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Estimation of the Correlation Between Oscillation Modes and Operating Conditions using Quantile Regression: A Measurement-Based Approach

机译:使用分位数回归估计振荡模式和运行条件之间的相关性:基于测量的方法

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In this paper, a measurement-based approach is introduced to estimate the impact of operating conditions on the inter-area oscillations in the Western Electricity Coordinating Council (WECC) power grid using field measurement data. The correlation between oscillation modes and operating conditions is essential to ensure the grid's small-signal stability under increasing variability and uncertainty introduced by the accelerating penetration of renewable generation. Past studies have been focused on model-based methods, whose applications are limited by the model availability and accuracy. To overcome this limitation, the quantile regression method is proposed in this paper to establish a correlation model between the oscillation modes and operating conditions such as generation mix and load and tie-line flows using measurement data. To quantify the uncertainty of the correlation model, the bootstrap method is used to estimate the confidence intervals of the coefficients of the correlation model. Study results show that the high penetration of solar generation has decreased the damping ratio of a major inter-area oscillation Mode. The proposed approach is generic and can be applied to estimate other correlations using measurement data under a statistical framework.
机译:本文介绍了一种基于测量的方法,利用现场测量数据估计运行条件对西部电力协调委员会(WECC)电网区域间振荡的影响。振荡模式和运行条件之间的相关性对于确保电网在可再生能源发电加速普及带来的日益增加的可变性和不确定性下的小信号稳定性至关重要。过去的研究主要集中在基于模型的方法上,其应用受到模型可用性和准确性的限制。为了克服这一局限性,本文提出了分位数回归方法,利用测量数据建立振荡模式与运行条件(如发电组合、负荷和联络线流量)之间的相关性模型。为了量化相关模型的不确定性,使用bootstrap方法估计相关模型系数的置信区间。研究结果表明,太阳能发电的高穿透性降低了主要区域间振荡模式的阻尼比。所提出的方法是通用的,可以应用于在统计框架下使用测量数据估计其他相关性。

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