Frequency Control Support of a Doubly-Fed Induction ... - IEEE Xplore

IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 31, NO. 6, NOVEMBER 2016

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Frequency Control Support of a Doubly-Fed Induction Generator Based on the Torque Limit Moses Kang, Student Member, IEEE, Keonhui Kim, Student Member, IEEE, Eduard Muljadi, Fellow, IEEE, Jung-Wook Park, Senior Member, IEEE, and Yong Cheol Kang, Senior Member, IEEE

Abstract—This paper proposes a torque limit-based inertial control scheme of a doubly-fed induction generator (DFIG) that supports the frequency control of a power system. If a frequency deviation occurs, the proposed scheme aims to release a large amount of kinetic energy (KE) stored in the rotating masses of a DFIG to raise the frequency nadir (FN). Upon detecting the event, the scheme instantly increases its output to the torque limit and then reduces the output with the rotor speed so that it converges to the stable operating range. To restore the rotor speed while causing a small second frequency dip (SFD), after the rotor speed converges the power reference is reduced by a small amount and maintained until it meets the reference for maximum power point tracking control. The test results demonstrate that the scheme can improve the FN and maximum rate of change of frequency while causing a small SFD in any wind conditions and in a power system that has a high penetration of wind power, and thus the scheme helps maintain the required level of system reliability. The scheme releases the KE from 2.9 times to 3.7 times the Hydro-Québec requirement depending on the power reference.

Reference GSC voltage.

Index Terms—Rotor speed, over-deceleration (OD), torque limit, second frequency dip (SFD), frequency nadir (FN).

Optimal rotor speed prior to an event.

NOMENCLATURE Voltage and current at rotor circuit. Voltage and current at point of common coupling. Voltage and current at GSC. DC-link voltage. Reference RSC voltage. Manuscript received May 29, 2015; revised September 05, 2015 and December 09, 2015; accepted December 25, 2015. Date of publication January 25, 2016; date of current version October 18, 2016. This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2010-0028509) and in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. 2010-0028065). NREL's contribution to this work was supported by the U.S. Department of Energy under Contract No. DE-AC36-08-GO28308 with NREL. Paper no. TPWRS-00762-2015. (Corresponding author: Yong Cheol Kang.) M. Kang and K. Kim are with the Department of Electrical Engineering and Wind energy Grid-Adaptive Technology (WeGAT) Research Center, Chonbuk National University, Chonju 561-756, Korea (e-mail: [email protected]; [email protected]). E. Muljadi is with the National Renewable Energy Laboratory, Golden, CO 80401 USA (e-mail: [email protected]). J.-W. Park is with the School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, Korea (e-mail: [email protected]). Y. C. Kang is with the Department of Electrical Engineering, WeGAT Research Center, and Smart Grid Research Center, Chonbuk National University, Chonju 561-756, Korea (e-mail: [email protected]). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TPWRS.2015.2514240

Pitch angle. Rotor speed. Reference for MPPT control. Mechanical input power. Reference for stepwise inertial control. Active power reference. Electrical output power. Reference for torque limit-based inertial control. Torque limit referred to power. Reference prior to a disturbance. Incremental power. Minimum rotor speed. Nominal and system frequency. DFIG

Doubly-fed induction generator.

FBIC

Frequency-based inertial control.

FN

Frequency nadir.

GSC

Grid-side converter.

KE

Kinetic energy.

MPPT

Maximum power point tracking.

OD

Over-deceleration.

PSO

Particle swarm optimization.

ROCOF

Rate of change of frequency.

RSC

Rotor-side converter.

SFD

Second frequency dip.

SIC

Stepwise inertial control.

WPP

Wind power plant.

WTG

Wind turbine generator. I. INTRODUCTION

S

YSTEM frequency should be maintained within an allowable tolerance at all times. If a frequency deviation occurs, such as a large generator trip, synchronous generators (SGs) inherently release their kinetic energy (KE) stored in their rotating masses as an inertial response, and they participate in primary and secondary controls to recover the system frequency to the nominal value [1]. To maintain the required level of system reliability, the frequency nadir (FN) should be kept within a specified value.

