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Contract No. DE-AC36-08GO28308

Role of Wind Power in Primary 

Frequency Response of an 

Interconnection

Preprint

Y.C. Zhang, V. Gevorgian, and E. Ela 

National Renewable Energy Laboratory

V. Singhvi and P. Pourbeik 

Electric Power Research Institute

To be presented at the International Workshop on Large-Scale 

Integration of Wind Power Into Power Systems as Well as on 

Transmission Networks for Offshore Wind Power Plants

London, United Kingdom

October 22–24, 2013

Conference Paper

NREL/CP-5D00-58995

September 2013
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Role of Wind Power in the Primary Frequency 

Response of an Interconnection

Yingchen Zhang, Member, IEEE

Vahan Gevorgian, Member, IEEE

Erik Ela, Member, IEEE

National Renewable Energy Laboratory (NREL)

Golden, Colorado-80401, USA

Vikas Singhvi, Member, IEEE

Pouyan Pourbeik, Fellow, IEEE

Electric Power Research Institute (EPRI)

Knoxville, TN-37932, USA

Abstract—The practice in North America is to maintain the 

electrical frequency of the three major interconnections very 

close to its nominal level at all times. Large frequency 

deviations can lead to unintended consequences such as load

shedding, instability, and machine damage, among others. The 

action of turbine governors of conventional generating units 

provides primary frequency response (PFR) to ensure that 

frequency deviations are not significant during large transient 

events. Increasing penetrations of variable renewable 

generation, such as wind and solar power, and planned 

retirements of conventional thermal plants—and thus a 

reduction in the amount of suppliers with PFR capabilities—

causes concerns about a decline of PFR and system inertia in 

North America. The majority of wind generation is connected 

to the grid via power inverters. If appropriately equipped with 

the necessary control features, inverter-coupled wind 

generation technologies are capable of contributing to PFR and 

inertia. This capability can help alleviate those concerns. 

However, these responses differ from those supplied by 

conventional generation, and it is not entirely understood how 

they will affect the system response at different penetration 

levels. The focus of the simulation work presented in this paper 

is to evaluate the impact of wind generation providing PFR and 

synthetic inertial response on a large interconnection. All 

simulations were conducted on the Western Interconnection 

system with different assumptions of wind power penetration 

levels. It should be noted that the results presented here are 

hypothetical, so they do not claim to demonstrate the actual 

present of the North American Western Interconnection. 

Although we found little risk of events causing the need for 

under frequency load shedding without controls from wind 

power, the ability of wind power plants to provide PFR, and the 

combination of inertial response and PFR, gave a significant 

improvement in the frequency response performance of the 

system; providing inertia alone did not improve performance. 

The simulation results also showed how other individual 

responsive units are affected by different levels of wind power 

and various control strategies. Last, we provided a case study 

with the realistic assumption that not all conventional units 

would be providing PFR; whereas the provision of wind power

providing PFR in high wind power penetrations actually 

avoided triggering under frequency load shedding. The 

simulation results provide insight in designing and operating 

wind generation active power controls to facilitate adequate 

PFR of an interconnection.

Index Terms—wind generation, primary frequency response,

active power control, inertial control, primary frequency 

control

I. INTRODUCTION 

The ability of a power system to maintain its electrical 

frequency within a specified range is a crucial element in 

maintaining a reliable and secure power system. An 

interconnected power system must have adequate resources 

to respond to a variety of contingency events to ensure rapid 

restoration of the balance between generation and load.

Primary frequency response (PFR)—also called primary 

control reserve [1] and frequency responsive reserve [2]—is 

the capacity available for automatic local response to correct 

frequency excursions through turbine speed governors and 

frequency responsive demand that adjust counter-frequency 

deviations and stabilize frequency. System inertia is the 

cumulative synchronous generation and load inertia that 

slows the initial rate of change of frequency deviation. The 

combined response of PFR and inertia is essential to arrest 

electrical frequency changes before triggering under

frequency load-shedding (UFLS) relays. In extreme cases, 

large deviations in frequency may result in generation 

protection relays operating or machine damage, or unstable 

frequencies that could potentially lead to a blackout.

The frequency response of the system is the aggregated 

result of PFR from all resources on the power system, 

including the natural load response. It is typically measured 

in MW/0.1 Hz, which measures the megawatt response 

provided for a 0.1-Hz steady-state frequency deviation. 

