Abstract
Ant colony system (ACS) is more suitable for hard combinatorial optimization problems. So ACS has been applied to unit commitment problem (UCP). The UCP is solved with power flow constraints. Also to make the system function in a realistic environment, white Gaussian noise (WGN) is added to the network nodes with proportional loads to the demand forecasted at each hourly stage. Multi-stage decisions give ant search competitive over other conventional techniques. The proposed model is tested on IEEE 30 bus system and has been compared with dynamic programming (DP) and branch and bound integer programming (BBIP) approaches
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
