Enhancing Frequency Response Control by DFIGs in the High Wind Penetrated Power Systems

Chang-Chien, Le-Ren; Lin, Wei‐Ting; Yin, Yao-Ching

doi:10.1109/tpwrs.2010.2052402

Cited by 203 publications

(101 citation statements)

References 20 publications

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“…Figure 9b further explains the reason is that the DFIG can provide more extra active power to support system frequency recovery, which has been clearly and directly analyzed in Section 3.2.1 based on the novel SFR model. As shown in Figure 10, two main simulation results can be observed: (1) with an increase of parameter p k (0,8,16,24), the frequency response curves coincide with each other at the initial stage (5.1-5.3 s). This means that IROCOF is insensitive to the change of parameter p k at all.…”

Section: Validation Of the Impact Of The Initial Operation Point On Tmentioning

confidence: 83%

“…As shown in Figure 10, two main simulation results can be observed: (1) with an increase of parameter k p (0, 8,16,24), the frequency response curves coincide with each other at the initial stage (5.1-5.3 s). This means that IROCOF is insensitive to the change of parameter k p at all.…”

Section: Validation Of the Impact Of The Initial Operation Point On Tmentioning

confidence: 83%

“…The literature [8] proposed a set of frequency control strategies for all wind conditions. Among them are:…”

Section: Frequency Control Strategy and Response Characteristic Of Dfigmentioning

confidence: 99%

“…(B) Medium wind condition: In this wind region, DFIG can provide sufficient reserve capacity to participate in frequency control just by rotor over-speed regulation, and the pitch angle need not take an action (fixed at minimum angle β = 0 • ) just because the rotor speed could not exceed the upper limit ω rmax . In order to make the novel SFR model derived in next section more representative, the original primary frequency control strategy in [8] is replaced by the combined inertia and primary control strategy [13][14][15][16][17] (shown in Figure 1) which is now more widely used. In addition, the reserve capacity command sent to the DFIG is set as a deloading rate d% [17] substituting for a fixed command P cmd .…”

Section: Frequency Control Strategy and Response Characteristic Of Dfigmentioning

confidence: 99%

See 3 more Smart Citations

A Low-Order System Frequency Response Model for DFIG Distributed Wind Power Generation Systems Based on Small Signal Analysis

Quan

Pan

2017

Energies

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Abstract:Integrating large amounts of wind power into power systems brings a large influence on the dynamic frequency response characteristic (DFRC). The traditional low-order system frequency response (SFR) model is no longer applicable at the current time. Based on the small signal analysis theory, a set of novel low-order SFR models for doubly-fed induction generator (DFIG) distributed wind power generation systems (DWPGS) are derived under low, medium, and high wind speed conditions, respectively. Time-domain simulations have been conducted on PSCAD/EMTDC, and the novel SFR model is tested and evaluated on a real system. The simulation results from the novel model agree with those from the detailed model. The novel SFR model can also directly show the impact of the initial wind speed and auxiliary frequency controller (AFC) parameters on DFRC, but not on the detailed model.

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Section: Validation Of the Impact Of The Initial Operation Point On Tmentioning

confidence: 83%

Section: Validation Of the Impact Of The Initial Operation Point On Tmentioning

confidence: 83%

“…The literature [8] proposed a set of frequency control strategies for all wind conditions. Among them are:…”

Section: Frequency Control Strategy and Response Characteristic Of Dfigmentioning

confidence: 99%

Section: Frequency Control Strategy and Response Characteristic Of Dfigmentioning

confidence: 99%

See 2 more Smart Citations

A Low-Order System Frequency Response Model for DFIG Distributed Wind Power Generation Systems Based on Small Signal Analysis

Quan

Pan

2017

Energies

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“…The second widely used solution is the rotational kinetic energy (KE) of WT rotor mass, which can well stabilize the grid frequency through the proper control design of the so-called emulated inertia control [14][15][16][17][18][19][20][21][22]. In general, when detecting the grid frequency excursion, the set-point of WT generation reference will be accordingly changed.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Control Schemes of Super-Capacitor and Kinetic Energy of DFIG for System Frequency Support

Xiong

Zhu

et al. 2018

Energies

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This paper mainly focuses on how to provide frequency supports by the doubly fed induction generator (DFIG) during system disturbances. Two coordinated controls that enable system frequency supports by DFIG-based wind turbines (WTs) are proposed in this paper. The first control scheme seeks to render system support via simultaneously utilizing the energy from the installed super-capacitor between the back-to-back converter of DFIG, and WT rotational kinetic energy (KE). The second one stabilizes system frequency by firstly exerting the installed super-capacitor energy and then WT rotational KE via a unique cascading control. Both proposed coordinated control schemes jointly utilize two virtual inertia sources, namely super-capacitor in the DFIG and rotor rotational mass in the WT to fast provide system frequency support. However, the second proposed one stands itself out by reducing its impaired impacts on the overall wind energy production. Two proposed controls on rapidly providing frequency support are effectively verified and compared in detail by different system disturbances in the DIgSILENT/Powerfactory software.

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Impact of demand management with load frequency control in distribution network with high penetration of renewable energy sources

Ranjitha¹,

Sivakumar²,

Rajapandiyan³

2021

Int Trans Electr Energ Syst

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Summary Renewable sources are deployed to meet the growing needs of the energy demand. Integration of these renewable sources in a power system leads to increased complexity due to which it is essential to adapt new control strategies to retain system stability by preserving frequency in a nominal value. Therefore, the objective of the work is to control the load frequency of an interconnected hybrid (wind, solar, thermal) power system by optimizing generator cost while implementing the demand management technique. Deviation in the frequency and tie‐line power due to fluctuation of renewable energy sources and load is addressed. For cost optimization, demand management technique was applied to the distribution system comprising flexible loads such as electric vehicle and heat pump. Voltage constraints and network congestion in the system are considered. The cascaded control technique is proposed for load frequency control and firefly based controller for cost optimization in the thermal power system. In the cascaded controller, proportional integral derivative (PID) and atom search optimization algorithm‐tuned PID controller are recommended. Performance of the projected approach is compared with a PID controller and fuzzy logic controller‐based load frequency control. Simulation studies and the result of various test cases considered clearly show the effectiveness of the controller implemented in the proposed system.

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Enhancing Frequency Response Control by DFIGs in the High Wind Penetrated Power Systems

Cited by 203 publications

References 20 publications

A Low-Order System Frequency Response Model for DFIG Distributed Wind Power Generation Systems Based on Small Signal Analysis

A Low-Order System Frequency Response Model for DFIG Distributed Wind Power Generation Systems Based on Small Signal Analysis

Coordinated Control Schemes of Super-Capacitor and Kinetic Energy of DFIG for System Frequency Support

Impact of demand management with load frequency control in distribution network with high penetration of renewable energy sources

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