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A new quantum inspired chaotic artificial bee colony algorithm for optimal power flow problem
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DOI：10.1016/j.enconman.2015.04.051.png)
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This paper proposes a new artificial bee colony algorithm with quantum theory and the chaotic local search strategy (QCABC), and uses it to solve the optimal power flow (OFF) problem. Under the quantum computing theory, the QCABC algorithm encodes each individual with quantum bits to form a corresponding quantum bit string. By determining each quantum bits value, we can get the value of the individual. After the scout bee stage of the artificial bee colony algorithm, we begin the chaotic local search in the vicinity of the best individual found so far. Finally, the quantum rotation gate is used to process each quantum bit so that all individuals can update toward the direction of the best individual. The QCABC algorithm is carried out to deal with the OFF problem in the IEEE 30-bus and IEEE 118-bus standard test systems. The results of the QCABC algorithm are compared with other algorithms (artificial bee colony algorithm, genetic algorithm, particle swarm optimization algorithm). The comparison shows that the QCABC algorithm can effectively solve the OPF problem and it can get the better optimal results than those of other algorithms. (C) 2015 Elsevier Ltd. All rights reserved.
Keyword:
Artificial bee colony algorithm
Quantum computing theory
Chaos theory
Optimal power flow
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期刊
IF:
10.9
论文数:
2.0W
被引数:
11.3W
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引用论文
Experiments with the interior-point method for solving large scale Optimal Power Flow problems用内点法求解大规模最优潮流问题的实验
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