Journal
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
Volume 18, Issue 7, Pages 1746-1756Publisher
ELSEVIER
DOI: 10.1016/j.cnsns.2012.11.003
Keywords
Cascaded hydroelectric system; Particle swarm optimization; Chaotic search; Improved logistic map; Death penalty function; Scheduling
Categories
Funding
- China Postdoctoral Science Special Foundation [201104323]
- China Postdoctoral Science Foundation [20100480679]
- National High Technology Research and development of China (863 Program) [2011AA05A116]
- Natural Science Foundation of China [71131002, 71071045]
- Doctor's Special Research Foundation of Hefei University of Technology [2010HGBZ0599]
- Fundamental Research Funds for the Central Universities [2012-IV-102]
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In order to solve the model of short-term cascaded hydroelectric system scheduling, a novel chaotic particle swarm optimization (CPSO) algorithm using improved logistic map is introduced, which uses the water discharge as the decision variables combined with the death penalty function. According to the principle of maximum power generation, the proposed approach makes use of the ergodicity, symmetry and stochastic property of improved logistic chaotic map for enhancing the performance of particle swarm optimization (PSO) algorithm. The new hybrid method has been examined and tested on two test functions and a practical cascaded hydroelectric system. The experimental results show that the effectiveness and robustness of the proposed CPSO algorithm in comparison with other traditional algorithms. (C) 2012 Elsevier B. V. All rights reserved.
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