Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/70227
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dc.titleEvolving cooperative bidding strategies in a power market
dc.contributor.authorSrinivasan, D.
dc.contributor.authorLye, K.W.
dc.contributor.authorWoo, D.
dc.date.accessioned2014-06-19T03:09:41Z
dc.date.available2014-06-19T03:09:41Z
dc.date.issued2006
dc.identifier.citationSrinivasan, D.,Lye, K.W.,Woo, D. (2006). Evolving cooperative bidding strategies in a power market. 2006 IEEE Congress on Evolutionary Computation, CEC 2006 : 2563-2570. ScholarBank@NUS Repository.
dc.identifier.isbn0780394879
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/70227
dc.description.abstractThis paper presents an evolutionary algorithm to generate cooperative strategies for individual buyers in a competitive power market The paper explores how buyers can lower their costs by using an evolutionary algorithm that evolves their group sizes and memberships. The evolutionary process uncovers interesting agent behaviors and strategies for collaboration. The developed agent-based model uses PowerWorld simulator to incorporate the traditional physical system characteristics and constraints while evaluating individual agent's behavior, actions and reactions on market dynamics. Simulation results on IEEE 14-bus system show that the evolutionary approach evolves mutually beneficial strategies that enhance the buyer's profitability. The buyers learn to achieve substantial cost savings by forming groups and adjusting their demand curves, without sacrificing much in desired power consumption. © 2006 IEEE.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.sourcetitle2006 IEEE Congress on Evolutionary Computation, CEC 2006
dc.description.page2563-2570
dc.identifier.isiutNOT_IN_WOS
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