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Variable-speed wind turbine generators (WTGs), such as doubly-fed induction generators (DFIGs) and fully rated converter-based WTGs, have been widely used because of their improved controllabilities. As one of these, they perform maximum power point tracking (MPPT) control to capture the maximum energy from the wind. However, MPPT operation decouples the frequency of a WTG from the system frequency. This adversely impacts the frequency stability if a frequency deviation occurs, particularly in a power system that has a high penetration level of wind power [2]. Therefore, Nordic grid operators have imposed a requirement regarding inertial emulation of WTGs [3]. The Hydro-Québec requirement for the inertial response of a wind power plant (WPP) more than 10 MW specifies that “this target performance is met, for instance, when the frequency control system varies the real power dynamically and rapidly by at least 5% for 10 s when a large, short-term frequency deviation occurs in the power system” [4]. Many researches have reported on inertial control that temporarily releases the KE stored in the rotating masses in a WTG to arrest the frequency drop during an event. Frequency- based inertial control (FBIC) uses the additional loops based on the measured frequency [5]–[7]: the rate of change of frequency (ROCOF) loop [5] and the ROCOF and droop loops [6], [7]. FBIC provides a contribution to raise the FN; however, these loops show relatively slow response because they rely on the measured system frequency. To provide a fast inertial response, upon detecting an event stepwise inertial control (SIC) rapidly increases the output and remains for the predefined time [8]–[13]. SIC can improve the FN more than FBIC because the former instantly releases more KE than the latter during the early stage of an event; however, to accelerate the rotor speed, SIC reduces the WTG output in a step-like manner [8]–[11] or in a ramp manner [12], [13]. Thus, the former results in a second frequency dip (SFD) because of the rapid output reduction, whereas the latter results in a smaller SFD than the former while reducing the output, but it might result in over-deceleration (OD) because of the release of the excessive KE. The parameters used in the power reference function were heuristically determined in [12], whereas they were optimized using the particle swarm optimization (PSO) algorithm in [13], but they are valid only for a specific system condition. This paper proposes a torque limit-based inertial control scheme of a DFIG that can release a large amount of KE to improve the FN while preventing OD. Upon detecting an event, the scheme instantly increases its output to the torque limit and then reduces the output with the rotor speed. The proposed reference ensures that the rotor speed converges to the stable operating range. To restore the rotor speed while causing a small SFD, when the rotor speed converges the power reference is reduced by a small amount and maintained until it meets the reference for MPPT. The performance of the scheme is validated under the scenarios by varying the wind speeds and wind power penetration levels using an EMTP-RV simulator in a power system consisting of steam turbine generators, which have a low ramping capability.


Fig. 1. Typical configuration of a DFIG.

II. OPERATIONAL CHARACTERISTICS OF A DFIG This section briefly describes the overall features of a DFIG model, and Fig. 1 illustrates a typical configuration of a DFIG model, which includes a mechanical power model, two-mass shaft model, and DFIG controllers. The mechanical power model of a DFIG extracted from the wind is represented as (1) where , and are the air density, blade length, wind speed, power coefficient, tip-speed ratio, and pitch angle, respectively. used in this paper can be represented as

(2) where (3) , the maximum is set to 0.5, and In this paper, optimal is set to 9.95 [14]. A two-mass shaft model showing the dynamics between the wind turbine and generator is expressed as (4) where , and are the inertia time constants, angular speeds, torques, and damping constants of a wind turbine and a generator mass, respectively; , and are the shaft stiffness, damping constant, torsional twist, and base value of angular speed, respectively [15]. The DFIG controller consists of a rotor-side converter (RSC) and grid-side converter (GSC). An RSC controls the active and reactive powers injected into a power grid, and a GSC controls the DC-link and terminal voltages. To capture the maximum energy, the reference for MPPT control, , is set to (5), as in [16]. (5) where is a constant and set to 0.512 in this paper. As shown in Fig. 2(a), the rated, cut-in, and cut-out speeds of the DFIG are set to 11 m/s, 4 m/s, and 25 m/s, respectively. Fig. 2(b) shows the mechanical power curves at different wind

KANG et al.: FREQUENCY CONTROL SUPPORT OF A DOUBLY-FED INDUCTION GENERATOR BASED ON THE TORQUE LIMIT

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Fig. 2. Characteristics of a DFIG. (a) Power-speed curve of a DFIG, (b) Inputoutput power characteristics of a DFIG model.

speeds and as indicated by the thin solid lines and a dashed red line, respectively. To obtain the realistic results, this paper considers power and torque limits as represented by the dotted and solid black lines, respectively. The maximum power and torque limits are set to 1.20 p.u. and 1.17 p.u., respectively [17]. The operating range of is from 0.70 p.u. to 1.25 p.u., as represented by the two black dashed lines.