Other metrics have also been proposed recently that focus 

more on the frequency nadir [3]. The frequency response of 

the power system with high levels of variable generation to 

sudden, large imbalances between generation and load has 

been a focal point of many studies both nationally and 

internationally [3]–[5]. Currently, many variable energy 

resources typically do not provide PFR. Many renewable 

generation technologies are controlled by and interface with 

the grid using power electronics. As such, not only are they 

asynchronous, but the megawatt output of the unit is tightly 

controlled and maintained at a fixed value for given 

operating conditions. Thus, they do not inherently provide 

inertial response. Lower system inertia as a result of

increased renewable penetration will cause increased rates of 

change of frequency immediately following a disturbance. 

Lower amounts of PFR caused by the displacement of

conventional generators with active governors by variable 
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generation will cause greater steady-state frequency 

deviations. 

In the United States, recent studies have suggested that

the frequency response has been declining during the last 

several years [6], [7]. Some potential reasons for this include 

generators that operate in modes that do not offer PFR (e.g., 

sliding pressure mode) and blocked governors [8], [9]. Other 

reasons may include institutional reasons [10] and electricity 

market designs [11]. Such a decline may translate to a 

decrease in bulk power system reliability. In particular, the 

Eastern Interconnection of the United States and Canada has 

been seeing steady decline of approximately 60 MW/0.1 Hz 

to 70 MW/0.1 Hz per year during the past two decades [7]. 

An IEEE task force report studied the issue with great detail 

and developed a number of conclusions and 

recommendations [12]. These concerns prompted further 

industry-wide efforts by the North American Electric 

Reliability Corporation (NERC) and the regional reliability 

entities to broaden the understanding and increase 

transparency by highlighting mitigation efforts to ensure 

adequate frequency response. The Federal Energy 

Regulatory Commission (FERC)’s Frequency Response 

Initiative sets a number of objectives to comprehensively 

address the issues related to frequency response [13]. Such 

objectives include a) clearer identification of frequencyrelated reliability factors, b) improvements of frequency 

response metrics, and c) assessing impacts of emerging 

technologies, including inverter-coupled renewable energy 

generation. The proposed BAL-003-1 standard would set a 

minimum frequency response obligation for balancing 

authorities (BAs) within an interconnection and means for 

measuring their performance [14]. It requires sufficient 

frequency response from the BA to maintain interconnection 

frequency within predefined bounds. A systematic approach 

to identifying frequency response that is useful for operating 

a reliable system with increased amounts of variable 

renewable generation is presented in [3]. It also confirmed 

the validity of using frequency response as predictive metrics 

to assess the reliable operation of interconnected systems. 

Frequency response study for the US Eastern 

Interconnection (EI) is described in [22], and was intended to 

create a meaningful baseline model for the EI for examining 

its frequency response to investigate the possible impacts of 

large amounts of wind generation. Among other useful 

results, this EI study demonstrated benefits of wind power 

providing PFR. 

A typical wind power plant appears to the grid as a 

substantially different generation source than a conventional 

hydro or thermal power plant. Without special controls, a

wind power plant does not participate in PFR. Further, 

inverter-based wind turbine generators (WTGs) (i.e., Type 3 

and Type 4 units) do not, without special controls, provide 

any inherent inertial response. In this paper, we will present 

a detailed account of these two control features, PFR and 

inertial response, and illustrate some of the issues related to 

applying both these control strategies and how they might 

work best together. In contrast to previous studies, the focus 

of this work is more on the different effects that each of 

these controls has on the large, interconnected system 

response and how the two controls can complement each 

other.

Many researchers and wind turbine manufacturers have 

proposed different designs that allow wind power plants to 

provide capabilities similar to PFR and inertial control [15]. 

The work reported here is a continuation of previous work. 

