Hybrid Algorithm for Coordinated Design of PSSs and FACTS

E. Ali, S. M. A. Elazim
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Abstract

The assessment of new coordinated design of Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method is proposed in this paper. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is formulated as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to search for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is performed to ensure the effectiveness of coordinated controller versus uncoordinated one.
pss与FACTS协调设计的混合算法
本文用统计方法对多机电力系统稳定器与静态无功补偿器的新型协调设计进行了评价。将大范围载荷条件下PSSs与SVC的协同设计问题表述为优化问题。采用细菌群优化算法(BSO)将细菌觅食算法(BF)与粒子群优化算法(PSO)协同耦合,搜索最优控制器参数。通过最小化所提出的目标函数,其中涉及发电机之间的速度偏差;提高了系统的稳定性。为了比较PSS和SVC的性能,我们先对两者进行独立设计,然后再进行协调设计。与基于BSO的优化PSS控制器(BSOPSS)和基于BSO的优化SVC控制器(BSOSVC)相比,基于BSO的协调控制器在大范围工况和大扰动下具有鲁棒的阻尼性能。此外,还进行了统计T检验,以确保协调控制器与非协调控制器的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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