Fig. 3. Operational characteristics of the conventional scheme [8]. (a) Control scheme, (b) Reference power function, (c) Power-speed trajectory.

B. Torque Limit-Based Inertial Control Scheme of a DFIG III. TORQUE LIMIT-BASED INERTIAL CONTROL OF A DFIG This section briefly describes the overall features of the conventional SIC scheme in [8] and as illustrated in Fig. 3. Thereafter, this section describes the operational features of the proposed inertial control scheme.

Fig. 4 shows the operating characteristics of the proposed inertial control scheme. As shown in Fig. 4(a), the proposed scheme switches from to the reference of the proposed scheme, , which is given by

A. Conventional SIC Scheme [8] As shown in Fig. 3(a), at the instant of an event, , the reference, , is switched from to , which is defined in two sections: the deceleration period and the acceleration period . aims to improve the FN. At rapidly increases from to , where is the output power prior to an event, and is the incremental power. During keeps decreasing from , which is the optimal prior to an event. aims to restore . At rapidly decreases from to . If at Point is smaller than starts increasing; otherwise, keeps decreasing. In a conventional SIC scheme, if a too large is selected, OD might occur, thereby causing the deactivation of inertial control to protect a WTG. Thus, a significant output reduction might occur, thereby causing an SFD. If a too small is selected, keeps decreasing. Conversely, if a too large is selected, it will cause an SFD. In [8], for wind conditions higher than 7.5 m/s , and are set to the fixed values of 0.1 p.u., 10 s, and 20 s, respectively.

(6) where , and are the minimum rotor speed limit, at , and torque limit referred to power, , at . As shown in Fig. 4(b), upon detecting an event the proposed scheme instantly increases the output from to . This means that the incremental power at the instant of an event, , becomes , which is dependent on the wind speed. Afterward, because is larger than keeps decreasing until reaches . At this point, , and thus converges to , which is higher than . Note that the proposed reference function ensures no OD, because does not decrease below . In addition, during the inertial control period, keeps decreasing with time, because continuously decreases with time. On the other hand, can be obtained as (7)

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Fig. 5. Model system.

To reliably decide the convergence of , a waiting counter is used in this paper. If (8) is met, the counter is increased by one; otherwise, the counter is decreased by one. If the counter equals five, it is decided that is converged. To recover to should be less than at ; thus, the reduction in is required. A significant reduction can promptly recover , but it may cause a significant SFD. To avoid this, a small reduction is desirable. Note that in the proposed scheme, we can assume that at is nearly the same as , because converges to . This allows for a small reduction. In this paper, to obtain that can cause a small SFD, a small amount of 0.030 p.u. is reduced from ; then is maintained until meets the curve at Point (see Fig. 4(b)). during this period can be represented as (9)

Fig. 4. Operational characteristics of the proposed scheme. (a) Control scheme, (b) Power-rotor speed trajectory at the wind speed of 9 m/s, (c) Output power in the time domain.

As shown in (7), is proportional to , which critically depends on . This value decreases with and becomes zero at (see Fig. 4(b)). Thus, keeps decreasing to zero until reaches . As shown in Fig. 4(c), although might have a large value for a few seconds after an event, it promptly decreases with time until it converges to , where equals . Therefore, the proposed ensures the slow output reduction rate, and thus it successfully prevents an SFD during the deceleration period. To improve the FN, a large is desirable. However, if this value remains for a long time, OD might occur because too excessive KE is released during the initial stage of an event. As mentioned in the previous two paragraphs, the proposed instantly increases the output to following an event, and it decreases with . It causes neither SFD nor OD except during extremely low wind conditions. After converges to Point the proposed scheme starts recovering . To decide whether converges, the following condition is used: (8)

