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Power Converter Control Applications in Low-Inertia Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (10 June 2023) | Viewed by 25422

Special Issue Editors


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Guest Editor
Department of Electrical Sustainable Energy, Delft University of Technology (TU Delft), 2628 CD Delft, The Netherlands
Interests: power system control and dynamics; integration of renewable based generation; automatic generation control; power converter application in the power system; optimal control; heuristic algorithms applied to power systems

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Guest Editor
Department of Electrical Sustainable Energy, Delft University of Technology (TU Delft), 2628 CD Delft, The Netherlands
Interests: modeling power and energy systems; digital controls; digital transformation of the power system; numerical (co-)simulation; cyberphysical energy systems
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Electrical Sustainable Energy, Delft University of Technology (TU Delft), 2628 CD Delft, Netherlands
Interests: circuit theory; multiport power system analysis; HVDC-based systems; harmonic stability assessment of the hybrid power systems consisting of the passive and active components; impedance-based MMC and other VSC modeling; nonlinear controlling methods

Special Issue Information

Dear Colleagues,

As power electronic (PE) interfaced generation (PEIG) and load (PEIL) behave differently than conventional generation and load, it is of importance to study the possible impact of different types of PE-based energy sources in low-inertia power systems. In most research projects, control and optimization of high shared PE-based generation with different types of energy sources is considered as an immediate challenge of the future power grid.

Technological advances, such as the use of modern power electronic systems, energy storage, intelligence-based methods, and advanced control techniques in power systems, as well as the large-scale penetration of renewable energy sources, have led to a reformulation of the conventional power systems, moving toward a more flexible scheme. Wind and photovoltaic systems together with hybrid energy storage systems (HESS) are among the main technologies that are expected to become essential in future power systems. Embedding HESS to the modern power system will offer a bigger degree of freedom by applying advanced control concepts that are resilient and affordable with flexible operational capabilities.

Potential topics include, but are not limited to:

  • Advanced control methodologies with dynamic stability assessment of low-inertia systems;
  • Co-simulation and hardware-in-the-loop simulations for low-inertia systems;
  • Flexible control algorithms for power electronics in AC/DC networks;
  • Different control methodologies for providing virtual inertia;
  • Wind power and energy storage integration.

Dr. Elyas Rakhshani
Prof. Peter Palensky
Dr. Aleksandra Lekić
Guest Editors

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Keywords

  • Control of AC/DC interconnected power systems
  • Power converter control application
  • Renewable energy integration
  • Energy storage applications
  • Low inertia power systems
  • Frequency control
  • Demand response
  • Control systems
  • Inertia emulation

Published Papers (11 papers)

