Show simple item record

dc.contributor.authorChen, Ruidien_US
dc.contributor.authorPaschalidis, Ioannis Ch.en_US
dc.contributor.authorCaramanis, Michael C.en_US
dc.contributor.authorAndrianesis, Panagiotisen_US
dc.date2018-12-28
dc.date.accessioned2020-01-10T14:34:18Z
dc.date.available2020-01-10T14:34:18Z
dc.date.issued2019-01-09
dc.identifier.citationRuidi Chen, Ioannis Ch Paschalidis, Michael C Caramanis, Panagiotis Andrianesis. 2019. "Learning from Past Bids to Participate Strategically in Day-Ahead Electricity Markets." IEEE Transactions on Smart Grid, Volume 10, Issue 5, pp. 5794 - 5806. https://doi.org/10.1109/TSG.2019.2891747
dc.identifier.issn1949-3053
dc.identifier.urihttps://hdl.handle.net/2144/39073
dc.description.abstractWe consider the process of bidding by electricity suppliers in a day-ahead market context, where each supplier bids a linear non-decreasing function of her generating capacity with the goal of maximizing her individual profit given other competing suppliers' bids. Based on the submitted bids, the market operator schedules suppliers to meet demand during each hour and determines hourly market clearing prices. Eventually, this game-theoretic process reaches a Nash equilibrium when no supplier is motivated to modify her bid. However, solving the individual profit maximization problem requires information of rivals' bids, which are typically not available. To address this issue, we develop an inverse optimization approach for estimating rivals' production cost functions given historical market clearing prices and production levels. We then use these functions to bid strategically and compute Nash equilibrium bids. We present numerical experiments illustrating our methodology, showing good agreement between bids based on the estimated production cost functions with the bids based on the true cost functions. We discuss an extension of our approach that takes into account network congestion resulting in location-dependent pricesen_US
dc.format.extentp. 5794 - 5806en_US
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineersen_US
dc.relation.ispartofIEEE Transactions on Smart Grid
dc.subjectDay-ahead marketen_US
dc.subjectEquilibrium bidsen_US
dc.subjectLearningen_US
dc.subjectInverse equilibriumen_US
dc.subjectInverse optimizationen_US
dc.subjectElectrical and electronic engineeringen_US
dc.subjectInterdisciplinary engineeringen_US
dc.titleLearning from past bids to participate strategically in day-ahead electricity marketsen_US
dc.typeArticleen_US
dc.description.versionFirst author draften_US
dc.identifier.doi10.1109/TSG.2019.2891747
pubs.elements-sourcemanual-entryen_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Mechanical Engineeringen_US
pubs.publication-statusPublisheden_US
dc.identifier.orcid0000-0002-3343-2913 (Paschalidis, Ioannis Ch)
dc.identifier.mycv406767


This item appears in the following Collection(s)

Show simple item record