because is convex Note that (9) always lies below upward. Thus, it ensures the rotor speed recovery; further, it accelerates the recovery as increases. After Point returns to of (5) as (10) recovery, the conventional scheme instantly To ensure the reduces . Thus, a significant SFD is caused. Conversely, because the proposed scheme reduces its output after the rotor speed converges, it can reduce a 0.03 p.u., which results in a smaller SFD than the conventional scheme. In this paper, a disturbance detector is used to activate the proposed scheme. The proposed reference is activated if the frequency deviation exceeds 0.02 Hz. In addition, this paper considers the rate limiter [18] and power limiter. The former focuses on the mechanical stress on a drivetrain of a DFIG; the latter is set to the minimum value of power limit and torque limit, min , of a DFIG with . IV. MODEL SYSTEM Fig. 5 shows a model system used to investigate the performance of the proposed scheme. It is simulated using an EMTP-RV simulator. The model system consists of six SGs, one aggregated DFIG-based WPP, a static load of 220 MW and 79 MVAr, and a 330-MW asynchronous motor. Two 200-MVA SGs, two 150-MVA SGs, and two 100-MVA SGs are included in the model system. The inertia time constants for the 200-MVA SGs, 150-MVA SGs, and 100-MVA SGs are set to 5 s, 4.3 s, and 4 s, respectively [19]. To simulate a power


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TABLE II OUTPUT POWER OF GENERATORS FOR ALL CASES

Fig. 6. IEEEG1 steam governor model.

TABLE I COEFFICIENTS OF THE IEEEG1 MODEL

system with a low ramping capability, they are all assumed to be steam turbine generators; their steam turbine governor model is the IEEEG1 steam model. The droop gains are set to 5%. Fig. 6 and Table I show the steam turbine governor model and its coefficients [20]. Because automatic generation control is not included in this paper, the error of the system frequency after the frequency rebound remains. The motor load shares 60% of a total load of 550 MW, and the static load shares the rest of the load. The motor load is modeled as a frequency-dependent load to include the impact of the motor load during a disturbance. In this paper, the system frequency for detecting a disturbance is calculated in the DFIG controller from the measured WPP terminal voltage at the sampling frequency of 3840 Hz using a phase-locked loop proposed in [21]. V. CASE STUDIES This section investigates the performance of the proposed scheme under the scenarios by varying the wind speeds of 10.5 m/s, 9 m/s, and 8 m/s and wind power penetration levels of 16.7% and 33.3%. In this paper, the wind power penetration level was defined based on the installed capacity because the system inertia is not related to the output power but to the capacity of the generators in operation [1]. The installed capacities of the WPP for the two wind power penetration levels are set to 100 MW and 200 MW, respectively. Table II shows the output power of the and WPPs in the model system prior to a disturbance. As a disturbance, generating 100 MW is tripped at 40.0 s in all cases. As the wind power penetration level is increased, in Case 4 and Case 5, is replaced by WPPs. The performance of the proposed scheme is compared to the conventional scheme [8]. In addition, it is compared to a case that has no inertial control. A. Effects of Wind Speeds The performance of the inertial schemes is affected by the wind speed, which results in the different levels of KE in the

Fig. 7. Results for Case 1. (a) System frequency, (b) WPP output, (c) Rotor speed.

DFIG. This subsection validates the performance of the inertial control schemes for the three cases with wind speeds of 10.5 m/s, 9 m/s, and 8 m/s. Case 1: Wind Speed of 10.5 m/s and Wind Power Penetration Level of 16.7%: Fig. 7 shows the results for Case 1. In this case, in the proposed scheme is set to 0.24 p.u. As shown in Fig. 7(a), the FNs for “no inertial control,” the conventional scheme, and the proposed scheme are 58.99 Hz, 59.09 Hz, and 59.20 Hz, respectively. In addition, the maximum ROCOFs for “no inertial control,” the conventional scheme, and the proposed scheme are Hz/s, Hz/s, and Hz/s, respectively. A significant SFD starts at 50.0 s in the conventional scheme; in contrast, in the proposed scheme a small SFD begins at 60.8 s when the WPP output is reduced by 0.03 p.u. The sizes of the SFDs for the conventional scheme and the proposed scheme are 0.116 Hz and 0.044 Hz, respectively. (In this paper, a size of an

