Shanzah Naseem, I. Butt, Sadiq Ahmad, Abdullah Shoukat
{"title":"Islanding Detection in Distributed Microgrid using Quadrature Demodulation","authors":"Shanzah Naseem, I. Butt, Sadiq Ahmad, Abdullah Shoukat","doi":"10.1109/ICT-PEP57242.2022.9988927","DOIUrl":null,"url":null,"abstract":"In grid-connected distributed generating (DG) systems, islanding has become a severe problem. Emerging energy production into the current power system has produced a variety of difficulties, the most significant of which is fast and efficient islanding detection to minimize damage to equipment, system security interference, and safety threats. Whenever a microgrid system is deployed, it is completely disconnected from the main grid. Several strategies have been developed in recent research publications to identify the islanding situation, which is classified as active, passive, or hybrid. In this work, the variation in the autocorrelation function of a modal current envelope (VAMCE) approach is utilized to identify the islanding scenario rapidly and precisely. The approach first transforms the three-phase current signal into a modal current signal and then calculates the envelope using a quadrature demodulation method. Finally, the suggested methodology used a VAMCE technique to discriminate among islanding and non-islanding circumstances. The VAMCE methodology changes insignificantly under normal settings, but it differs widely during islanding scenarios, making this approach more beneficial for islanding detection. This approach is examined using many simulations with parameters like active and reactive power in normal and islanded condition. According to the simulation findings, the suggested methodology is more accurate and can be finished in a reasonable timeframe than the previous methods. The recognition performance in terms of time is only 0.4s, also the NDZ is very minor.","PeriodicalId":163424,"journal":{"name":"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Technology and Policy in Energy and Electric Power (ICT-PEP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICT-PEP57242.2022.9988927","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
In grid-connected distributed generating (DG) systems, islanding has become a severe problem. Emerging energy production into the current power system has produced a variety of difficulties, the most significant of which is fast and efficient islanding detection to minimize damage to equipment, system security interference, and safety threats. Whenever a microgrid system is deployed, it is completely disconnected from the main grid. Several strategies have been developed in recent research publications to identify the islanding situation, which is classified as active, passive, or hybrid. In this work, the variation in the autocorrelation function of a modal current envelope (VAMCE) approach is utilized to identify the islanding scenario rapidly and precisely. The approach first transforms the three-phase current signal into a modal current signal and then calculates the envelope using a quadrature demodulation method. Finally, the suggested methodology used a VAMCE technique to discriminate among islanding and non-islanding circumstances. The VAMCE methodology changes insignificantly under normal settings, but it differs widely during islanding scenarios, making this approach more beneficial for islanding detection. This approach is examined using many simulations with parameters like active and reactive power in normal and islanded condition. According to the simulation findings, the suggested methodology is more accurate and can be finished in a reasonable timeframe than the previous methods. The recognition performance in terms of time is only 0.4s, also the NDZ is very minor.