The initial findings of this work were described in [16], in 

which impacts of wind power providing separately inertial 

and PFR were investigated. It was demonstrated in [16] that 

synthetic inertial control from WTGs, if tuned properly, can 

significantly improve the frequency nadir during 

disturbances. PFR from WTGs can be tuned to provide 

droop-like response and can significantly improve frequency 

nadir as well as settling (steady-state) frequency. This paper 

provides further in-depth analysis of the system-level 

frequency response at higher levels of wind power 

penetration and various levels of enabled governors in the 

conventional fleet. This work uses many methods and 

assumptions used in a similar simulation study [4]. In 

Section II, we give an overview of the frequency response 

metrics used in this study. Section III provides an overview 

of the system and assumptions used in the study. Section IV 

provides results for different active power control strategies 

from wind power, different penetration levels, and different 

levels of contribution from thermal plants. Section V 

concludes.

II. OVERVIEW OF FREQEUNCY RESPONSE METRICS

In this work, we adopted a similar approach to frequency 

response metrics as that described in [3]. Consider a real 

frequency event that took place in the Western 

Interconnection (WI) on August 6, 2011. This event started 

after a large generation loss at t=0 sec, as shown in Fig.1. 

The Point A value of frequency is the pre-disturbance 

frequency and is calculated as an average of frequency 

values from t=0 to t=-16 seconds [14]. The grid frequency 

started declining immediately because of an imbalance 

between generation and load. The initial rate of change of 

frequency was about -63 mHz/sec, and is determined by the 

amount of rotating mass (mechanical inertia) in the 

interconnection. The PFR of conventional generation with 

active governors starts to respond immediately after the 

frequency decline passes beyond their governor deadband 

thresholds. The characteristics of system inertia and PFR 

determine the lowest frequency (nadir), which is shown as 

Point C in Fig 1. The important characteristics are the system 

inertia, amount of PFR available, and the response speed of 

PFR. Point C has to be higher than the highest set point for 

UFLS within an interconnection. Measuring the level of 

Point C based on what large, credible disturbances the 

interconnection plans for helps determine the amount and 

characteristics of PFR that are needed to arrest frequency 

decline above the first stage of UFLS. 
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Fig. 1. Description of frequency response metrics

After the frequency decline has been arrested, continued 

delivery of PFR will stabilize frequency at a steady-state 

settling level (Point B). This point at which frequency is 

stabilized is often referred to as the settling frequency. The 

B-value is determined by averaging the frequency values 

from a period of 32 s starting at t=20 s after the disturbance 

[14].

The work presented in this paper is focused on assessing 

the impact of wind generation on the frequency response of 

the WI. We study this case while considering wind power as 

usual without any frequency response capabilities, as well as 

allowing wind power to have combinations of inertial and 

PFR response capabilities. The following frequency metrics 

are used in the study:

1. Initial rate of decline of frequency, or rate of change 

of frequency

2. Value of frequency nadir (Point C)

3. Transition time between beginning of disturbance

and frequency nadir (transition time from Point A to 

Point C)

4. Value of settling frequency (Point B)

5. Transition time between frequency nadir and 

settling frequency (transition time from Point C to 

Point B)

According to [3], the Interconnection Frequency Response 

Obligation is calculated from statistical observations of 

many events similar to the one shown in Fig. 1. Various 

parameters, such as the ratio of Point C to value B (CBR), are 

used in Interconnection Frequency Response Obligation 

calculations. For the WI, BAL-003-1 requires IFRO = -840 

MW/0.1 Hz [14].

III. BASE CASE DEVELOPMENT AND MODELING 

ASSUMPTIONS

The purpose of this study is to investigate the overall 

frequency response of the WI with different levels of 

variable wind generation with enabled inertial and PFR

controls using the GE Positive Sequence Load Flow

(PSLFTM) dynamic simulation software. For this purpose, it 

was decided to use one of the PSLF base cases developed 

under guidance by the Transmission Expansion Planning 

Policy Committee (TEPPC). In particular, the TEPPC 2022 

light spring load base case (model 22lsp1s) with 

approximately 15% wind power penetration was selected as

a basis for simulating future penetration scenarios. This 

particular base case under light spring load conditions 

throughout the WI and renewable penetrations is consistent 

with state renewable portfolio standard requirements for 

2022. Generation, load, and transmission topology are based 

on conditions modeled in the TEPPC 2022 common case 

[17]. It should be noted that the results presented here are 

hypothetical, so they do not claim to represent the actual 

present or future response of the North American WI. This is 

a research study with the goal of identifying what realistic 

behavior might be expected.