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SFD is defined as the difference between the frequency prior to an SFD and the second FN.) in the conventional scheme starts the recovery from 50.0 s. In the proposed scheme, converges to 1.06 p.u. at 60.8 s, then it starts the recovery and returns to . However, the frequency in the proposed scheme is smoothly settled to a value with less fluctuation than it is in the conventional scheme, as shown in Fig. 7(a). Case 2: Wind Speed of 9 m/s and Wind Power Penetration Level of 16.7%: Fig. 8 shows the results for Case 2. In this case, the WPP contains a smaller KE than that in Case 1, and in the proposed scheme is set to 0.39 p.u., which is larger than that in Case 1. The FN of the proposed scheme is 59.27 Hz, which is larger than it is in the case of “no inertial control” by 0.28 Hz and larger than in the conventional scheme by 0.18 Hz. In addition, the maximum ROCOFs for “no inertial control,” the conventional scheme, and the proposed scheme are Hz/s, Hz/s, and Hz/s, respectively. The maximum ROCOF of the proposed scheme is the smallest because the output in the proposed scheme is significantly larger than it is in the conventional scheme at the early stage of the event (see Fig. 8(b)). The sizes of the SFDs for the conventional scheme and proposed scheme are 0.116 Hz and 0.028 Hz, respectively. in the conventional scheme starts the recovery from 50.0 s. In the proposed scheme, converges to 0.84 p.u. at



56.4 s, which is faster than in Case 1. Then it starts the recovery and returns to . As in Case 1, the frequency in the proposed scheme is smoothly stabilized to a value with less fluctuation (see Fig. 8(a)). Case 3: Wind Speed of 8 m/s and Wind Power Penetration Level of 16.7%: Fig. 9 shows the results for Case 3, in which the wind speed is less than it is in Case 1 and Case 2; thus, the releasable KE is smaller. In this case, was set to 0.44 p.u. The FN of the proposed scheme is 59.23 Hz, which is larger than it is in the case of “no inertial control” by 0.24 Hz and larger than in the conventional scheme by 0.14 Hz. The improvement of the FN is less than in Case 2 despite the larger . The maximum ROCOFs for “no inertial control,” the conventional scheme, and the proposed scheme are Hz/s, Hz/s, and Hz/s, respectively. The sizes of the SFDs for the conventional scheme and the proposed scheme are 0.116 Hz and 0.004 Hz, respectively. In addition, in the proposed scheme starts the recovery from 51.0 s, and it returns to . The results of the three cases demonstrate that the proposed scheme can improve the FN and maximum ROCOF in any wind conditions. In addition, after converges it starts recovering by reducing by a small amount; thereby it causes a significantly smaller SFD than in the conventional scheme. Further, the frequency in the proposed scheme is smoothly stabilized with less fluctuation.


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B. Effects of Wind Power Penetration Level

than it is in Cases 1–3 because of a high wind power penetration level. Case 5: Wind Speed of 8 m/s and Wind Power Penetration Level of 33.3%: Fig. 11 shows the results for Case 5, which is identical to Case 3 except for the wind power penetration level of 33.3%. The FN of the proposed scheme is 59.18 Hz, which is larger than it is in the case of “no inertial control” by 0.32 Hz and larger than in the conventional scheme by 0.08 Hz. The maximum ROCOFs for “no inertial control,” the conventional scheme, and the proposed scheme are Hz/s, Hz/s, and Hz/s, respectively. The sizes of the SFDs for the conventional scheme and the proposed scheme are 0.300 Hz and 0.009 Hz, respectively. As in the previous cases, the size of an SFD in the proposed scheme is significantly smaller than it is in the conventional scheme. In addition, in the proposed scheme starts the recovery from 51.0 s, and it returns to . The results of the two cases indicate that the proposed scheme successfully improves the FN and maximum ROCOF while causing a small SFD, even for a high penetration level of wind power, irrespective of wind conditions. Conversely, the conventional scheme causes significant SFDs. Table III shows the comparison results for all cases in terms of the released KE for 10 s after an event. During this period, the released KE in the conventional scheme and the proposed

