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Optimal Design of Passive Power Filters Based on Multi-objective Cultural Algorithms

机译:基于多目标文化算法的无源电力滤波器的最优设计

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Design of passive power filters shall meet the demand of harmonics suppression effect and economic target. However, existing optimization methods for this problem only take technology target into account or do not utilize knowledge enough, which limits the speed of convergence and the performance of solutions. To solve the problem, two objectives including minimum total harmonics distortion of current and minimum cost for equipments are constructed. In order to achieve the optimal solution effectively, a novel multi-objective optimization method, which adopts dual evolution structure in cultural algorithms, is adopted. Implicit knowledge describing the dominant space are extracted and utilized to induce the direction of evolution. Taken three-phase full wave controlled rectifier as harmonic source, simulation results show that filter designed by the proposed algorithm have better harmonics suppression effect and lower investment for equipments than filter designed by existing methods.
机译:无源电源过滤器的设计应符合谐波抑制效果和经济目标的需求。然而,对于此问题的现有优化方法仅考虑技术目标或者不充分利用足够的知识,这限制了收敛速度和解决方案的性能。为了解决问题,构建了两个包括最小总谐波变形的两个目标和设备最低成本。为了有效地实现最佳解决方案,采用了一种采用了一种采用文化算法中双重演化结构的新型多目标优化方法。提取描述主导空间的隐式知识并利用以诱导进化方向。采用三相全波控整流器作为谐波源,仿真结果表明,由所提出的算法设计的过滤器具有更好的谐波抑制效果和降低设备投资,而不是通过现有方法设计的滤波器。

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