{"title":"Automatic Power System Restoration With Inrush Current Estimation For Industrial Facility","authors":"Anusha Papasani, Kaynat Zia, Weijen Lee","doi":"10.1109/ICPS51807.2021.9416636","DOIUrl":null,"url":null,"abstract":"The power system industry often operates close to its limits to accommodate the increased demand posing a high risk of blackouts. Power system restoration techniques are utilized post breakout focusing on load pickup and speedy recovery. In traditional heuristic methods, the load is considered to be constant after it is picked. However, from a system operation point of view, the load varies once picked up. This is commonly observed in industrial loads. In Industrial systems, loads, which involve many induction motors. The high starting currents of the induction motors leads to voltage sags that may affect variable speed drives and cause contactors to drop out. If the load variation and inrush currents are not considered, load will be significantly underestimated at the time of pickup which might lead to a system re-collapse. Besides, one may have to prioritize the loads to help the operator during restoration. An automatic power system restoration tool is developed using graph theory to provide an efficient restoration path and considers the priority of loads, Cold load pickup, Inrush currents, and load variation after picking up for a smooth and successful restoration process. Evolution of smart grid, the Intelligent Electronic Device (IED) has been deployed throughout the power system network for monitoring and control. Therefore, this paper takes advantages on the availability of IEDs to report the loads right before the blackout and the real-time load during the restoration. The industrial system is used as a test case to demonstrate the effectiveness of the proposed methodology.","PeriodicalId":350508,"journal":{"name":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE/IAS 57th Industrial and Commercial Power Systems Technical Conference (I&CPS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPS51807.2021.9416636","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The power system industry often operates close to its limits to accommodate the increased demand posing a high risk of blackouts. Power system restoration techniques are utilized post breakout focusing on load pickup and speedy recovery. In traditional heuristic methods, the load is considered to be constant after it is picked. However, from a system operation point of view, the load varies once picked up. This is commonly observed in industrial loads. In Industrial systems, loads, which involve many induction motors. The high starting currents of the induction motors leads to voltage sags that may affect variable speed drives and cause contactors to drop out. If the load variation and inrush currents are not considered, load will be significantly underestimated at the time of pickup which might lead to a system re-collapse. Besides, one may have to prioritize the loads to help the operator during restoration. An automatic power system restoration tool is developed using graph theory to provide an efficient restoration path and considers the priority of loads, Cold load pickup, Inrush currents, and load variation after picking up for a smooth and successful restoration process. Evolution of smart grid, the Intelligent Electronic Device (IED) has been deployed throughout the power system network for monitoring and control. Therefore, this paper takes advantages on the availability of IEDs to report the loads right before the blackout and the real-time load during the restoration. The industrial system is used as a test case to demonstrate the effectiveness of the proposed methodology.