Determine Q-V characteristics of grid connected wind farms for voltage control using data driven analytics approach

Andalib-Bin-Karim, Chowdhury; Khan, Nahidul; Zhang, Huaguang

doi:10.1109/icps.2017.7945124

Cited by 6 publications

(6 citation statements)

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“…A traditional voltage droop strategy is deeply discussed in [6, 25, 26]. It is simplified in (1) below in which the line is assumed to be lossless ( R = 0) and mainly inductive

V_{ref}^{t} = V_{rated} - K_{dr} ()(, Q_{rated} - Q_{measured}^{t}),

where

K_{dr}

is the droop magnitude coefficient,

V_{rated}

and

Q_{rated}

are the rated voltage and reactive power,

Q_{measured}^{t}

is the measured reactive power at the time t and

V_{ref}^{t}

is the voltage reference at time t [6].…”

Section: Conventional Voltage Droop Controlmentioning

confidence: 99%

“…Andalib‐Bin‐Karim et al . [6] performed an analysis to find a curve which fits the Q–V model to be able to control the voltage of wind farm at the point of connection (POC). Authors have also illustrated that based on real data analysis of two wind farms in Canada, the relationship of the voltage at the POC and reactive power can be non‐linear and can follow very different trajectory at different voltage levels.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Improving voltage of remote connection using wind‐solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication

Aghanoori

Masoum

Islam

et al. 2019

IET Generation, Transmission & Distribution

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“…A traditional voltage droop strategy is deeply discussed in [6, 25, 26]. It is simplified in (1) below in which the line is assumed to be lossless ( R = 0) and mainly inductive

V_{ref}^{t} = V_{rated} - K_{dr} ()(, Q_{rated} - Q_{measured}^{t}),

where

K_{dr}

is the droop magnitude coefficient,

V_{rated}

and

Q_{rated}

are the rated voltage and reactive power,

Q_{measured}^{t}

is the measured reactive power at the time t and

V_{ref}^{t}

is the voltage reference at time t [6].…”

Section: Conventional Voltage Droop Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improving voltage of remote connection using wind‐solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication

Aghanoori

Masoum

Islam

et al. 2019

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

“…In [8] the authors investigated the feasibility of utilizing the reactive power of grid-connected variable-speed wind generators to enhance the steady voltage stability margin of the system. In [9] data-driven methods were used to evaluate several approaches to fitting the PV curve of WFs and determine the best fitting method based on a variety of indicators, which provided useful information for SVS evaluation. However, the influence of the uncertain fluctuation of WF output on the analysis and control of SVS was not considered in any of these studies [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

“…In [9] data-driven methods were used to evaluate several approaches to fitting the PV curve of WFs and determine the best fitting method based on a variety of indicators, which provided useful information for SVS evaluation. However, the influence of the uncertain fluctuation of WF output on the analysis and control of SVS was not considered in any of these studies [6][7][8][9]. Methods for considering the influence of the uncertain WF output fluctuation on the analysis and control of SVS include the Monte Carlo method [10,11], probability method [12][13][14], and interval method [4,5,15].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimal Control Approach for Static Voltage Stability of Power System Considering Interval Uncertainty of the Wind Farm Output

et al. 2020

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The static voltage stability margin (SVSM) of a power system considering the uncertain fluctuation range of wind farm (WF) output can be described as an interval value called the SVSM interval. A multi-objective optimal control model for SVS of a power system considering the interval uncertainty of WF output is proposed. The objective functions of the model are to increase the central value and reduce the fluctuation range of the SVSM interval, and the decision variables are the active power output and terminal voltage of generators and the switching capacity of shunt capacitors. Thus, it is a multi-layer optimization model. A parametric approximation (PA) method is used to obtain the approximate functional relationship between the optimal objective function values and the decision variables of the inner-layer and mid-layer optimization models and convert the optimization model into a single-layer bi-objective optimization model. A method for obtaining the continuous Pareto frontier of the bi-objective optimization model is proposed based on the normalized normal constraint and PA methods, and the compromise optimal solution calculated from the continuous Pareto frontier is used as the optimal control scheme. Two methods for improving the calculation efficiency of the PA method are also proposed. Finally, results from experimentation on the IEEE 39-bus system and an actual provincial power grid demonstrate the effectiveness of the proposed method.

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“…As one of the most promising renewable energy resources to be used in the world, wind energy has attracted the attention of many researchers [1][2][3][4]. With the fast development of power electronics, the fully-rated permanent magnet synchronous generator (PMSG) and partially-rated doubly-fed induction generator (DFIG)-based wind energy conversion systems (WECSs) are the ones mainly used in the wind energy market, since they have the ability of variable-speed constant-frequency (VSCF) operation.…”

Section: Introductionmentioning

confidence: 99%

Sensorless Control of Late-Stage Offshore DFIG-WT with FSTP Converters by Using EKF to Ride through Hybrid Faults

et al. 2017

Energies

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Abstract:A hybrid fault scenario in a late-stage offshore doubly-fed induction generator (DFIG)-based wind turbine (DFIG-WT) with converter open-circuit fault and position sensor failure is investigated in this paper. An extended Kalman filter (EKF)-based sensorless control strategy is utilized to eliminate the encoder. Based on the detailed analysis of the seventh-order dynamic state space model of DFIG, along with the input voltage signals and measured current signals, the EKF algorithm for DFIG is designed to estimate the rotor speed and position. In addition, the bridge arm open circuit in the back-to-back (BTB) power converter of DFIG is taken as a commonly-encountered fault due to the fragility of semiconductor switches. Four-switch three-phase (FSTP) topology-based fault-tolerant converters are employed for post-fault operation by considering the minimization of switching losses and reducing the circuit complexity. Moreover, a simplified space vector pulse width modulation (SVPWM) technique is proposed to reduce the computational burden, and a voltage balancing scheme is put forward to increase the DC-bus voltage utilization rate. Simulation studies are carried out in MATLAB/Simulink2017a (MathWorks, Natick, MA, USA) to demonstrate the validity of the proposed hybrid fault-tolerant strategy for DFIG-WT, with the wind speed fluctuation, measurement noises and grid voltage sag taken into consideration.

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Determine Q-V characteristics of grid connected wind farms for voltage control using data driven analytics approach

Cited by 6 publications

References 0 publications

Improving voltage of remote connection using wind‐solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication

Improving voltage of remote connection using wind‐solar farms equipped with new voltage control strategy based on virtual impedance monitoring enabled by IEC 61850 communication

Multi-Objective Optimal Control Approach for Static Voltage Stability of Power System Considering Interval Uncertainty of the Wind Farm Output

Sensorless Control of Late-Stage Offshore DFIG-WT with FSTP Converters by Using EKF to Ride through Hybrid Faults

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