{"title":"An Intelligent Real-Time Renewables-Based Power Scheduling System for the Internet of Energy","authors":"Chenn-Jung Huang, Kai-Wen Hu, Yu-Kang Huang","doi":"10.1109/ICIVC.2018.8492903","DOIUrl":null,"url":null,"abstract":"Recently, the architecture of the Internet of Energy (IoE) has been proposed to replace the current smart grid in the future. However, the large volume of energy produced, the copious amounts of accompanying consumption data, and the uncertainties germane to intermittent energy sources will result in the real-time energy management of the IoE in the future being much more complicated than the energy management of traditional power generation systems. We thus propose a real-time power scheduling system to tackle these complex energy management problems. The whole power system is divided into different geographical regional grids under a hierarchical framework, and the scheduling process is activated at the regional grid if a power shortage is estimated to happen during a fixed time period ahead. The experimental results show that the proposed work can mitigate the dependency on traditional power plants effectively and balance peak and off-peak period loads in an electricity market.","PeriodicalId":173981,"journal":{"name":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","volume":"512 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIVC.2018.8492903","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
Recently, the architecture of the Internet of Energy (IoE) has been proposed to replace the current smart grid in the future. However, the large volume of energy produced, the copious amounts of accompanying consumption data, and the uncertainties germane to intermittent energy sources will result in the real-time energy management of the IoE in the future being much more complicated than the energy management of traditional power generation systems. We thus propose a real-time power scheduling system to tackle these complex energy management problems. The whole power system is divided into different geographical regional grids under a hierarchical framework, and the scheduling process is activated at the regional grid if a power shortage is estimated to happen during a fixed time period ahead. The experimental results show that the proposed work can mitigate the dependency on traditional power plants effectively and balance peak and off-peak period loads in an electricity market.