ARMAX-based method for inertial constant estimation of generation units using synchrophasors

Lugnani, Lucas; Dotta, Daniel; Lackner, Christoph; Chow, Joe H.

doi:10.1016/j.epsr.2019.106097

Cited by 43 publications

(14 citation statements)

References 9 publications

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“…Specifically, ARMAX modelling is applied to a short window length close to the inertial response period (see Fig. 7), to minimize the impact of additional system dynamics, e.g., caused by frequency control systems and inter-area oscillations [57]. The total window length includes pre-and post-disturbance data of length B 1 and B 2 , respectively, as shown in Fig.…”

Section: Frequency Response Analysismentioning

confidence: 99%

A Three-Level Distributed Architecture for the Real-Time Monitoring of Modern Power Systems

2022

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Section: Frequency Response Analysismentioning

confidence: 99%

A Three-Level Distributed Architecture for the Real-Time Monitoring of Modern Power Systems

2022

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“…In [18], an approach that accommodates frequency and voltage variations through curve-fitting is proposed, but accuracy highly depend on the percentage of generating units monitored. In [19], the inertia of an area as perceived by a particular bus of the system is evaluated through an autoregressive moving average exogenous input model, but in all testes, generators are assumed as monitored.…”

Section: Introductionmentioning

confidence: 99%

A Perturbation-Based Methodology to Estimate the Equivalent Inertia of an Area Monitored by PMUs

et al. 2021

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This paper proposes a novel methodology to estimate equivalent inertia of an area, observed from its boundary buses where Phasor Measurement Units (PMUs) are assumed to be installed. The areas are divided according to the measurement points, and the methodology proposed can obtain the equivalent dynamic response of the area dependent of or independent of coherency of the generators inside, which is the first contribution of this paper. The methodology is divided in three parts: estimating the frequency response, estimating the power imbalance and estimating inertia through the solution of the swing equation by Least-Squares Method (LSM). The estimation of the power imbalance is the second contribution of this paper, enabling the study of areas that contain perturbations and attending the limitation of methods of the literature that rely on assumptions of slow mechanical power. It can be further divided in three steps: accounting the total power injected, estimating an equivalent load behavior and estimating an equivalent mechanical power. The quality of results is proved with test systems of different sizes, simulating different types of perturbations.

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“…The proposed method again uses the swing equation as the basis to determine the inertia constant. Similarly, in [16], online inertia estimation based on an auto-regressive moving average exogenous (ARMAX) input model is proposed. However, the method requires the data to be collected over a certain time-period (30 s recommended in the paper), which can introduce significant delays in the estimate.…”

Section: Introductionmentioning

confidence: 99%

“…In [17], system identification techniques relying on ambient frequency measurements are proposed. However, techniques that depend on ambient frequency measurements may be unable to distinguish between voltage and frequency dynamics and even other electro-mechanical dynamics in the power system [16]. In [18], online identification of inertia response of a system is performed by using a system identification approach on PMU recordings.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Estimation of Microgrid Inertia and Damping Constant

et al. 2021

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The displacement of rotational generation and the consequent reduction in system inertia is expected to have major stability and reliability impacts on modern power systems. Fast-frequency support strategies using energy storage systems (ESSs) can be deployed to maintain the inertial response of the system, but information regarding the inertial response of the system is critical for the effective implementation of such control strategies. In this paper, a moving horizon estimation (MHE)-based approach for online estimation of inertia constant of low inertia microgrids is presented. Based on the frequency measurements obtained in response to a non-intrusive excitation signal from an ESS, the inertia constant was estimated using local measurements from the ESS's phase-locked loop. The proposed MHE formulation was first tested in a linearized power system model, followed by tests in a modified microgrid benchmark from Cordova, Alaska. Even under moderate measurement noise, the technique was able to estimate the inertia constant of the system well within ±20% of the true value. Estimates provided by the proposed method could be utilized for applications such as fast-frequency support, adaptive protection schemes, and planning and procurement of spinning reserves.INDEX TERMS Energy storage systems, inertia estimation, microgrids, moving horizon estimation, virtual inertia.

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ARMAX-based method for inertial constant estimation of generation units using synchrophasors

Cited by 43 publications

References 9 publications

A Three-Level Distributed Architecture for the Real-Time Monitoring of Modern Power Systems

A Three-Level Distributed Architecture for the Real-Time Monitoring of Modern Power Systems

A Perturbation-Based Methodology to Estimate the Equivalent Inertia of an Area Monitored by PMUs

Real-Time Estimation of Microgrid Inertia and Damping Constant

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