Analysis and Comparison for the Unit Commitment Problem in a Large-Scale Power System by Using Three Meta-Heuristic Algorithms. (December 2017)

• Record Type: Journal Article
• Authors: Wu, Yuan-Kang; Chang, Hong-Yi; Chang, Shih Ming
• Is Part Of: Energy procedia. Volume 141(2017)
• Page Start: 423
• Page End: 427
• Publication Date: 2017-12
• Subjects: Unit commitment -- particle swarm optimization (PSO) -- charged search system(CSS) -- ants colony search (ACS); Power resources -- Congresses; Power resources -- Periodicals; Power resources; Conference proceedings; Periodicals; 333.7905
• DOI: 10.1016/j.egypro.2017.11.054
• Languages: English
• ISSNs: 1876-6102

Abstract

Abstract: This work applied three algorithms including charged search system (CSS), particle swarm optimization (PSO), and ants colony search (ACS) to solve the unit commitment problem in a large-scale power system. The three algorithms were applied to 10-, 20-, 40-, 60-, 80-, 100-bus testing systems to solve the UC problem. Then, this work compares the total generation cost and calculation time obtained from the three algorithms. This work also discussed the tunable parameters in the three algorithms, and compared the solutions on UC cost and computation time by setting different parameters.