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Research

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19 pages, 1889 KiB  
Article
Flexible Smart Energy-Management Systems Using an Online Tendering Process Framework for Microgrids
by Mansour Selseleh Jonban, Luis Romeral, Elyas Rakhshani and Mousa Marzband
Energies 2023, 16(13), 4914; https://doi.org/10.3390/en16134914 - 24 Jun 2023
Cited by 1 | Viewed by 879
Abstract
Currently, modern power grids are evolving into complex cyber-physical systems integrated with distributed energy resources that can be controlled and monitored by computer-based algorithms. Given the increasing prevalence of artificial intelligence algorithms, it is essential to explore the possibility of energy management in [...] Read more.
Currently, modern power grids are evolving into complex cyber-physical systems integrated with distributed energy resources that can be controlled and monitored by computer-based algorithms. Given the increasing prevalence of artificial intelligence algorithms, it is essential to explore the possibility of energy management in microgrids by implementing control methodologies with advanced processing centers. This study proposes a novel smart multi-agent-based framework under a tendering process framework with a bottom-up approach to control and manage the flow of energy into a grid-connected microgrid (MG). The tendering organization in this structure as an upstream agent allocates demand among generators, creates a balance between supply and demand, and provides optimal energy cost for the MG. To optimize the electricity cost and decrease the use of grid power, the first-price sealed-bid (FPSB) algorithm is implemented over the tendering process. The proposed approach from one side optimally allocates energy among generators, and, from the other side, guarantees the system from blackouts. Theoretical analysis and results demonstrate that the proposed technique is easy to implement and provides a robust and stable control for MGs, which can guarantee energy management as well as flexible and online control. Furthermore, results show the proposed framework besides the real-time allocation of power among providers to optimize the injected power from the grid so that the total injected power by the grid is 146.92 kWh and the injected power to the grid is 214.34 kWh. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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24 pages, 10820 KiB  
Article
Hybrid Wind-Solar Power System with a Battery-Assisted Quasi-Z-Source Inverter: Optimal Power Generation by Deploying Minimum Sensors
by Matija Bubalo, Mateo Bašić, Dinko Vukadinović and Ivan Grgić
Energies 2023, 16(3), 1488; https://doi.org/10.3390/en16031488 - 02 Feb 2023
Cited by 4 | Viewed by 1458
Abstract
This paper presents a hybrid renewable energy system (RES) including wind and photovoltaic (PV) power sources. The wind energy subsystem (WES) consists of a squirrel-cage induction generator (SCIG) driven by a variable-speed wind turbine (WT) and corresponding power electronic converter, by means of [...] Read more.
This paper presents a hybrid renewable energy system (RES) including wind and photovoltaic (PV) power sources. The wind energy subsystem (WES) consists of a squirrel-cage induction generator (SCIG) driven by a variable-speed wind turbine (WT) and corresponding power electronic converter, by means of which a speed-sensorless indirect-rotor-field-oriented control of the SCIG is implemented. The outputs of both the WES and PV power source rated 1.5 kW and 3.5 kW, respectively, are connected to the DC bus, with the quasi-Z-source inverter (qZSI) acting as an interlinking converter between the DC bus and the AC grid/load. An advanced pulse-width-modulation scheme is applied to reduce the qZSI switching losses. The considered RES can operate both in grid-tie and island operation, whereas the battery storage system—integrated within the qZSI impedance network—enables more efficient energy management. The proposed control scheme includes successively executed algorithms for the optimization of the WES and PV power outputs under varying atmospheric conditions. A perturb-and-observe PV optimization algorithm is executed first due to the significantly faster dynamics and higher-rated power of the PV source compared to the WES. The WES optimization algorithm includes two distinct fuzzy logic optimizations: one for extraction of the maximum wind power and the other for minimization of the SCIG losses. To reduce the number of the required sensors, all three MPPT algorithms utilize the same input variable—the qZSI’s input power—thus increasing the system’s reliability and reducing the cost of implementation. The performance of the proposed hybrid RES was experimentally evaluated over wide ranges of simulated atmospheric conditions in both the island and grid-tie operation. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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24 pages, 6177 KiB  
Article
Recurrent Convolutional Neural Network-Based Assessment of Power System Transient Stability and Short-Term Voltage Stability
by Estefania Alexandra Tapia, Delia Graciela Colomé and José Luis Rueda Torres
Energies 2022, 15(23), 9240; https://doi.org/10.3390/en15239240 - 06 Dec 2022
Cited by 4 | Viewed by 1655
Abstract
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental importance for the operation security of power systems. Both phenomena can be mutually influenced in weak power systems due to the proliferation of power electronic interface devices and the phase-out of [...] Read more.
Transient stability (TS) and short-term voltage stability (STVS) assessment are of fundamental importance for the operation security of power systems. Both phenomena can be mutually influenced in weak power systems due to the proliferation of power electronic interface devices and the phase-out of conventional heavy machines (e.g., thermal power plants). There is little research on the assessment of both types of stability together, despite the fact that they develop over the same short-term period, and that they can have a major influence on the overall transient performance driven by large electrical disturbances (e.g., short circuits). This work addresses this open research challenge by proposing a methodology for the joint assessment of TS and STVS. The methodology aims at estimating the resulting short-term stability state (STSS) in stable, or unstable conditions, following critical events, such as the synchronism loss of synchronous generators (SG) or the stalling of induction motors (IM). The estimations capture the mechanisms responsible for the degradations of TS and STVS, respectively. The paper overviews the off-line design of the data-driven STSS classification methodology, which supports the design and training of a hybrid deep neural network RCNN (recurrent convolutional neural network). The RCNN can automatically capture spatial and temporal features from the power system through a time series of selected physical variables, which results in a high estimation degree for STSS in real-time applications. The methodology is tested on the New England 39-bus system, where the results demonstrate the superiority of the proposed methodology over other traditional and deep learning-based methodologies. For reference purposes, the numerical tests also illustrate the classification performance in special situations, when the training is performed by exclusively using measurements from generation and motor load buses, which constitute locations where the investigated stability can be observed. