An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description
Document Type
Article
Publication Date
8-6-2018
Abstract
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.
Identifier
85051376620 (Scopus)
Publication Title
IEEE Access
External Full Text Location
https://doi.org/10.1109/ACCESS.2018.2861319
e-ISSN
21693536
First Page
43535
Last Page
43545
Volume
6
Grant
2017YFB0306400
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Zhao, Jian; Liu, Shixin; Zhou, Meng Chu; Guo, Xiwang; and Qi, Liang, "An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description" (2018). Faculty Publications. 8456.
https://digitalcommons.njit.edu/fac_pubs/8456
