{"title":"Segmentation of low voltage consumers for designing individualized pricing policies","authors":"M. Kotouza, Antonios C. Chrysopoulos, P. Mitkas","doi":"10.1109/EEM.2017.7981862","DOIUrl":null,"url":null,"abstract":"In recent years, the liberation of distribution and energy services has led towards competitive Energy Market environments. In these Markets, the participating suppliers need to provide more reliable services, specifically tailored to each customer or group of customers with similar needs. Thus, it is important to identify the consumer types in their portfolio, through Customer Load Profiling. In this paper, algorithms that provide robust and reliable clustering results are examined, as tools for meaningful Low Voltage consumers' segmentation. A number of experiments on two different data sets were implemented to provide an insight to the proposed attributes' input selection. Additionally, a set of custom pricing schemes was produced based on the segmentation results and the peak and cost reduction are estimated. The results are promising and enhance our understanding of the long-term gains that can be obtained by well-defined customer segmentation and the design of individualized pricing schemes.","PeriodicalId":416082,"journal":{"name":"2017 14th International Conference on the European Energy Market (EEM)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th International Conference on the European Energy Market (EEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EEM.2017.7981862","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Segmentation of low voltage consumers for designing individualized pricing policies
In recent years, the liberation of distribution and energy services has led towards competitive Energy Market environments. In these Markets, the participating suppliers need to provide more reliable services, specifically tailored to each customer or group of customers with similar needs. Thus, it is important to identify the consumer types in their portfolio, through Customer Load Profiling. In this paper, algorithms that provide robust and reliable clustering results are examined, as tools for meaningful Low Voltage consumers' segmentation. A number of experiments on two different data sets were implemented to provide an insight to the proposed attributes' input selection. Additionally, a set of custom pricing schemes was produced based on the segmentation results and the peak and cost reduction are estimated. The results are promising and enhance our understanding of the long-term gains that can be obtained by well-defined customer segmentation and the design of individualized pricing schemes.