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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18 pages, 15267 KiB  
Article
Obtaining Robust Performance of a Current fed Voltage Source Inverter for Virtual Inertia Response in a Low Short Circuit Ratio Condition
by Clint Z. Ally and Erik C. W. de Jong
Energies 2021, 14(17), 5546; https://doi.org/10.3390/en14175546 - 05 Sep 2021
Viewed by 1805
Abstract
Low inertia levels are typical in island power systems due to the relatively small rotational generation. Displacing rotational generation units with static inertia-less PV power results in a significant increase in the frequency volatility. Virtual inertia provided by inverter-storage systems can resolve this [...] Read more.
Low inertia levels are typical in island power systems due to the relatively small rotational generation. Displacing rotational generation units with static inertia-less PV power results in a significant increase in the frequency volatility. Virtual inertia provided by inverter-storage systems can resolve this issue. However, a low short circuit ratio (SCR) at the point of common coupling together with a fast phase locked loop (PLL) will compromise the response performance of the system. To address this issue, a robust PI controller (RPI) for the inner current-loop of a current fed grid-connected inverter is proposed. The PLL disturbance and grid impedance are incorporated into a single model and recast to a generalized representation of the system, thereby allowing easy tuning of the RPI by the mixed sensitivity H method. The performance of the RPI is compared with that of a PI controller (PI) tuned by the regular loop-shaping method. The results show that when the SCR is above 10, the performance of both controllers is equivalent. However, lowering of the SCR compromises the performance of the system with PI and it becomes underdamped at SCR < 2. On the contrary, the system with the RPI is capable of maintaining the nominal performance throughout the same SCR decrease. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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26 pages, 14738 KiB  
Article
Microsecond Enhanced Indirect Model Predictive Control for Dynamic Power Management in MMC Units
by Ajay Shetgaonkar, Aleksandra Lekić, José Luis Rueda Torres and Peter Palensky
Energies 2021, 14(11), 3318; https://doi.org/10.3390/en14113318 - 05 Jun 2021
Cited by 9 | Viewed by 2504
Abstract
The multi-modular converter (MMC) technology is becoming the preferred option for the increased deployment of variable renewable energy sources (RES) into electrical power systems. MMC is known for its reliability and modularity. The fast adjustment of the MMC’s active/reactive powers, within a few [...] Read more.
The multi-modular converter (MMC) technology is becoming the preferred option for the increased deployment of variable renewable energy sources (RES) into electrical power systems. MMC is known for its reliability and modularity. The fast adjustment of the MMC’s active/reactive powers, within a few milliseconds, constitutes a major research challenge. The solution to this challenge will allow accelerated integration of RES, without creating undesirable stability issues in the future power system. This paper presents a variant of model predictive control (MPC) for the grid-connected MMC. MPC is defined using a Laguerre function to reduce the computational burden. This is achieved by reducing the number of parameters of the MMC cost function. The feasibility and effectiveness of the proposed MPC is verified in the real-time digital simulations. Additionally, in this paper, a comparison between an accurate mathematical and real-time simulation (RSCAD) model of an MMC is given. The comparison is done on the level of small-signal disturbance and a Mean Absolute Error (MAE). In the MMC, active and reactive power controls, AC voltage control, output current control, and circulating current controls are implemented, both using PI and MPC controllers. The MPC’s performance is tested by the small and large disturbance in active and reactive powers, both in an offline and online simulation. In addition, a sensitivity study is performed for different variables of MPC in the offline simulation. Results obtained in the simulations show good correspondence between mathematical and real-time analytical models during the transient and steady-state conditions with low MAE. The results also indicate the superiority of the proposed MPC with the stable and fast active/reactive power support in real-time simulation. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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31 pages, 11663 KiB  
Article
Electromechanical Design of Synchronous Power Controller in Grid Integration of Renewable Power Converters to Support Dynamic Stability
by Mostafa Abdollahi, Jose Ignacio Candela, Andres Tarraso, Mohamed Atef Elsaharty and Elyas Rakhshani
Energies 2021, 14(8), 2115; https://doi.org/10.3390/en14082115 - 10 Apr 2021
Cited by 1 | Viewed by 2030
Abstract
Nowadays, modern power converters installed in renewable power plants can provide flexible electromechanical characteristics that rely on the developed control technologies such as Synchronous Power Controller (SPC). Since high renewable penetrated power grids result in a low-inertia system, this electromechanical characteristic provides support [...] Read more.
