U. Hilleringmann, D. Petrov, Ibrahim Mwammenywa, Geoffrey Mark Kagarura
{"title":"Local Power Control using Wireless Sensor System for Microgrids in Africa","authors":"U. Hilleringmann, D. Petrov, Ibrahim Mwammenywa, Geoffrey Mark Kagarura","doi":"10.1109/africon51333.2021.9570970","DOIUrl":null,"url":null,"abstract":"Photovoltaic microgrids in Sub-Saharan Africa (SSA) suffer from limited voltage stability and frequent blackouts caused by power generation/consumer load mismatch. To improve the reliability of the microgrids, a wireless sensor network for distributed load monitoring in combination with solar irradiation forecasts based on weather data are proposed. Implementing both, local load surveillance and weather prognosis, will considerably improve the overall network stability as this combination enables specific tailored countermeasures just in time. The proposed system further allows the implementation of a cost-effective time-based tariff management to support a better uniformity of the load during daytime.","PeriodicalId":170342,"journal":{"name":"2021 IEEE AFRICON","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE AFRICON","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/africon51333.2021.9570970","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
Photovoltaic microgrids in Sub-Saharan Africa (SSA) suffer from limited voltage stability and frequent blackouts caused by power generation/consumer load mismatch. To improve the reliability of the microgrids, a wireless sensor network for distributed load monitoring in combination with solar irradiation forecasts based on weather data are proposed. Implementing both, local load surveillance and weather prognosis, will considerably improve the overall network stability as this combination enables specific tailored countermeasures just in time. The proposed system further allows the implementation of a cost-effective time-based tariff management to support a better uniformity of the load during daytime.
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