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Implementation of advanced genetic algorithm to modern power system stabilization control

机译:先进遗传算法对现代电力系统稳定控制的实现

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This paper focuses on the use of advanced techniques in genetic algorithm for solving power system stabilization control problems. At the outset, the proposed hierarchical genetic algorithm (HGA) and parallel micro genetic algorithm (parallel microGA) are proposed and then they will be extended to solve two example problems. In the first example, these techniques are applied to simultaneously tune power system stabilizers (PSSs). The PSSs are optimally tuned to simultaneously shift the lightly damped and undamped oscillation modes to a stable zone in the s-plane and to self identify the appropriate PSS locations. In second example, parallel microGA is used to design the fuzzy logic controller (FLC) of STATCOM. The applied technique for designing a FLC helps us save time and does not require experts for designing. From these results, we can see that these advanced techniques provide enhanced versatility for solving problems in power system stabilization control.
机译:本文侧重于利用先进技术在遗传算法中解决电力系统稳定控制问题。在开始时,提出了所提出的分层遗传算法(HGA)和并行微遗传算法(并行MicroGa),然后将它们扩展以解决两个示例问题。在第一示例中,这些技术应用于同时调谐电力系统稳定器(PSS)。 PSS被最佳地调谐以同时将轻微阻尼和未透明的振荡模式移动到S平面中的稳定区域并自动识别适当的PSS位置。在第二个示例中,并行MicroGA用于设计Statcom的模糊逻辑控制器(FLC)。设计FLC的应用技术有助于我们节省时间,不需要专家进行设计。从这些结果来看,我们可以看出,这些先进技术为解决电力系统稳定控制中的问题提供了增强的多功能性。

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