Toomas Erik Anijärv, Noman Shabbir, L. Kütt, M. N. Iqbal
{"title":"Requirements to Data Acquisition and Signal Analysis for Electrical Grid Condition Monitoring","authors":"Toomas Erik Anijärv, Noman Shabbir, L. Kütt, M. N. Iqbal","doi":"10.1109/RTUCON51174.2020.9316487","DOIUrl":null,"url":null,"abstract":"Electrical outages cause economical loss but in many cases lead also to broken devices. Similarly, repeated voltage fluctuation may result in overstress of the components of the grid which leads to electrical failure. Before any electrical fault, usually, some smaller-scale anomalies occur in load current or voltage. These anomalies can usually be detected from measured quantities by using the Fourier transform and by analyzing voltage changes indicated as additional frequency components. However, the noise present in the real signal makes this analysis less accurate. Therefore, a wavelet transform based denoising method is proposed here along with Fourier transform to overcome this problem. In this paper, a discussion on the options for real-time diagnostics of an electrical grid is presented. The methods are compared and analyzed to assess the reliability of the proposed method. The anomalies observed are linked to unexpected voltage RMS values which correspond to variations in frequency domain components.","PeriodicalId":332414,"journal":{"name":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 61th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTUCON51174.2020.9316487","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Electrical outages cause economical loss but in many cases lead also to broken devices. Similarly, repeated voltage fluctuation may result in overstress of the components of the grid which leads to electrical failure. Before any electrical fault, usually, some smaller-scale anomalies occur in load current or voltage. These anomalies can usually be detected from measured quantities by using the Fourier transform and by analyzing voltage changes indicated as additional frequency components. However, the noise present in the real signal makes this analysis less accurate. Therefore, a wavelet transform based denoising method is proposed here along with Fourier transform to overcome this problem. In this paper, a discussion on the options for real-time diagnostics of an electrical grid is presented. The methods are compared and analyzed to assess the reliability of the proposed method. The anomalies observed are linked to unexpected voltage RMS values which correspond to variations in frequency domain components.