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Adaptive Particle Swarm Optimization for Simultaneous Design of UPFC Damping Controllers

机译:UPFC阻尼控制器同时设计的自适应粒子群算法

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摘要

An adaptive particle swarm optimization based on nonlinear time-varying acceleration coefficients (NTVAC-PSO) is proposed for solving global optimization problems and damping of power system oscillations. The new method aims to control the global exploration ability of the original PSO algorithm and to increase its convergence rate with an acceptable solution in less iteration. A set of 10 well-known benchmark optimization problems is utilized to validate the performance of the NTVAC-PSO as a global optimization algorithm and to compare with similar methods. The numerical experiments show that the proposed algorithm leads to a significantly more accurate final solution for a variety of benchmark test functions faster. In addition, the simultaneous coordinated design of unified power flow controller-based damping controllers is presented to illustrate the feasibility and effectiveness of the new method. The performance of the proposed algorithm is compared with other methods through eigenvalue analysis and nonlinear time-domain simulation. The simulation studies show that the controllers designed using NTVAC-PSO performed better than controllers designed by other methods. Moreover, experimental results confirm superior performance of the new method compared with other methods.
机译:提出了一种基于非线性时变加速度系数(NTVAC-PSO)的自适应粒子群算法,以解决全局优化问题和抑制电力系统振荡的问题。新方法旨在控制原始PSO算法的全局探索能力,并以可接受的解决方案以较小的迭代次数提高其收敛速度。利用一组10个众所周知的基准优化问题来验证NTVAC-PSO作为全局优化算法的性能,并与类似方法进行比较。数值实验表明,所提出的算法可以为各种基准测试功能带来更快,更准确的最终解决方案。此外,提出了基于统一潮流控制器的阻尼控制器的同步协调设计,以说明该方法的可行性和有效性。通过特征值分析和非线性时域仿真,将该算法的性能与其他方法进行了比较。仿真研究表明,使用NTVAC-PSO设计的控制器的性能优于通过其他方法设计的控制器。而且,实验结果证实了该新方法与其他方法相比的优越性能。

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