Online Estimation of Power System Inertia Using Dynamic Regressor Extension and Mixing

Abstract

The increasing penetration of power-electronicinterfaced devices is expected to have a significant effect on the overall system inertia and a crucial impact on the system dynamics. In the future, the reduction of inertia will have drastic consequences on protection and real-time control and will play a crucial role in the system operation. Therefore, in a highly deregulated and uncertain environment, it is necessary for Transmission System Operators to be able to monitor the system inertia in real time. We address this problem by developing and validating an online inertia estimation algorithm. The estimator is derived using the recently proposed dynamic regressor and mixing procedure. The performance of the estimator is demonstrated via several test cases using the 1013-machine ENTSO-E dynamic model.Index Terms-Power system inertia, power system dynamics, power system stability, low-inertia systems, parameter estimation. J. Schiffer is with Brandenburgische

On parameter tuning and convergence properties of the DREM procedure

“…From (18) and (19) it follows that if ∆ is PE, then the signal t → p i (t)∆(t) is bounded and PE as well. Therefore the exponential convergence ofθ follows from (13). Moreover, the convergence is monotonic since p i (t)∆ 2 (t) ≥ 0, ∀t ≥ 0.…”

“…In [9], the authors propose an interpretation of this procedure as a functional Luenberger observer. The DREM approach has been successfully applied to a variety of adaptive control problems and applications, such as direct model reference control [10], time-varying frequency estimation [11], electrical drives velocity estimation [12], and power system applications [13], [14]. Among many, the DREM procedure has the following advantages:…”

Local Frequency-Based Estimation of the Rate of Change of Frequency of the Center of Inertia

“…The swing equation can be used to estimate the size of active power deficit following an LoG event. This would need the knowledge of the aggregate system inertia [5], [6], in addition to a reliable communication network for transmitting measured generator frequencies to the control center. If such a communication network was already available, it would be much straightforward and easier to directly monitor active power injected by every generator and/or the status of the corresponding circuit breakers in order to detect LoG events.…”

PMU‐based decentralised mixed algebraic and dynamic state observation in multi‐machine power systems

“…In this setting, our main contributions are three‐fold: We propose a decentralised algebraic observer for the load angle and quadrature‐axis internal voltage using only the measurements provided via PMUs at the terminal buses. To establish this result, we assume that the direct‐axis transient reactance and quadrature‐axis reactance are equal. A certainty equivalent adaptive observer for the relative shaft speed is designed by combining the classical immersion and invariance (I&I) technique [15] with the recently introduced dynamic regressor extension and mixing (DREM) procedure [26], which has been successfully applied to several engineering problems [27–29]. This observer is decentralised, does not require any prior knowledge on the system, and its convergence is ensured via very weak excitation assumptions. The effectiveness of the proposed DSE technique is demonstrated in extensive simulations based on the New England IEEE‐39 bus system [30].…”