{"title":"智能电表在电网改造中的应用及配电网潮流数据的可靠性","authors":"Sindi Ndaba, I. Davidson","doi":"10.1109/PowerAfrica49420.2020.9219916","DOIUrl":null,"url":null,"abstract":"High electrical power loss is of concern in South Africa and it is an issue that many power utilities around the world encounter. Technical and non-technical losses are the contributing factors of electrical power losses. Technical losses are regarded as the electrical system losses which are caused by network impedance, current flows, and auxiliary supplies. Electricity thefts, measurement system errors and non-payments of bills are the contributing factors to non-technical losses which resulted in revenue loss increasing every year in Eskom. The smart grid with smart meters implemented promises to be an effectively integrated technology to address the issue of non-technical losses. To analyze the effectiveness of smart prepaid split meters implementation on Eskom distribution networks, a quantitative random sample assessment of 334 respondents was evaluated using a self-administered questionnaire. The collected data was analyzed with Statistical Package for the Social Sciences software (SPSS) version 26.0 and Microsoft Excel 2016 version to achieve multi-objective decision-making for smart prepaid split metering effectiveness for both utility and customer satisfaction. The different inferential statistics techniques used include regression, correlations, multifactor analysis (MFA), and chi-square goodness of fit test to interpret the p-values, identify the change-point, detect the trend and to correlated best fit time series for decision making. The findings showed that smart metering usage as emerging technology has offer multiple benefits to utilities and provide a possible long-term solution to many of the power-related problems utilities face.","PeriodicalId":325937,"journal":{"name":"2020 IEEE PES/IAS PowerAfrica","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Implementation of Smart Meters for Electric Grid Improvements and Reliable Power Flow Data on Electrical Power Distribution Network\",\"authors\":\"Sindi Ndaba, I. Davidson\",\"doi\":\"10.1109/PowerAfrica49420.2020.9219916\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"High electrical power loss is of concern in South Africa and it is an issue that many power utilities around the world encounter. Technical and non-technical losses are the contributing factors of electrical power losses. Technical losses are regarded as the electrical system losses which are caused by network impedance, current flows, and auxiliary supplies. Electricity thefts, measurement system errors and non-payments of bills are the contributing factors to non-technical losses which resulted in revenue loss increasing every year in Eskom. The smart grid with smart meters implemented promises to be an effectively integrated technology to address the issue of non-technical losses. To analyze the effectiveness of smart prepaid split meters implementation on Eskom distribution networks, a quantitative random sample assessment of 334 respondents was evaluated using a self-administered questionnaire. The collected data was analyzed with Statistical Package for the Social Sciences software (SPSS) version 26.0 and Microsoft Excel 2016 version to achieve multi-objective decision-making for smart prepaid split metering effectiveness for both utility and customer satisfaction. The different inferential statistics techniques used include regression, correlations, multifactor analysis (MFA), and chi-square goodness of fit test to interpret the p-values, identify the change-point, detect the trend and to correlated best fit time series for decision making. The findings showed that smart metering usage as emerging technology has offer multiple benefits to utilities and provide a possible long-term solution to many of the power-related problems utilities face.\",\"PeriodicalId\":325937,\"journal\":{\"name\":\"2020 IEEE PES/IAS PowerAfrica\",\"volume\":\"56 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE PES/IAS PowerAfrica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PowerAfrica49420.2020.9219916\",\"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 IEEE PES/IAS PowerAfrica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PowerAfrica49420.2020.9219916","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Implementation of Smart Meters for Electric Grid Improvements and Reliable Power Flow Data on Electrical Power Distribution Network
High electrical power loss is of concern in South Africa and it is an issue that many power utilities around the world encounter. Technical and non-technical losses are the contributing factors of electrical power losses. Technical losses are regarded as the electrical system losses which are caused by network impedance, current flows, and auxiliary supplies. Electricity thefts, measurement system errors and non-payments of bills are the contributing factors to non-technical losses which resulted in revenue loss increasing every year in Eskom. The smart grid with smart meters implemented promises to be an effectively integrated technology to address the issue of non-technical losses. To analyze the effectiveness of smart prepaid split meters implementation on Eskom distribution networks, a quantitative random sample assessment of 334 respondents was evaluated using a self-administered questionnaire. The collected data was analyzed with Statistical Package for the Social Sciences software (SPSS) version 26.0 and Microsoft Excel 2016 version to achieve multi-objective decision-making for smart prepaid split metering effectiveness for both utility and customer satisfaction. The different inferential statistics techniques used include regression, correlations, multifactor analysis (MFA), and chi-square goodness of fit test to interpret the p-values, identify the change-point, detect the trend and to correlated best fit time series for decision making. The findings showed that smart metering usage as emerging technology has offer multiple benefits to utilities and provide a possible long-term solution to many of the power-related problems utilities face.