{"title":"Energy quality optimization in smart grids Faults monitoring by the space vector signature analysis method","authors":"Youssef Ait El Kadi, F. Baghli, Yassine Lakhal","doi":"10.1109/ICOA49421.2020.9094451","DOIUrl":null,"url":null,"abstract":"The research work presented in this paper focuses on energy quality monitoring in the smart grids. Optimizing the quality of power is the greatest challenges of this grids, it is currently a subject with a great interest for the following two reasons: The massive use of equipment generating disturbances and themselves sensitive to these disturbances, the integration more and more of intermittent renewable energy sources and the development of decentralized production station. The improvement of electrical energy quality is characterized by two main focus of research: prophylactic and curative solutions on the one side and monitoring of faults on the other, i.e. measurement and analysis of electrical disturbances. The monitoring represents the preliminary step to search for solutions; it helps to understand the origin of the disturbances, to assess their impact on different devices, and therefore to choose the most appropriate economical and technical solution. The aim of this study is to apply an analysis technique of the signature of the space vector in order to evaluate and to treat the problems of the quality of all energy exchanged between the producer and the consumer through the smart grids. The obtained results prove the efficiency of the used method to ensure a fast and automatic analysis of voltage magnitude, voltage drop, overvoltage and harmonic distortion faults. The use of the space vector signature analysis technique to optimize the energy quality in smart grids allows to identify the types of disturbances, to classify them precisely and to evaluate their severity, real-time measurement and a control using the minimum of variables.","PeriodicalId":253361,"journal":{"name":"2020 IEEE 6th International Conference on Optimization and Applications (ICOA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 6th International Conference on Optimization and Applications (ICOA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOA49421.2020.9094451","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
The research work presented in this paper focuses on energy quality monitoring in the smart grids. Optimizing the quality of power is the greatest challenges of this grids, it is currently a subject with a great interest for the following two reasons: The massive use of equipment generating disturbances and themselves sensitive to these disturbances, the integration more and more of intermittent renewable energy sources and the development of decentralized production station. The improvement of electrical energy quality is characterized by two main focus of research: prophylactic and curative solutions on the one side and monitoring of faults on the other, i.e. measurement and analysis of electrical disturbances. The monitoring represents the preliminary step to search for solutions; it helps to understand the origin of the disturbances, to assess their impact on different devices, and therefore to choose the most appropriate economical and technical solution. The aim of this study is to apply an analysis technique of the signature of the space vector in order to evaluate and to treat the problems of the quality of all energy exchanged between the producer and the consumer through the smart grids. The obtained results prove the efficiency of the used method to ensure a fast and automatic analysis of voltage magnitude, voltage drop, overvoltage and harmonic distortion faults. The use of the space vector signature analysis technique to optimize the energy quality in smart grids allows to identify the types of disturbances, to classify them precisely and to evaluate their severity, real-time measurement and a control using the minimum of variables.