Please use this identifier to cite or link to this item:
|Title:||Multi-agent approach for profit based unit commitment||Authors:||Sharma, D.
|Issue Date:||2011||Citation:||Sharma, D.,Srinivasan, D.,Trivedi, A. (2011). Multi-agent approach for profit based unit commitment. 2011 IEEE Congress of Evolutionary Computation, CEC 2011 : 2527-2533. ScholarBank@NUS Repository. https://doi.org/10.1109/CEC.2011.5949932||Abstract:||Deregulation in the electricity market offers freedom to the generator companies (GENCOs) to schedule their generators in order to maximize their profit without actually satisfying the load and the reserve requirements. Various techniques have been developed for solving the profit based unit commitment (PBUC) problem. Among them, the multi-agent approach is different where each generator unit is referred to as an intelligent agent. In this paper, we develop a new multi-agent approach for PBUC problem in which the rule based intelligence is provided to the independent system operator (ISO) agent. Intelligence of generator agents (GenAgents) is limited to maximize their profit for the given demand and reserve using real-parametric genetic algorithm (GA) and share the results with ISO agent. In this approach, ISO agent commits the maximum profit generating GenAgents for every hour while satisfying the up/down time constraints. ISO agent also asks other GenAgents to calculate their profit for the remaining demand and reserve. The simulation results of 10 units problem for two payment methods are shown and compared with other techniques. © 2011 IEEE.||Source Title:||2011 IEEE Congress of Evolutionary Computation, CEC 2011||URI:||http://scholarbank.nus.edu.sg/handle/10635/71028||ISBN:||9781424478347||DOI:||10.1109/CEC.2011.5949932|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Sep 21, 2022
checked on Sep 22, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.