{"title":"Geometric numeric integration in the event-driven measurement method","authors":"M. Simonov","doi":"10.1109/EBCCSP.2016.7605247","DOIUrl":null,"url":null,"abstract":"The Event-Driven Metering (EDM) method is about data-driven compression of the measurement data based on the replacement of the original arbitrary shape of the load by a simplified polygonal line that represents the same values of the energy per interval of time. EDM algorithm receives the Shannon data samples encoding the local measurements and reports the pre-processed knowledge to the controlling hosts in the form of Lebesgue-based events. This article explains the mathematical foundations of the invention that allows improved data efficiency. Method decomposes the global behavior of an energy system in a sequence of linearized chunks and exploits the energy conservation law in order to set up data-driven geometric integration. The result is an operator that maps a load shape into a data-efficient sequence of tokens representing exactly the same energy quantities as in the original pattern.","PeriodicalId":411767,"journal":{"name":"2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Second International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EBCCSP.2016.7605247","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The Event-Driven Metering (EDM) method is about data-driven compression of the measurement data based on the replacement of the original arbitrary shape of the load by a simplified polygonal line that represents the same values of the energy per interval of time. EDM algorithm receives the Shannon data samples encoding the local measurements and reports the pre-processed knowledge to the controlling hosts in the form of Lebesgue-based events. This article explains the mathematical foundations of the invention that allows improved data efficiency. Method decomposes the global behavior of an energy system in a sequence of linearized chunks and exploits the energy conservation law in order to set up data-driven geometric integration. The result is an operator that maps a load shape into a data-efficient sequence of tokens representing exactly the same energy quantities as in the original pattern.