{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/106200"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/106200","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Game-theoretic analysis of deregulated electricity markets: From retail to wholesale","abstract":"As end-consumers of electricity become more proactive and as many countries around the world push for a deeper penetration of renewable resources into the power grid, critical issues and challenges arise to the design and operation of deregulated electricity markets. In this dissertation, we exploit tools from game theory and optimization theory to address some of these critical issues. Firstly, wholesale and retail markets are becoming more integrated due to the increasing adoption of distributed energy resources, creating a large gap in the current understanding of the impact of such small-scale energy resources on the larger power system operation and electricity market outcomes. This motivates us to develop a metric, called the Price of Aggregation, which quantifies the impact of integrating distributed energy resources in the retail-level on wholesale market efficiency. Secondly, evidence from real markets indicate that large-scale adoption of wind energy in the transmission system leads to significantly higher price volatility in wholesale markets. To mitigate the effects of price volatility, we propose an add-on centralized clearing mechanism that is applicable to any wholesale market, with the aim of allowing any market participant to hedge against profit volatilities, without changing the existing market operations. Finally, we continue previous efforts in the literature toward developing a multi-period-multi-company demand response framework in retail markets, which captures the behavior of competing companies and their price-responsive end-consumers. Using real-life data, we demonstrate potential savings that can exceed 30% for end-consumers, in addition to revealing desirable mathematical properties and achieving optimal power allocation across the time horizon.","abstract_html":"As end-consumers of electricity become more proactive and as many countries around the world push for a deeper penetration of renewable resources into the power grid, critical issues and challenges arise to the design and operation of deregulated electricity markets. In this dissertation, we exploit tools from game theory and optimization theory to address some of these critical issues. Firstly, wholesale and retail markets are becoming more integrated due to the increasing adoption of distributed energy resources, creating a large gap in the current understanding of the impact of such small-scale energy resources on the larger power system operation and electricity market outcomes. This motivates us to develop a metric, called the Price of Aggregation, which quantifies the impact of integrating distributed energy resources in the retail-level on wholesale market efficiency. Secondly, evidence from real markets indicate that large-scale adoption of wind energy in the transmission system leads to significantly higher price volatility in wholesale markets. To mitigate the effects of price volatility, we propose an add-on centralized clearing mechanism that is applicable to any wholesale market, with the aim of allowing any market participant to hedge against profit volatilities, without changing the existing market operations. Finally, we continue previous efforts in the literature toward developing a multi-period-multi-company demand response framework in retail markets, which captures the behavior of competing companies and their price-responsive end-consumers. Using real-life data, we demonstrate potential savings that can exceed 30% for end-consumers, in addition to revealing desirable mathematical properties and achieving optimal power allocation across the time horizon.","abstract_has_math":false,"creators":["Alshehri, Khaled"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Başar, Tamer","Bose, Subhonmesh","Domínguez-García, Alejandro","Sauer, Peter"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2020,"date_issued":"2020-03-02T21:58:13Z","date_published":"2020-03-02T21:58:13Z","updated_at":"2026-07-22T22:24:45Z","subjects":["Game Theory","Electricity Markets","Power System Economics","Smart Grid"],"languages":["en"],"rights":["Copyright 2019 Khaled Alshehri"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/106200","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Başar, Tamer","Bose, Subhonmesh","Domínguez-García, Alejandro","Sauer, Peter"]},{"key":"dc:creator","label":"Author","values":["Alshehri, Khaled"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2020-03-02T21:58:13Z","2019-11-22","2019-12"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Game Theory","Electricity Markets","Power System Economics","Smart Grid"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Khaled Alshehri"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/106200"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["As end-consumers of electricity become more proactive and as many countries around the world push for a deeper penetration of renewable resources into the power grid, critical issues and challenges arise to the design and operation of deregulated electricity markets. In this dissertation, we exploit tools from game theory and optimization theory to address some of these critical issues. Firstly, wholesale and retail markets are becoming more integrated due to the increasing adoption of distributed energy resources, creating a large gap in the current understanding of the impact of such small-scale energy resources on the larger power system operation and electricity market outcomes. This motivates us to develop a metric, called the Price of Aggregation, which quantifies the impact of integrating distributed energy resources in the retail-level on wholesale market efficiency. Secondly, evidence from real markets indicate that large-scale adoption of wind energy in the transmission system leads to significantly higher price volatility in wholesale markets. To mitigate the effects of price volatility, we propose an add-on centralized clearing mechanism that is applicable to any wholesale market, with the aim of allowing any market participant to hedge against profit volatilities, without changing the existing market operations. Finally, we continue previous efforts in the literature toward developing a multi-period-multi-company demand response framework in retail markets, which captures the behavior of competing companies and their price-responsive end-consumers. Using real-life data, we demonstrate potential savings that can exceed 30% for end-consumers, in addition to revealing desirable mathematical properties and achieving optimal power allocation across the time horizon.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, Khaled Alshehri, accepted the attached license on 2019-11-21 at 01:52.","The student, Khaled Alshehri, submitted this Dissertation for approval on 2019-11-21 at 17:23.","This Dissertation was approved for publication on 2019-11-22 at 14:28.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14578 on 2020-02-28 at 17:13:52","Made available in DSpace on 2020-03-02T21:58:13Z (GMT). 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To mitigate the effects of price volatility, we propose an add-on centralized clearing mechanism that is applicable to any wholesale market, with the aim of allowing any market participant to hedge against profit volatilities, without changing the existing market operations. Finally, we continue previous efforts in the literature toward developing a multi-period-multi-company demand response framework in retail markets, which captures the behavior of competing companies and their price-responsive end-consumers. Using real-life data, we demonstrate potential savings that can exceed 30% for end-consumers, in addition to revealing desirable mathematical properties and achieving optimal power allocation across the time horizon.","Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2020-02-28 without embargo terms","The student, Khaled Alshehri, accepted the attached license on 2019-11-21 at 01:52.","The student, Khaled Alshehri, submitted this Dissertation for approval on 2019-11-21 at 17:23.","This Dissertation was approved for publication on 2019-11-22 at 14:28.","DSpace SAF Submission Ingestion Package generated from Vireo submission #14578 on 2020-02-28 at 17:13:52","Made available in DSpace on 2020-03-02T21:58:13Z (GMT). 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