Pirmin Held, Daniel Weißhaar, S. Mauch, D. Abdeslam, Dirk Benyoucef
{"title":"Parameter Optimized Event Detection for NILM Using Frequency Invariant Transformation of Periodic Signals (FIT-PS)","authors":"Pirmin Held, Daniel Weißhaar, S. Mauch, D. Abdeslam, Dirk Benyoucef","doi":"10.1109/ETFA.2018.8502522","DOIUrl":null,"url":null,"abstract":"This paper describes the optimization of parameters of an event detection method for Non-Intrusive Load Monitoring (NILM). The input signal consisting of voltage and current was processed with FIT-PS. An event detection method is presented with regard to the adjustable parameters. For parameter optimization the methods simulated annealing and pattern search are used. By using automatic parameter optimization methods, previous results based on manually selected parameters can be significantly improved up to 11.5 %. In the runtime investigation, pattern search has clear advantages over simulated annealing for comparable or better results. In addition, it is possible in the future to adapt this method very quickly to other boundary conditions.","PeriodicalId":6566,"journal":{"name":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","volume":"13 1","pages":"832-837"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETFA.2018.8502522","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
This paper describes the optimization of parameters of an event detection method for Non-Intrusive Load Monitoring (NILM). The input signal consisting of voltage and current was processed with FIT-PS. An event detection method is presented with regard to the adjustable parameters. For parameter optimization the methods simulated annealing and pattern search are used. By using automatic parameter optimization methods, previous results based on manually selected parameters can be significantly improved up to 11.5 %. In the runtime investigation, pattern search has clear advantages over simulated annealing for comparable or better results. In addition, it is possible in the future to adapt this method very quickly to other boundary conditions.