DocumentCode :
1955552
Title :
Short term unit-commitment using genetic algorithms
Author :
Dasgupta, Dipankar ; McGregor, Douglas R.
Author_Institution :
Dept. of Comput. Sci., Stratchclyde Univ., Glasgow, UK
fYear :
1993
fDate :
8-11 Nov 1993
Firstpage :
240
Lastpage :
247
Abstract :
The authors present a genetic approach for determining the priority order in the commitment of thermal units in power generation. The objective of the problem is to properly schedule the on/off states of all thermal units in a system to meet the load demand and the reverse requirement at each time interval, such that the overall system generation cost is a minimum, while satisfying various operational constraints. The authors examine the feasiblity of using genetic algorithms and report some simulation results in near-optimal commitment of thermal units in a power system
Keywords :
economics; electric power generation; genetic algorithms; load distribution; thermal power stations; commitment; generation cost; genetic algorithms; load; on/off states; power generation; thermal units; Biological cells; Character generation; Costs; Dynamic programming; Genetic algorithms; Power generation; Power generation economics; Power system simulation; Processor scheduling; Thermal loading;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Tools with Artificial Intelligence, 1993. TAI '93. Proceedings., Fifth International Conference on
Conference_Location :
Boston, MA
ISSN :
1063-6730
Print_ISBN :
0-8186-4200-9
Type :
conf
DOI :
10.1109/TAI.1993.633963
Filename :
633963
Link To Document :
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