Nowadays, modern power converters installed in renewable power plants can provide flexible electromechanical characteristics that rely on the developed control technologies such as Synchronous Power Controller (SPC). Since high renewable penetrated power grids result in a low-inertia system, this electromechanical characteristic provides support to the dynamic stability of active power and frequency in the power generation area. This goal can be achieved through the proper tuning of virtual electromechanical parameters that are embedded in the control layers of power converters. In this paper, a novel mathematical pattern and strategy have been proposed to adjust dynamic parameters in Renewable Static Synchronous Generators controlled by SPC (RSSG-SPC). A detailed dynamic modeling was obtained for a feasible design of virtual damping coefficient and virtual moment of inertia in the electrometrical control layer of RSSG-SPC’s power converters. Mathematical solutions, modal analysis outcomes, time-domain simulation results, and real-time validations of the test in IEEE-14B benchmark confirm that the proposed method is an effective procedure for the dynamic design of RSSG-SPC to provide these dynamic stability supports in grid connection. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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15 pages, 6115 KiB  
Article
Hybrid Islanding Detection Method of Photovoltaic-Based Microgrid Using Reference Current Disturbance
by Reza Bakhshi-Jafarabadi and Marjan Popov
Energies 2021, 14(5), 1390; https://doi.org/10.3390/en14051390 - 03 Mar 2021
Cited by 10 | Viewed by 2061
Abstract
This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an [...] Read more.
This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d-axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms without false tripping during non-islanding incidents. In addition to the precise and fast islanding classification, the presented scheme is realized inexpensively; its thresholds are determined self-standing, and its output power quality degradation is eminently small. Moreover, the active power output is restored to the nominal set after islanding recognition, enhancing the chance of GCPVS generation at its highest possible level in the autonomous microgrid. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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20 pages, 1554 KiB  
Article
Adaptive Control of HVDC Links for Frequency Stability Enhancement in Low-Inertia Systems
by Jelena Stojković, Aleksandra Lekić and Predrag Stefanov
Energies 2020, 13(23), 6162; https://doi.org/10.3390/en13236162 - 24 Nov 2020
Cited by 6 | Viewed by 1930
Abstract
Decarbonization of power systems has put Renewable Energy Sources (RES) at the forefront when it comes to electric power generation. The increasing shares of converter-connected renewable generation cause a decrease of the rotational inertia of the Electric Power System (EPS), and consequently deteriorate [...] Read more.
Decarbonization of power systems has put Renewable Energy Sources (RES) at the forefront when it comes to electric power generation. The increasing shares of converter-connected renewable generation cause a decrease of the rotational inertia of the Electric Power System (EPS), and consequently deteriorate the system capability to withstand large load-generation imbalances. Low-inertia systems are subjected to fast and large frequency changes in case of in-feed loss, where the traditional primary frequency control is not sufficient to preserve the frequency stability and to maintain the frequency above the critical value. One possible solution to this rising problem is seen in Fast Frequency Response (FFR) provided by the High-Voltage Direct-Current (HVDC)-based systems. This paper presents the adaptive FFR control of HVDC-based systems for frequency stability enhancement in the low-inertia system. The EPS is considered as a “black box” and the HVDC response is determined only using the locally measured frequency change. Sliding Mode Control (SMC) of the Modular Multilevel Converter (MMC) was developed and demonstrated to provide faster and more appropriate frequency response compared to the PI controller. The described adaptive HVDC control considers the size of disturbance and the inertia of the power system, and it is verified by simulations on the IEEE 39 bus test system implemented in MATLAB/Simulink for different system configurations and different sizes of disturbance. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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24 pages, 803 KiB  
Article
Effects of Cyber Attacks on AC and High-Voltage DC Interconnected Power Systems with Emulated Inertia
by Kaikai Pan, Jingwei Dong, Elyas Rakhshani and Peter Palensky
Energies 2020, 13(21), 5583; https://doi.org/10.3390/en13215583 - 26 Oct 2020
Cited by 9 | Viewed by 2213
Abstract
The high penetration of renewable energy resources and power electronic-based components has led to a low-inertia power grid which would bring challenges to system operations. The new model of load frequency control (LFC) must be able to handle the modern scenario where controlled [...] Read more.
The high penetration of renewable energy resources and power electronic-based components has led to a low-inertia power grid which would bring challenges to system operations. The new model of load frequency control (LFC) must be able to handle the modern scenario where controlled areas are interconnected by parallel AC/HVDC links and storage devices are added to provide virtual inertia. Notably, vulnerabilities within the communication channels for wide-area data exchange in LFC loops may make them exposed to various cyber attacks, while it still remains largely unexplored how the new LFC in the AC/HVDC interconnected system with emulated inertia would be affected under malicious intrusions. Thus, in this article, we are motivated to explore possible effects of the major types of data availability and integrity attacks—Denial of Service (DoS) and false data injection (FDI) attacks—on such a new LFC system. By using a system-theoretic approach, we explore the optimal strategies that attackers can exploit to launch DoS or FDI attacks to corrupt the system stability. Besides, a comparison study is performed to learn the impact of these two types of attacks on LFC models of power systems with or without HVDC link and emulated inertia. The simulation results on the the exemplary two-area system illustrate that both DoS and FDI attacks can cause large frequency deviations or even make the system unstable; moreover, the LFC system with AC/HVDC interconnections and emulated inertia could be more vulnerable to these two types of attacks in many adversarial scenarios. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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Review

