Title :
Unit commitment using stochastic optimization
Author :
Numnonda, T. ; Annakkage, U.D. ; Pahalawaththa, N.C.
Author_Institution :
Dept. of Comput. Eng., Khon Kaen Univ., Thailand
Abstract :
This paper demonstrates how the simulated annealing algorithm and genetic algorithms can be used as means to solve the power system unit commitment problem. In addition, this paper presents parallel approaches to speed up the computational requirement of the simulated annealing algorithm. The algorithms were tested with two different problems. The results have demonstrated the success of the algorithms in consistently reaching good solutions
Keywords :
genetic algorithms; load dispatching; load distribution; optimal control; power system control; simulated annealing; stochastic processes; computational requirement; control optimisation; genetic algorithms; power generating units; power system unit commitment; simulated annealing algorithm; stochastic optimization; Concurrent computing; Cost function; Dynamic programming; Genetic algorithms; Genetic engineering; Power demand; Power generation; Simulated annealing; Spinning; Stochastic processes;
Conference_Titel :
Intelligent Systems Applications to Power Systems, 1996. Proceedings, ISAP '96., International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-3115-X
DOI :
10.1109/ISAP.1996.501111
