Online Measurement-Based Estimation of Dynamic System State Matrix in Ambient Conditions

Abstract

In this paper, a purely measurement-based method is proposed to estimate the dynamic system state matrix by applying the regression theorem of the multivariate Ornstein-Uhlenbeck process. The proposed method employs a recursive algorithm to minimize the required computational effort, making it applicable to the real-time environment. One main advantage of the proposed method is model independence, i.e., it is independent of the network model and the dynamic model of generators. Among various applications of the estimated matrix, detecting and locating unexpected network topology change is illustrated in details. Simulation studies have shown that the proposed measurement-based method can provide an accurate and efficient estimation of the dynamic system state matrix under the occurrence of unexpected topology change. Besides, various implementation conditions are tested to show that the proposed method can provide accurate approximation despite measurement noise, missing PMUs, and the implementation of higher-order generator models with control devices.Index Terms-Dynamic system state matrix, Ornstein-Uhlenbeck process, phasor measurement units, topology change.

Online Model-Free Estimation of the Dynamic System Model for a Power System With Renewables in Ambient Conditions

“…In [12], a measurement-based method has been proposed to estimate the dynamic system state matrix A o in (6). The method is developed based on an important property of Ornstein-Uhlenbeck process.…”

“…The equation (11) relates the physical model knowledge with the statistical properties of state variables, providing a ingenious way of estimating the dynamic system state matrix from measurements. More details can be found in [12]. Note that with sufficient PMU measurements, both R (τ ) and C can be estimated bŷ…”

“…However, the aforementioned method proposed in [12] does not consider the integration of distributed RES, which nevertheless is imperative and significant, considering that the growing RES are being integrated into power grids. Besides, it is not obvious that what A o in (12) becomes and how to extract A and B in (10), with the presence of distributed RES.…”

“…Step 4: Collect new PMU measurements; Estimate the closed-loop system state matrix after the perturbation by (12).…”

“…However, this method is not purely model-free as the damping and the inertia constants of generators are still needed. Recently, a purely measurement-based strategy was proposed in [12] to estimate the true dynamic system state matrix of a power system by exploiting the regression theorem of Ornstein-Uhlenbeck process. Yet the method does not consider the impacts of RES.…”