The electric power system is a complicated dynamic system with a range of operating states and parametric uncertainties, especially due to change of the network topology, load increment and generation scheduling. Under this circumstance, traditional power system transient stability analysis methods may not always be appropriate. This paper presents the development of a computational methodology for evaluating the effect of parametric uncertainties on the small-signal stability analysis of power systems. A probabilistic approach is applied as a metric for the dynamic performance of the damping ratio of critical eigenvalues. The method is based on a Monte Carlo simulation for the analysis of automatic control of generation. The methodology is used for the performance evaluation of three classical controller tuning techniques: Frequency Response, Approximate Method and Ziegler-Nichols. The results show that the methodology is valid and potentially useful for quantifying the effect of parametric uncertainties in power systems dynamics simulations.

中文翻译：

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具有参数不确定性的电力系统小扰动角稳定性控制器设计的性能


电力系统是一个复杂的动态系统，具有多种运行状态和参数不确定性，特别是由于网络拓扑、负荷增量和发电调度的变化。在这种情况下，传统的电力系统暂态稳定分析方法可能并不总是合适的。本文介绍了一种计算方法的开发，用于评估参数不确定性对电力系统小信号稳定性分析的影响。应用概率方法作为临界特征值阻尼比动态性能的度量。该方法基于蒙特卡罗模拟来分析发电的自动控制。该方法用于评估三种经典控制器调谐技术的性能：频率响应、近似方法和齐格勒-尼科尔斯。结果表明，该方法是有效的，并且对于量化电力系统动力学仿真中参数不确定性的影响可能有用。