{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/16146"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/16146","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Impacts of demand response resources on scheduling and prices in day-ahead electricity markets","abstract":"This thesis addresses the explicit representation of demand-side resources as participants in the day-ahead electricity markets and assesses their impacts on schedul- ing and prices. These resources offer to reduce their loads and compete side-by-side with the supply-side resources in the hourly auctions in the day-ahead markets for energy and capacity-based ancillary services. These demand-side market participants are commonly referred to as demand response resources (DRRs). The unit commitment problem is used as the vehicle for the study and to evaluate the changes in the operating schedules of the supply-side resources and the resulting prices. In the study, the load recovery effects that accompany the load curtailment that DRRs provide are assessed. A mixed-integer programming solver is used to explicitly represent the integral nature of the decision variables involved in determining the optimal schedules for next day system operations. The solutions of the unit commitment problem are studied to develop appropriate insights into the impacts of DRRs on the prices and quantities of energy and capacity-based ancillary services in the hourly auctions for the next day. The testing is performed on a test system with 24 supply-side resources, to quantify the role of the DRRs in the joint electricity markets for energy and capacity-based ancillary services.","abstract_html":"This thesis addresses the explicit representation of demand-side resources as participants in the day-ahead electricity markets and assesses their impacts on schedul- ing and prices. These resources offer to reduce their loads and compete side-by-side with the supply-side resources in the hourly auctions in the day-ahead markets for energy and capacity-based ancillary services. These demand-side market participants are commonly referred to as demand response resources (DRRs). The unit commitment problem is used as the vehicle for the study and to evaluate the changes in the operating schedules of the supply-side resources and the resulting prices. In the study, the load recovery effects that accompany the load curtailment that DRRs provide are assessed. A mixed-integer programming solver is used to explicitly represent the integral nature of the decision variables involved in determining the optimal schedules for next day system operations. The solutions of the unit commitment problem are studied to develop appropriate insights into the impacts of DRRs on the prices and quantities of energy and capacity-based ancillary services in the hourly auctions for the next day. The testing is performed on a test system with 24 supply-side resources, to quantify the role of the DRRs in the joint electricity markets for energy and capacity-based ancillary services.","abstract_has_math":false,"creators":["Nelli, Rajesh B."],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Sauer, Peter W."],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2010,"date_issued":"2010-05-19T18:38:38Z","date_published":"2010-05-19T18:38:38Z","updated_at":"2026-07-22T22:25:08Z","subjects":["Unit Commitment","Demand Response","Mixed-Integer Programming"],"languages":["en"],"rights":["Copyright 2010 Rajesh B. 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In the study, the load recovery effects that accompany the load curtailment that DRRs provide are assessed. A mixed-integer programming solver is used to explicitly represent the integral nature of the decision variables involved in determining the optimal schedules for next day system operations. The solutions of the unit commitment problem are studied to develop appropriate insights into the impacts of DRRs on the prices and quantities of energy and capacity-based ancillary services in the hourly auctions for the next day. 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The unit commitment problem is used as the vehicle for the study and to evaluate the changes in the operating schedules of the supply-side resources and the resulting prices. In the study, the load recovery effects that accompany the load curtailment that DRRs provide are assessed. A mixed-integer programming solver is used to explicitly represent the integral nature of the decision variables involved in determining the optimal schedules for next day system operations. The solutions of the unit commitment problem are studied to develop appropriate insights into the impacts of DRRs on the prices and quantities of energy and capacity-based ancillary services in the hourly auctions for the next day. 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