Jump to: Research

18 pages, 1400 KiB  
Review
Review of Impedance-Based Analysis Methods Applied to Grid-Forming Inverters in Inverter-Dominated Grids
by Ishita Ray
Energies 2021, 14(9), 2686; https://doi.org/10.3390/en14092686 - 07 May 2021
Cited by 16 | Viewed by 3891
Abstract
As the use of distributed generation with power electronics-based interfaces increases, the separation between DC and AC parts of the grid is reduced. In such inverter-dominated AC grids, impedance-based analysis methods are proving to be more powerful than traditional state-space-based analysis methods. Even [...] Read more.
As the use of distributed generation with power electronics-based interfaces increases, the separation between DC and AC parts of the grid is reduced. In such inverter-dominated AC grids, impedance-based analysis methods are proving to be more powerful than traditional state-space-based analysis methods. Even the conventional parameters and standards used to estimate the stability of generators and stronger grids cannot fully capture the dynamics of weaker, inverter-dominated grids. It then stands to reason that system impedances that are commonly used to analyze DC systems will be useful in the analysis of grid-forming inverters in these hybrid systems. To understand the value of studying the impedances of inverters and other elements in weak AC grids, this article reviews and describes the various ways in which impedance-based analyses can be used to define, assess, and improve the performance of grid-forming inverter controllers. An exemplary case using the conventional P-f/Q-V droop control demonstrates the application of impedance-based analyses to determine the impact of the controller on the input and output stability of the inverter. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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12 pages, 3638 KiB  
Review
A Power Hardware-in-the-Loop Based Method for FAPR Compliance Testing of the Wind Turbine Converters Control
by Zameer Ahmad, Jose Rueda Torres, Nidarshan Veera Kumar, Elyas Rakhshani, Peter Palensky and Mart van der Meijden
Energies 2020, 13(19), 5203; https://doi.org/10.3390/en13195203 - 06 Oct 2020
Cited by 11 | Viewed by 2473
Abstract
A task for new power generation technologies, interfaced to the electrical grid by power electronic converters, is to stiffen the rate of change of frequency (RoCoF) at the initial few milliseconds (ms) after any variation of active power balance. This task is defined [...] Read more.
A task for new power generation technologies, interfaced to the electrical grid by power electronic converters, is to stiffen the rate of change of frequency (RoCoF) at the initial few milliseconds (ms) after any variation of active power balance. This task is defined in this article as fast active power regulation (FAPR), a generic definition of the FAPR is also proposed in this study. Converters equipped with FAPR controls should be tested in laboratory conditions before employment in the actual power system. This paper presents a power hardware-in-the-loop (PHIL) based method for FAPR compliance testing of the wind turbine converter controls. The presented PHIL setup is a generic test setup for the testing of all kinds of control strategies of the grid-connected power electronic converters. Firstly, a generic PHIL testing methodology is presented. Later on, a combined droop- anFd derivative-based FAPR control has been implemented and tested on the proposed PHIL setup for FAPR compliance criteria of the wind turbine converters. The compliance criteria for the FAPR of the wind turbine converter controls have been framed based on the literature survey. Improvement in the RoCoF and and maximum underfrequency deviation (NADIR) has been observed if the wind turbine converter controls abide by the FAPR compliance criteria. Full article
(This article belongs to the Special Issue Power Converter Control Applications in Low-Inertia Power Systems)
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