The performance of inertial control is affected by the wind power penetration level; thus, this subsection validates the performance of the inertial control schemes for wind speeds of 9 m/s and 8 m/s for the wind power penetration level of 33.3% Case 4: Wind Speed of 9 m/s and Wind Power Penetration Level of 33.3%: Fig. 10 shows the results for Case 4, which is identical to Case 2 except for the wind power penetration level. Thus, in the proposed scheme the same value of as in Case 2 is used. The FN of the proposed scheme is 59.29 Hz, which is higher than that for the case of “no inertial control” by 0.43 Hz and higher than that in the conventional scheme by 0.19 Hz. The improvement in Case 4 is larger than it is in Case 2 because the wind power penetration level is higher, and thus the WPP provides more power. The maximum ROCOFs for “no inertial control,” the conventional scheme, and the proposed scheme are Hz/s, Hz/s, and Hz/s, respectively. In this case, the maximum ROCOF in the proposed scheme is significantly improved by releasing a large amount of power. In the conventional scheme, an SFD occurs as in Case 2; however, the size of the SFD in Case 4 is 0.299 Hz, which is larger than it is in Case 2. In the proposed scheme, after converges to 0.84 p.u., it returns to , similar to Case 2. However, the frequency in the proposed scheme is less smoothly stabilized

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TABLE III COMPARISON OF THE RELEASED KE FOR 10 S AFTER AN EVENT

TABLE IV COMPARISON OF NUMERICAL RESULTS FOR ALL CASES

requirement, and thereby it improves the FN and maximum ROCOF while causing a small SFD in a system dominated by steam turbines regardless of wind conditions and wind power penetration levels. • Further, although the power reference increases its output upon detecting an event, it reduces the output with time and thereby prevents an SFD during the deceleration period. Although this paper shows the results for a DFIG, the scheme can be applicable for variable-speed WTGs. • The advantage of the proposed scheme is that it shows fast inertial response and thereby improves the FN while causing a small SFD. In addition, it ensures stable operation of a WTG during inertial control in any wind conditions. Further, it provides adaptive performance to wind conditions and wind power penetration levels. Therefore, the scheme helps maintain the required level of power system reliability when increasing the wind power penetration level. REFERENCES

scheme ranges from 18.1% to 49.5% and from 25.8% to 72.3% of the total releasable KE, respectively. In addition, the proposed scheme releases the KE ranging from 42.7% to 84.0% more than the conventional scheme, thereby improving the FN and maximum ROCOF more than the conventional scheme. Further, the conventional scheme releases the KE twice the Hydro-Québec requirement; whereas the proposed scheme releases the KE from 2.9 times to 3.7 times the Hydro-Québec requirement. Table IV shows a comparison of the results for all cases in terms of the first FN, maximum ROCOF, and size of an SFD. Because the proposed scheme releases a large amount of KE immediately after an event, the first FN is significantly higher than it is in the conventional scheme. In addition, the reduction in the maximum ROCOF for the conventional scheme and the proposed scheme compared to “no inertial control” ranges from 1.6% to 10.6% and from 4.9% to 40.9%, respectively. Further, the ratios of the SFD size of the proposed scheme to that of the conventional scheme range from 3.0% to 37.9%. This is because the proposed scheme reduces the power reference by a small amount for the rotor speed recovery after the rotor speed converges. VI. CONCLUSION This paper proposes a torque limit-based inertial control scheme of a DFIG and investigates the impact of the two inertial control schemes on the frequency control of a power system. Upon comparing the two schemes, it appears that the proposed scheme provides better performance than the conventional scheme in terms of FN, ROCOF, and SFD. The scheme can be summarized as follows: • At the onset of an event, the proposed scheme instantly increases its output to the torque limit and then reduces the output with the rotor speed. • The results demonstrate that the scheme promptly releases a large amount of KE, up to 3.7 times the Hydro-Québec

