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PMU-Based System Identification for Wide Area Robust PSS Design in Interconnected Power Systems with Wind Farm

机译:基于PMU的系统识别用于风电场互联电力系统中的广域鲁棒PSS设计

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摘要

Itis well known that the penetration of wind power in the smart power grids not only causes the power fluctuation problem, but also results in the system instability. To tackle this problem, a sophisticated design of robust power system stabilizer (PSS) based on system identification using multiple synchronized phasor measurement units (PMUs) is proposed. The small load fluctuation is applied to the system in order to generate the phasor data measured from multiple PMUs which are assumed to be located in the system. Applying the least square method, the phasor data are used to identify the coupled vibration model (CVM) which represents the dominant inter-area oscillation modes. The CVM is used to design the PSS which is a 2~(nd) -order lead-lag compensator. To take system uncertainties such as variation of system parameters etc., in the CVM, the inverse additive perturbation model is applied. Based on an enhancement of the robust stability margin and damping effect, the PSS parameters optimization problem is formulated. The genetic algorithm is used to solve the problem and achieve the PSS parameters. The performance and robustness of the proposed PSS are evaluated in the 1EEJ Western Japan 10 machine power system with wind farm in comparison with a conventional PSS.
机译:众所周知,风电在智能电网中的渗透不仅会引起电力波动问题,还会导致系统不稳定。为了解决这个问题,提出了一种基于鲁棒电力系统稳定器(PSS)的复杂设计,该系统基于使用多个同步相量测量单元(PMU)的系统识别。将较小的负载波动应用于系统,以生成从假定位于系统中的多个PMU测量的相量数据。应用最小二乘法,将相量数据用于识别代表主要区域间振荡模式的耦合振动模型(CVM)。 CVM用于设计PSS,它是2阶超前滞后补偿器。为了考虑系统不确定性,例如系统参数的变化等,在CVM中,应用了逆加性摄动模型。在增强鲁棒稳定性裕度和阻尼效果的基础上,提出了PSS参数优化问题。遗传算法用于解决该问题并获得PSS参数。与传统PSS相比,在带有风电场的1EEJ Western Japan 10机器动力系统中评估了拟议PSS的性能和鲁棒性。

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