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Reactive power optimization in power system based on chaos ant colony algorithm 基于混沌蚁群算法的电力系统无功优化
Pub Date : 2009-04-06 DOI: 10.1109/SUPERGEN.2009.5348366
Zhe Liu, Xiaohua Wang, Chaowei Li
A novel co-operative agents approach, ant colony optimization (ACO) algorithm, for solving problems of combinatorial optimization, is put forward by M. Dorigo. The main characteristics of ACO are positive feedback, distributed computation. Preliminary study has shown that it has many promising futures. This paper reviews recent work on ant algorithms and applications, the chaos ant colony optimization (CACO) algorithm is used in reactive power optimization problem in electric power system. The model of reactive power optimization is established taking the minimum network losses as the objective. Its validity is verified through arithmetic examples of IEEE30 node and the practical area network of Puyang city.
Dorigo提出了一种求解组合优化问题的新型合作智能体方法——蚁群优化算法。蚁群算法的主要特点是正反馈、分布式计算。初步研究表明,它的前景广阔。本文综述了近年来蚂蚁算法及其应用的研究进展,将混沌蚁群算法应用于电力系统无功优化问题。以网损最小为目标,建立了无功优化模型。通过IEEE30节点和濮阳市实际局域网的算例验证了该算法的有效性。
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引用次数: 5
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CICED 2010 Proceedings
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