An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description

Jian Zhao, Shixin Liu, Meng Chu Zhou, Xiwang Guo, Liang Qi

Research output: Contribution to journalArticlepeer-review

31 Scopus citations

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.

Original languageEnglish (US)
Article number8426049
Pages (from-to)43535-43545
Number of pages11
JournalIEEE Access
Volume6
DOIs
StatePublished - Aug 6 2018

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Keywords

  • Power system
  • cuckoo search algorithm
  • heuristic method
  • unit commitment

Fingerprint

Dive into the research topics of 'An Improved Binary Cuckoo Search Algorithm for Solving Unit Commitment Problems: Methodological Description'. Together they form a unique fingerprint.

Cite this