A Framework for Assessing Renewable Integration Limits With Respect to Frequency Performance

Ahmadyar, Ahmad Shabir; Riaz, Shariq; Verbič, Gregor; Chapman, Archie C.; Hill, David J.

doi:10.1109/tpwrs.2017.2773091

Cited by 72 publications

(48 citation statements)

References 21 publications

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“…The opportunities offered by demand side resources have also been recognized by the Australian Energy Market Commission [197], who argue that consumers with PV-battery systems can provide network support and ancillary services that were traditionally confined to the domain of large generators. Indeed, [198], [199] showed that a high penetration of prosumers, consumers equipped with rooftop solar and battery storage, changes the demand profile in ways that significantly improve the system loadability [198] and frequency performance [199].…”

Section: Distributed Controlmentioning

confidence: 99%

“…As an alternative to "system theoretic" approaches for inertia placement described in Section-IV-D, [199] proposes a computational scenario-based sensitivity analysis to asses the renewable integration limits with respect to frequency performance. While "system theoretic" approaches provide theoretically proven performance guarantees, they come with their own limitations.…”

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

“…Finally, the problem of optimal inertia placement cannot be separated from market dispatch given that the ability of an inverter-interfaced generator depends on its current dispatch level, which, in turn, depends on the market dispatch, as demonstrated in [199]. In addition to that, if prosumers are used as a source of flexibility [198], [199] including them in system dispatch is important. To account for a wide range of possible future evolutions, [199] uses scenario-based sensitivity analysis, which provides a systematic approach to capture the impact of a wide range of emerging technologies on the behavior of future grids.…”

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

See 3 more Smart Citations

Foundations and Challenges of Low-Inertia Systems (Invited Paper)

Milano

Dörfler

Hug

et al. 2018

2018 Power Systems Computation Conference (PSCC)

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608

504

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The electric power system is currently undergoing a period of unprecedented changes. Environmental and sustainability concerns lead to replacement of a significant share of conventional fossil fuel-based power plants with renewable energy resources. This transition involves the major challenge of substituting synchronous machines and their well-known dynamics and controllers with power electronics-interfaced generation whose regulation and interaction with the rest of the system is yet to be fully understood. In this article, we review the challenges of such low-inertia power systems, and survey the solutions that have been put forward thus far. We strive to concisely summarize the laidout scientific foundations as well as the practical experiences of industrial and academic demonstration projects. We touch upon the topics of power system stability, modeling, and control, and we particularly focus on the role of frequency, inertia, as well as control of power converters and from the demand-side.

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Section: Distributed Controlmentioning

confidence: 99%

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

Section: F Integration Studies 1) Pmu-based Monitoring and Forecastingmentioning

confidence: 99%

See 2 more Smart Citations

Foundations and Challenges of Low-Inertia Systems (Invited Paper)

Milano

Dörfler

Hug

et al. 2018

2018 Power Systems Computation Conference (PSCC)

Self Cite

608

504

View full text Add to dashboard Cite

show abstract

“…Many issues of power system stability have been well studied in recent decades through mathematical analysis and computational techniques [2]- [11]. However, many of the underlying assumptions and models must be called into question in the context of low-and variable-inertia power systems.…”

Section: Introductionmentioning

confidence: 99%

A Performance and Stability Analysis of Low-inertia Power Grids with Stochastic System Inertia

Guo

Summers

2019

2019 American Control Conference (ACC)

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Traditional synchronous generators with rotational inertia are being replaced by low-inertia renewable energy resources (RESs) in many power grids and operational scenarios. Due to emerging market mechanisms, inherent variability of RESs, and existing control schemes, the resulting system inertia levels can not only be low but also markedly time-varying. In this paper, we investigate performance and stability of low-inertia power systems with stochastic system inertia. In particular, we consider system dynamics modeled by a linearized stochastic swing equation, where stochastic system inertia is regarded as multiplicative noise. The H2 norm is used to quantify the performance of the system in the presence of persistent disturbances or transient faults. The performance metric can be computed by solving a generalized Lyapunov equation, which has fundamentally different characteristics from systems with only additive noise. For grids with uniform inertia and damping parameters, we derive closed-form expressions for the H2 norm of the proposed stochastic swing equation. The analysis gives insights into how the H2 norm of the stochastic swing equation depends on 1) network topology; 2) system parameters; and 3) distribution parameters of disturbances. A mean-square stability condition is also derived. Numerical results provide additional insights for performance and stability of the stochastic swing equation.

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Virtual generator‐based damping controller for microgrids with low inertia resources based on energy storage systems

Roudi

Ebrahimi

Ghanbari

et al. 2021

Int Trans Electr Energ Syst

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Summary In this paper, an adaptive concept of virtual generator (VG)‐based controller is presented for dynamic stability of stochastically‐modeled microgrids consisting of low inertia resources. For this purpose, considering a set of energy storage systems (ESSs) dispatched in the network, a controlled islanding scheme (CIS) is provided to dynamically control the microgrid frequency. In this context, based on the concept of center of inertia (COI), the proposed VG scheme is developed through mathematical formulation. Inter‐area torques evaluated by microgrid control areas in the COI frame are used as input signals of the developed VG‐based controller. Also, for the ESSs, an equivalent dispatch model is provided and developed through the microgrid dynamic model for improving frequency stability during inter‐area oscillations. The proposed VG‐based controller is an online and non‐model‐based scheme which controls several microgrid systems together as an integrated network connected to the upstream network. In order to evaluate the ability of the proposed scheme, real‐time simulations are carried out on two different test systems consisting of several microgrids. The system dynamic performances are evaluated in time‐domain simulations. Numerical results demonstrate the effectiveness of the proposed scheme in increasing system inertia constant resulting in a proper dynamic performance with a high damping ratio in facing severe inter‐area oscillations.

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A Framework for Assessing Renewable Integration Limits With Respect to Frequency Performance

Cited by 72 publications

References 21 publications

Foundations and Challenges of Low-Inertia Systems (Invited Paper)

Foundations and Challenges of Low-Inertia Systems (Invited Paper)

A Performance and Stability Analysis of Low-inertia Power Grids with Stochastic System Inertia

Virtual generator‐based damping controller for microgrids with low inertia resources based on energy storage systems

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