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A PSO Procedure for a Coordinated Tuning of Power System Stabilizers for Multiple Operating Conditions

机译:用于多种工作条件的电力系统稳定器协调调整的PSO程序

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The problem of coordinated tuning stabilizers in multi-machine power systems is formulated here as a sequence of optimization problems. The design problem of stabilizers is converted to a nonlinear optimization problem with a multi-objective fitness function. The proposed method employs particle swarm optimization (PSO), an algorithm to search for optimal parameter settings of a widely used conventional fixed-structure lead-lag power system stabilizers (CPSSs). One of the main advantages of the proposed approach is its robustness to the initial parameter settings. In addition, the quality of the optimal solution does not rely on the initial guess. The robustness and performance of the newly designed controllers is evaluated in a large sixteen-machine power system subjected to different loading conditions in comparison with the genetic algorithm (GA) based PSSs design. The superiority of the controller designed is demonstrated through the nonlinear time-domain simulation and some performance indices studies. The results analysis reveals that the tuned PSSs with proposed objective function has an excellent capability in damping power system low-frequency oscillations.
机译:这里将多机电源系统中协调稳定器的协调问题描述为一系列优化问题。稳定器的设计问题被转换为具有多目标适应度函数的非线性优化问题。所提出的方法采用粒子群优化(PSO),该算法可搜索广泛使用的常规固定结构超前-滞后电力系统稳定器(CPSS)的最佳参数设置。所提出的方法的主要优点之一是其对初始参数设置的鲁棒性。此外,最佳解决方案的质量不依赖于最初的猜测。与基于遗传算法(GA)的PSSs设计相比,该新设计控制器的鲁棒性和性能在具有不同负载条件的大型16机动力系统中进行了评估。通过非线性时域仿真和一些性能指标的研究证明了所设计控制器的优越性。结果分析表明,具有目标函数的调谐PSS具有良好的阻尼电力系统低频振荡的能力。

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