{"title":"基于保护的分布式发电渗透限值的推荐和价值评估系统的应用综述","authors":"E. Nxumalo, K. Awodele","doi":"10.1109/SAUPEC/RobMech/PRASA48453.2020.9041048","DOIUrl":null,"url":null,"abstract":"The rise of disruptive technologies and the rapid growth of innovative initiatives has led to a trend of decentralization, deregulation, and distribution of regulated/centralized services. As a result, there is an increasing number of distributed generator connection requests in the distribution networks and the need for Power utilities to quickly assess the impact of distributed generators (DGs) to keep up with these requests. Grid integration of DGs brings about protection issues: current protection systems were not designed for bidirectional power flow, thus the protective devices in the network lose their ability to perform their main functions. To mitigate the impact of Distributed Generation (DG), there are standards and policies that constrain the number of DGs that can be connected to the distribution network. The problem with these limits is that they are based only on overload and overvoltage, and do not adequately define the DG size/threshold before the occurrence of a protection issue. In addition, a load study for the area of connection still needs to be conducted and depending on the location, it takes time. In this paper, a study of the use of recommendation & value estimation systems to determine Protection based penetration limits and an opportunity network will be reviewed. These investigations are performed on Jupyter notebook (anaconda3).","PeriodicalId":215514,"journal":{"name":"2020 International SAUPEC/RobMech/PRASA Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Review on the Use of Recommendation and Value Estimation Systems to Determine Protection Based Distributed Generation Penetration Limits\",\"authors\":\"E. Nxumalo, K. Awodele\",\"doi\":\"10.1109/SAUPEC/RobMech/PRASA48453.2020.9041048\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rise of disruptive technologies and the rapid growth of innovative initiatives has led to a trend of decentralization, deregulation, and distribution of regulated/centralized services. As a result, there is an increasing number of distributed generator connection requests in the distribution networks and the need for Power utilities to quickly assess the impact of distributed generators (DGs) to keep up with these requests. Grid integration of DGs brings about protection issues: current protection systems were not designed for bidirectional power flow, thus the protective devices in the network lose their ability to perform their main functions. To mitigate the impact of Distributed Generation (DG), there are standards and policies that constrain the number of DGs that can be connected to the distribution network. The problem with these limits is that they are based only on overload and overvoltage, and do not adequately define the DG size/threshold before the occurrence of a protection issue. In addition, a load study for the area of connection still needs to be conducted and depending on the location, it takes time. In this paper, a study of the use of recommendation & value estimation systems to determine Protection based penetration limits and an opportunity network will be reviewed. These investigations are performed on Jupyter notebook (anaconda3).\",\"PeriodicalId\":215514,\"journal\":{\"name\":\"2020 International SAUPEC/RobMech/PRASA Conference\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International SAUPEC/RobMech/PRASA Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041048\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International SAUPEC/RobMech/PRASA Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAUPEC/RobMech/PRASA48453.2020.9041048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Review on the Use of Recommendation and Value Estimation Systems to Determine Protection Based Distributed Generation Penetration Limits
The rise of disruptive technologies and the rapid growth of innovative initiatives has led to a trend of decentralization, deregulation, and distribution of regulated/centralized services. As a result, there is an increasing number of distributed generator connection requests in the distribution networks and the need for Power utilities to quickly assess the impact of distributed generators (DGs) to keep up with these requests. Grid integration of DGs brings about protection issues: current protection systems were not designed for bidirectional power flow, thus the protective devices in the network lose their ability to perform their main functions. To mitigate the impact of Distributed Generation (DG), there are standards and policies that constrain the number of DGs that can be connected to the distribution network. The problem with these limits is that they are based only on overload and overvoltage, and do not adequately define the DG size/threshold before the occurrence of a protection issue. In addition, a load study for the area of connection still needs to be conducted and depending on the location, it takes time. In this paper, a study of the use of recommendation & value estimation systems to determine Protection based penetration limits and an opportunity network will be reviewed. These investigations are performed on Jupyter notebook (anaconda3).