期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 36, 期 4, 页码 8049-8055出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2008.10.047
关键词
Unit commitment; Priority list; Particle swarm optimization; Heuristic search
类别
资金
- National Natural Science Foundation of China [50779020, 40572166]
This paper proposes a new improved binary PSO (IBPSO) method to solve the unit commitment (UC) problem, which is integrated binary particle swarm optimization (BPSO) with lambda-iteration method. The IBPSO is improved by priority list based on the unit characteristics and heuristic search strategies to repair the spinning reserve and minimum up/down time constraints. To verify the advantages of the IBPSO method, the IBPSO is tested and compared to the other methods on the systems with the number of units in the range of 10-100. Numerical results demonstrate that the IBPSO is Superior to other methods reported in the literature in terms of lower production cost and shorter computational time. (c) 2008 Elsevier Ltd. All rights reserved.
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