transformer associations and to visualize voltage violations in a real-world distribution network.","PeriodicalId":102076,"journal":{"name":"SoutheastCon 2018","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoutheastCon 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2018.8479204","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Traditionally, distribution system operators had limited visibility beyond distribution system substations. It was not unusual for electric utilities to have insufficient information about the network and phase connectivity model for the distribution system. This resulted in limited situational awareness at the distribution system level. In this paper, a visual analytics approach to gleaning intelligence from the vast amounts of data accumulated in the distribution system is proposed. The web-based visual analytics interface integrates data from heterogeneous datasets such as AMI, GIS and SCADA. The interface is designed to enable distribution system operators visualize and analyze the state of the distribution system over time. This paper presents the use of the visual analytics system to identify mismatched meter-to-transformer associations and to visualize voltage violations in a real-world distribution network.