Journal
IEEE ACCESS
Volume 6, Issue -, Pages 43535-43545Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2018.2861319
Keywords
Power system; unit commitment; cuckoo search algorithm; heuristic method
Categories
Funding
- National Key R&D Program of China [2017YFB0306400]
- National Natural Science Foundation of China [61573089, 71472080, 71301066, U1731128]
- Deanship of Scientific Research (DSR) at King Abdulaziz University, Jeddah [G-415-135-38]
- Liaoning Province Dr. Research Foundation of China [20175032]
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The unit commitment problem is a large-scale, nonlinear, and mixed-integer optimization problem in an electric power system. Numerous researchers concentrate on minimizing its total generation cost. Cuckoo search is an efficient metaheuristic swarm-based approach that balances between local and global search strategy. Owing to its easy implementation and rapid convergence, it has been successfully used to solve a wide variety of optimization problems. This paper proposes an improved binary cuckoo search algorithm (IBCS) for solving the unit commitment problem. A new binary updating mechanism is introduced to help the IBCS choose a right search direction, and a heuristic search method based on a novel priority list can prevent it from being trapped into local optima. A 4-unit system is used as an example to validate the effectiveness of the proposed method.
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