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

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.