DocumentCode
2588925
Title
A Genetic Algorithm Approach to Price-Based Unit Commitment
Author
Solanki, Jignesh ; Khushalani, Sarika ; Srivastava, Anurag
Author_Institution
Mississippi State Univ., Oxford, MS
fYear
2006
fDate
17-19 Sept. 2006
Firstpage
425
Lastpage
429
Abstract
Deregulation creates competition amongst generator companies. The generator company objectives are to maximize their profit and to place proper bids in the market. In order to do this they need to determine the schedule and operating points based on the load and price forecasts. The traditional unit commitment problem aims at minimizing the cost of operation subject to fulfillment of demand. However in a deregulated environment the traditional unit commitment objective needs to be changed to maximization of profit with relaxation of the demand fulfillment constraint. This paper applies a genetic algorithm technique to price based unit commitment (PBUC) for GENCO with 3 generators and compares the solution with that obtained by dynamic programming. Proposed algorithm can be extended to ´n´ number of generators.
Keywords
dynamic programming; genetic algorithms; load forecasting; power markets; electricity supply industry deregulation; genetic algorithm; load forecasting; price forecasting; price-based unit commitment; Availability; Costs; Demand forecasting; Dynamic programming; Economic forecasting; Genetic algorithms; Lagrangian functions; Load forecasting; Power system dynamics; Power systems; Price based unit commitment; deregulation; dynamic programming; genetic algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Symposium, 2006. NAPS 2006. 38th North American
Conference_Location
Carbondale, IL
Print_ISBN
1-4244-0227-1
Electronic_ISBN
1-4244-0228-X
Type
conf
DOI
10.1109/NAPS.2006.359607
Filename
4201350
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