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
Link To Document :
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