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Power System Stabilizer Tuning Based on Multiobjective Design Using Hierarchical and Parallel Micro Genetic Algorithm

机译:基于分层并行微遗传算法的多目标设计电力系统稳定器整定

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摘要

In order to achieve the optimal design based on some specific criteria by applying conventional techniques, sequence of design, selected locations of PSSs are critical involved factors. This paper presents a method to simultaneously tune PSSs in multimachine power system using hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel micro-GA) based on multiobjective function comprising the damping ratio, damping factor and number of PSSs. First, the problem of selecting proper PSS parameters is converted to a simple multiobjective optimization problem. Then, the problem is solved by a parallel micro GA based on HGA. The stabilizers are tuned to simultaneously shift the lightly damped and undamped oscillation modes to a specific stable zone in the s-plane and to self identify the appropriate choice of PSS locations by using eigenvalue-based multiobjective function. Many scenarios with different operating conditions have been included in the process of simultaneous tuning so as to guarantee the robustness and their performance. A 68-bus and 16-generator power system has been employed to validate the effectiveness of the proposed tuning method.
机译:为了通过应用常规技术,基于设计顺序,PSS的选定位置,是基于某些特定标准实现最佳设计的关键因素。本文提出了一种基于多目标函数的分层遗传算法(HGA)和并行微遗传算法(parallel micro-GA)同时调整多机电力系统中PSS的方法,该方法包括阻尼比,阻尼因子和PSS数量。首先,选择合适的PSS参数的问题被转换为简单的多目标优化问题。然后,通过基于HGA的并行微型GA解决了该问题。调整稳定器可同时将轻微阻尼和未阻尼的振荡模式转移到s平面中的特定稳定区域,并通过使用基于特征值的多目标函数自行确定PSS位置的适当选择。同步调整过程中已包含许多具有不同操作条件的方案,以确保其鲁棒性和性能。 68总线和16发电机的电力系统已被用来验证所提出的调整方法的有效性。

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