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Solving the unit commitment problem with a genetic algorithm through a constraint satisfaction technique
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AI
DOI：10.1016/0378-7796(96)01036-X.png)
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This paper proposes a genetic algorithm (GA) in conjunction with constraint handling techniques to solve the thermal unit commitment problem. To deal effectively with the constraints of the problem and prune the search space of the GA in advance, the difficult minimum up- and down-time constraints are embedded in the binary strings that are coded to represent the on-off states of the generating units. The other constraints are handled by integrating penalty factors into the cost function within an enhanced economic dispatch program. The proposed GA approach has been tested on a practical Taiwan Power (Taipower) thermal system over a 24-hour period for different utility factors and GA control parameters. Test results reveal that the features of easy implementation, fast convergence, and a highly near-optimal solution in solving the UC problem can be achieved by the proposed GA approach.
Keyword:
unit commitment
genetic algorithms
optimization techniques
期刊
IF:
4.2
论文数:
1.2W
被引数:
2.2W
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