Stefany Yánez Rojas, Carlos Barrera-Singaña, Paul Muñoz Pilco, Darío Jaramillo Monje, Wilson Pavón
{"title":"Modelling of DC Power Equations Applied to State Estimation in High Renewable Penetration Power Systems","authors":"Stefany Yánez Rojas, Carlos Barrera-Singaña, Paul Muñoz Pilco, Darío Jaramillo Monje, Wilson Pavón","doi":"10.1109/GlobConHT56829.2023.10087445","DOIUrl":null,"url":null,"abstract":"Growth in power systems has led to an increase in operational complexity, highlighting the importance of maintaining them in optimal conditions. State estimation in electric power systems is a crucial tool for determining the state of transmission networks through the use of sensors and topology information. This information is then utilized for contingency analysis and error detection/identification to ensure system reliability. To maintain optimal power system operations, state estimation and its associated techniques are critical components. This work focuses on analyzing DC state estimation using a statistical method and weighted least squares methodology. Anomalous measurements are filtered and corrected using Chi-Square. The algorithm was developed in MATLAB and verified in DIgSILENT PowerFactory. The IEEE 14-bus system, with added wind turbines, was used as a test system to determine security in the power grid through estimator confidence parameters. The results provide valuable insights into the efficacy of the DC state estimation process.","PeriodicalId":355921,"journal":{"name":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE IAS Global Conference on Renewable Energy and Hydrogen Technologies (GlobConHT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobConHT56829.2023.10087445","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Growth in power systems has led to an increase in operational complexity, highlighting the importance of maintaining them in optimal conditions. State estimation in electric power systems is a crucial tool for determining the state of transmission networks through the use of sensors and topology information. This information is then utilized for contingency analysis and error detection/identification to ensure system reliability. To maintain optimal power system operations, state estimation and its associated techniques are critical components. This work focuses on analyzing DC state estimation using a statistical method and weighted least squares methodology. Anomalous measurements are filtered and corrected using Chi-Square. The algorithm was developed in MATLAB and verified in DIgSILENT PowerFactory. The IEEE 14-bus system, with added wind turbines, was used as a test system to determine security in the power grid through estimator confidence parameters. The results provide valuable insights into the efficacy of the DC state estimation process.