Title :
Genetic-based unit commitment algorithm
Author :
Maifeld, Tim T. ; Sheble, Gerald B.
Author_Institution :
Dept. of Electr. Eng., Iowa State Univ., Ames, IA, USA
fDate :
8/1/1996 12:00:00 AM
Abstract :
This paper presents a new unit commitment scheduling algorithm. The proposed algorithm consist of using a genetic algorithm with domain specific mutation operators. The proposed algorithm can easily accommodate any constraint that can be true costed. Robustness of the proposed algorithm is demonstrated by comparison to a Lagrangian relaxation unit commitment algorithm on three different electric utilities. Results show the proposed algorithm finds good unit commitment schedules in a reasonable amount of computation time. Included in the appendix is an explanation of the true costing approach
Keywords :
costing; economics; genetic algorithms; load dispatching; load distribution; numerical stability; power system planning; scheduling; Lagrangian relaxation; computation time; domain specific mutation operators; electric utilities; genetic algorithm; numerical robustness; power generation planning; true costing approach; unit commitment scheduling algorithm; Costing; Costs; Genetic algorithms; Genetic mutations; Lagrangian functions; Power system dynamics; Power systems; Processor scheduling; Robustness; Scheduling algorithm;
Journal_Title :
Power Systems, IEEE Transactions on
