A. C. Rueda-Medina, J. A. Domínguez-Navarro, A. Padilha-Feltrin
{"title":"Reactive power support pricing of Distributed Generators with primary energy source uncertainty","authors":"A. C. Rueda-Medina, J. A. Domínguez-Navarro, A. Padilha-Feltrin","doi":"10.1109/TDC-LA.2010.5762868","DOIUrl":null,"url":null,"abstract":"In this paper, a novel methodology to price the reactive power support ancillary service of Distributed Generators (DGs) with primary energy source uncertainty is shown. The proposed methodology provides the service pricing based on the Loss of Opportunity Costs (LOC) calculation. An algorithm is proposed to reduce the uncertainty present in these generators using Multiobjective Power Flows (MOPFs) implemented in multiple probabilistic scenarios through Monte Carlo Simulations (MCS), and modeling the time series associated with the generation of active power from DGs through Markov Chains (MC).","PeriodicalId":222318,"journal":{"name":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE/PES Transmission and Distribution Conference and Exposition: Latin America (T&D-LA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TDC-LA.2010.5762868","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, a novel methodology to price the reactive power support ancillary service of Distributed Generators (DGs) with primary energy source uncertainty is shown. The proposed methodology provides the service pricing based on the Loss of Opportunity Costs (LOC) calculation. An algorithm is proposed to reduce the uncertainty present in these generators using Multiobjective Power Flows (MOPFs) implemented in multiple probabilistic scenarios through Monte Carlo Simulations (MCS), and modeling the time series associated with the generation of active power from DGs through Markov Chains (MC).