Calculate Center-of-Inertia Frequency and System RoCoF Using PMU Data

You, Shutang; Li, Hongyu; Liu, Shengyuan; Sun, Kaiqi; Wang, Weikang; Qiu, Wei; Li, Fangxing

doi:10.1109/pesgm46819.2021.9638108

Cited by 11 publications

(4 citation statements)

References 60 publications

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“…Energies 2023, 16, x FOR PEER REVIEW 15 of points, we can obtain the approximate estimated value of the CoI frequency, so that t CoI RoCoF can be obtained, accordingly. Reference [100] proposes that the CoI frequen and RoCoF of the power system can be calculated more accurately by PMU data fro multiple locations. Firstly, the equivalent inertia constant is obtained by the least squar method, and then the CoI frequency is calculated according to Equation ( 4), and t RoCoF is the first-time derivative of CoI frequency; the simulation results show that t error can be effectively reduced.…”

Section: Other Methodsmentioning

confidence: 99%

“…Equation (8) implies that the measurement device that can track the dynamic voltage/current phase at a node of the power system, namely the synchrophasor, can be used to track the real-time local RoCoF with a proper algorithm; however, RoCoF estimation techniques face great challenges in accuracy and robustness. This section provides a comprehensive review of the existing real-time RoCoF tracking algorithms of synchrophasors, which can be divided into three main categories: (i) DFTbased [64][65][66][67][68][69][70][71][72][73][74][75][76], (ii) Kalman filter techniques [77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92], and (iii) other methods [93][94][95][96][97][98][99][100]. The details for each category are provided in the subsection.…”

Section: Real-time Rocof Tracking Techniquesmentioning

confidence: 99%

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Review of RoCoF Estimation Techniques for Low-Inertia Power Systems

Deng

Wang

et al. 2023

Energies

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As the traditional generation is gradually replaced by inverter-based resources, a lack of rotational inertia is now a common issue of modern power systems, which leads to an increasingly larger rate of change of frequency (RoCoF) following contingencies and may result in frequency collapse. As a crucial index of the frequency security and stability of power systems, the accurate estimation of the RoCoF can be a foundation for the development of advanced operations and control techniques of the future power system. This paper firstly analyzes the role of the RoCoF in typical blackouts occurring in recent years and discusses the physical and numerical nature of the RoCoF; then, by introducing the frequency spatial distribution of the power system, the paper discusses the concept of the “center” RoCoF that can present the frequency security and stability of the entire system. The estimation and prediction techniques of the maximal power system RoCoF following a contingency and the existing real-time tracking techniques of the power system RoCoF are comprehensively reviewed. Finally, the open questions and related research topics of the RoCoF estimation are discussed.

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Section: Other Methodsmentioning

confidence: 99%

Section: Real-time Rocof Tracking Techniquesmentioning

confidence: 99%

Review of RoCoF Estimation Techniques for Low-Inertia Power Systems

Deng

Wang

et al. 2023

Energies

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“…For every system load level involved and every inertia reduction scenario, the single outage of generators and the step increase of loads (one at a time) were considered as sudden power imbalances. In this manner, an average frequency of the system was determined after the disturbance based on the following equation, where fCOI represents the frequency of the center of inertia [18] of the grid under study:…”

Section: A Dataset For the Studiesmentioning

confidence: 99%

Power System Inertia Estimation Using A Residual Neural Network Based Approach

Ramirez-Gonzalez

Sevilla

Korba

2022

2022 4th Global Power, Energy and Communication Conference (GPECOM)

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The increasing penetration of non-synchronous generation into power grids is reducing the equivalent system inertia and leading to different frequency regulation and control challenges. Consequently, the monitoring and quantification of this inertia to implement actions that can keep it above critical levels have become a key issue for the stability of power systems. In this regard, a residual neural network (ResNet) based alternative is proposed and investigated in this paper to estimate the equivalent inertia of a sample system when synchronous generating units are displaced by converter-interfaced generators. The proposed ResNet model is trained according to the frequency of the center of inertia and the corresponding computed rates of change of frequency for a predefined time interval, where sudden generation outages and load step changes are considered under variations of total load demand and equivalent inertia reductions. The accuracy of the proposed approach is compared against the one achieved with the application of two traditional machine learning techniques, such as Support Vector Machine and Random Forest.

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“…One of the critical challenges in power systems operation planning with high penetration of inverter-based resources (IBRs) is the decrease in system inertia, which results in a high initial rate of change of frequency (ROCOF) [1]. Furthermore, recent theoretical studies [2], [3], [4] and datadriven analyzes [5], [6], [7] have shown that inertia providers are unevenly distributed across the system, and the frequency response after a disturbance has spatial-temporal characteristics. The practical problem is the unexpected tripping of The associate editor coordinating the review of this manuscript and approving it for publication was Youngjin Kim .…”

Section: Introduction a Motivationmentioning

confidence: 99%

An Analytical Formulation for Mapping the Spatial Distribution of Nodal Inertia in Power Systems

et al. 2023

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Mapping the spatial distribution of nodal inertia is crucial for helping system operators identify locational frequency stability issues in the power system operation planning process. Currently, index-based methods cannot retrieve the nodal inertia values for all load buses. To do so, this paper proposes an accurate analytical formulation relying only on steady-state system parameters to determine the nodal inertia values and, thus, map the spatial distribution of system inertia. The performance and reproducibility of the proposed formulation are evaluated using three test systems: a 5-bus radial system with two synchronous generators, a multimachine IEEE 68-bus benchmark system, and a larger NPCC 140-bus test system. We validate the proposed spatial distribution of nodal inertia using time-domain simulations and numerical estimations. In addition, we compare our method against the inertia distribution indexes presented in the literature. The results indicate that our formulation adequately quantifies the nodal inertia value in system buses, with low computational cost, and providing a suitable tool for operation planning analysis.

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Calculate Center-of-Inertia Frequency and System RoCoF Using PMU Data

Cited by 11 publications

References 60 publications

Review of RoCoF Estimation Techniques for Low-Inertia Power Systems

Review of RoCoF Estimation Techniques for Low-Inertia Power Systems

Power System Inertia Estimation Using A Residual Neural Network Based Approach

An Analytical Formulation for Mapping the Spatial Distribution of Nodal Inertia in Power Systems

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