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Profit based unit commitment using memetic binary differential evolution algorithm

delete2019-08-01
delete32
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J
J.S. Dhillon
DOI:10.1016/j.asoc.2019.105502delete
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摘要

摘要

En 中文
Profit-based unit-commitment problem (PBUCP) is a notable combinatorial optimizing problem faced in the deregulated power industry. The PBUCP finds the best profitable solution by committing and scheduling the thermal generating units efficiently. To solve the PBUCP, a new memetic binary differential evolution algorithm is proposed which considers binary differential evolution (BDE) algorithm as global search operator to improve the exploration aspect and binary hill-climbing (BHC) algorithm as local search operator to improve the exploitation aspect. A binary differential evolution algorithm is introduced whereby a new mutation strategy is implemented. A novel BHC algorithm makes priority-based perturbations on unit's status to improve the global best solution searched by the BDE algorithm alone. A new excessive unit de-commitment strategy based on priority and total profit is also proposed. The power to committed units is allocated based on priority of units. The efficacy of algorithms has been researched on the PBUCP test systems comprising of 10-, 40- and 100-units over a time horizon. The outcomes of the proposed algorithms are compared with previously known best solutions. Simulated outcomes achieved by the proposed algorithms compete with the already reported algorithms to solve the PBUCP. Wilcoxon signed-rank test proves the predominance of the proposed algorithms statistically. (C) 2019 Elsevier B.V. All rights reserved.
Keyword:
Profit-based unit commitment
Memetic binary differential evolution
Binary differential evolution
Binary hill-climbing
Memetic algorithm
Priority methods
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期刊

Applied Soft Computing 封面图
Applied Soft Computing
IF:
6.6
论文数:
1.4W
被引数:
4.8W

机构

S
sant longowal institute of engineering & technology (sliet)
学者数:
818
论文数: 814
被引数: 3
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