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[15] R.-J. Ye, H. Li, Z. Chen, and Q. Gao, “Comparison of transient behaviors of wind turbines with DFIG considering the shaft flexible models,” in Proc. IEEE Int. Conf. Electrical Machines and Systems (ICEMS) 2008, Wuhan, China, Oct. 2008. [16] B. Shen, B. Mwinyiwiwa, Y. Zhang, and B.-T. Ooi, “Sensorless maximum power point tracking of wind by DFIG using rotor position phase lock loop (PLL),” IEEE Trans. Power Electron., vol. 24, no. 4, pp. 942–951, Apr. 2009. [17] J. M. Mauricio, A. Marano, A. Gómez-Expósito, and J. L. M. Ramos, “Frequency regulation contribution through variable-speed wind energy conversion systems,” IEEE Trans. Power Syst., vol. 24, no. 1, pp. 173–180, Feb. 2009. [18] Y. Wang, G. Delille, H. Bayem, X. Guillaud, and B. Francois, “High wind power penetration in isolated power systems—Assessment of wind inertial and primary frequency responses,” IEEE Trans. Power Syst., vol. 28, no. 3, pp. 2412–2420, Aug. 2013. [19] J. Sutter, J. Maleche, and C. Muriithi, “Analysis of power system transient stability due to increased integration of geothermal power,” presented at the 39th Workshop Geothermal Reservoir Engineering, Stanford, CA, USA, Feb. 24–26, 2014. [20] R. T. Byerly, O. Aanstad, D. H. Berry, R. D. Dunlop, D. N. Ewart, B. M. Fox, L. H. Johnson, and D. W. Tschappat, “Dynamic models for steam and hydro turbines in power system studies,” IEEE Trans. Power App. Syst., vol. PAS-92, no. 6, pp. 1904–1915, Nov. 1973. [21] S. Li, J. Hu, S. Wang, H. He, L. Wang, and G. Liu, “A novel inertial control strategy for full-capacity wind turbine with PLL by optimizing internal potential response,” in Proc. 17th ICEMS, Hangzhou, China, Oct. 2014, pp. 3024–3028. Moses Kang (S'15) received the B.Sc. degree from Chonbuk National University, Korea, in 2015. He is currently pursuing an M.S. degree from the Department of Electrical Engineering, Chonbuk National University. He is an assistant researcher at the Wind energy Grid-Adaptive Technology (WeGAT) Research Center supported by the Ministry of Science, ICT, and future Planning (MSIP), Korea. His research interest is in frequency support for wind power plants.

Keonhui Kim (S'15) is currently pursuing his B.Sc. degree from Chonbuk National University, Korea. He is an assistant researcher at the Wind energy Grid-Adaptive Technology (WeGAT) Research Center supported by the Ministry of Science, ICT, and future Planning (MSIP), Korea. His research interest is in frequency support for wind power plants.

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Eduard Muljadi (M'82–SM'94–F'10) received his Ph.D. in electrical engineering from the University of Wisconsin at Madison. From 1988 to 1992, he taught at California State University at Fresno. In 1992, he joined the National Renewable Energy Laboratory in Golden, CO, USA. His current research interests are in the fields of electric machines, power electronics, and power systems in general, with an emphasis on renewable energy applications. Dr. Muljadi is an editor of the IEEE TRANSACTIONS ON ENERGY CONVERSION. He is involved in the activities of the IEEE Industry Application Society (IAS), Power Electronics Society, and Power and Energy Society (PES). He is currently a member of the Working Group on Renewable Technologies and the Task Force on Dynamic Performance of Wind Power Generation.

Jung-Wook Park (S'00–M'03–SM'09) received the B.S. degree (summa cum laude) from the Department of Electrical Engineering, Yonsei University, Seoul, Korea in 1999, and the M.S.E.C.E. and Ph.D. degrees from the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, in 2000 and 2003, respectively. He is currently an associate professor in the School of Electrical and Electronic Engineering, Yonsei University, Seoul, Korea.

Yong Cheol Kang (S'92–M'99–SM'13) received his B.Sc., M.Sc., and Ph.D. degrees in electrical engineering from Seoul National University, Korea, in 1991, 1993, and 1997, respectively. He has been with Chonbuk National University, Korea, since 1999. He is currently a professor at Chonbuk National University and the director of the Wind energy Grid-Adaptive Technology (WeGAT) Research Center supported by the Ministry of Science, ICT, and future Planning (MSIP), Korea. He is currently a visiting scholar at the National Renewable Energy Laboratory in Golden, CO, USA, and a member of the International Electrotechnical Commission working group TC88/WG27. His research interests include the development of control techniques for wind power plants.