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Chaotic ant swarm optimization to economic dispatch

机译:混沌蚁群算法对经济调度的优化

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This paper developed a novel algorithm named chaotic ant swarm optimization (CASO) for solving the economic dispatch (ED) problems of thermal generators in power systems. This algorithm combines with the chaotic and self-organization behavior of ants in the foraging process. It includes both effects of chaotic dynamics and swarm-based search. The algorithm was employed to solve the ED problems of thermal generators. The proposed method was applied to three examples of power systems. Simulation results demonstrated that the method can obtain feasible and effective solutions, and it is a promising alternative approach for solving the ED problems in practical power systems.
机译:本文开发了一种新颖的算法,称为混沌蚁群算法(CASO),用于解决电力系统中热力发电机的经济调度(ED)问题。该算法结合了蚂蚁在觅食过程中的混沌和自组织行为。它既包括混沌动力学的影响,又包括基于群体的搜索。该算法被用来解决热发电机的ED问题。该方法被应用于电力系统的三个例子。仿真结果表明,该方法可以获得可行,有效的解决方案,是解决实际电力系统中ED问题的一种有希望的替代方法。

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