It is important to note that this modeling study does not 

address any changes to the limits of transmission lines that 

will take place at higher penetration levels. Instead, we 

adopted an approach of replacing the existing conventional 

power plants with wind power plants to achieve the desired 

penetration levels without transmission upgrades. At the 

snapshots of time represented in these cases for different 

penetration levels, the portion of generation coming from 

wind power was in accordance with the results of the 

Western Wind and Solar Integration Study Phase 1 

(WWSIS-1) [18]. WWSIS-1 examined three different wind 

and PV power scenarios to obtain 30% penetration across the 

WI footprint. For this study, it was decided to base wind 

power location assumptions on the “In-Area Scenario,” in 

which each state meets its target using best in-state resources 

so no additional interstate transmission is needed. The other 

two WWSIS-1 scenarios (“Local Priority” and “Mega 

Project”) required different levels of interstate transmission. 

In addition, the “Mega Project” scenario located most of the 

wind power in few best wind-resource areas, causing 

localized frequency response from wind power. 

Five different wind penetration scenarios were 

studied in WWSIS-1. The level of installed wind capacity 

for these scenarios is different for different regions in WI. 

The total installed wind capacities used in WWSIS-1 are 

33.24, 42.9 and 75.39 GW for 10, 20 and 30% penetration 

cases respectively. These numbers have been used as a 

guideline for developing penetration scenarios for this study. 

The selection of conventional thermal units that are 

displaced by wind power plants is based on the approach to 

put new wind power plants at existing large, fossil-fueled

(steam) unit plants. During this high-wind spring period, 

these wind power plants operate within the range of 50% to 

60% of rated capacity. Such approach gives an approximate 

but reasonable distribution of loadings on the wind power

plants in the Western Electricity Coordinating Council. 

The scenarios for this study were developed for four

penetration cases using Equation (1) for replacing 

conventional plants with wind power plants:

Total Wind Capacity = Penetration % x Western Electricity Coordinating 

Council Total Load(MW)/0.56 (1)

This rule is based on an average 56% capacity factor for 

the wind power plants. The 56% capacity factor is based on 

the average capacity factor for all wind power in WI during 

the lowest demand hour, as described in [4]. This approach is 
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different from the re-dispatch methodology used in [4] that 

implemented the 2/3 to 1/3 rule (which means that for every 3 

MW of additional wind power production, there is a 2-MW 

reduction in thermal unit commitment and a 1-MW reduction 

in thermal unit dispatch). This rule was based on the MultiArea Production Simulation (MAPS) modeling used in [18]. 

In this study, we simply replaced conventional thermal units 

with wind power plants. This approach is a simplistic way of 

emulating the shutdown of steam units because of 

Environmental Protection Agency regulations. Clearly, 

detailed transmission planning and dispatch consideration are 

an absolutely essential part of actually planning a system; 

however, the focus here is on basic research.

The total light spring load in the TEPPC 2022 base case 

is approximately 113 GW, so the total wind power

nameplate capacities for each penetration case used in this 

study can be calculated using Equation (1). Table I shows 

the nameplate capacities and generation level by wind power

for each penetration case.

TABLE I. Wind Power Nameplate Capacities and Current Generation 

Levels

Wind Penetration 

Case

Total Wind 

Nameplate Capacity, 

GW

Generation Level, 

GW

15% base case 23 17.92

20% 41.65 22.5

30% 60.34 33.76

40% 80.45 45.19 

50% 101.67 56.89

The breakdown of wind generation by turbine type for 

TEPPC 2022 base case (15% penetration) is shown in Table 

II. 

For the purpose of this work, all Type 3 and Type 4 

generic models were replaced with GE dynamic models for 

doubly-fed induction generator and full-size powerconverter-based wind turbines as implemented in the PSLF 

dynamic simulation program [19]. These models were 

developed and validated specifically for the latest GE WTGs, 

and include an inertial control scheme and active power 

control emulator for PFR. The Type 1 and Type 2 wind 

power plants were not replaced by the GE dynamic model, 

so there was still a small amount of Type 1 and Type 2 

WTGs present in all simulated cases.

TABLE II. TEPPC Base Case Wind Generation by Type

Wind Turbine

Model

Total 

Nameplate 

Rating (GW)

Current 

Output 

(MW)

% of current output 

out of total current 

generation

Type 1 (wt1g) 0.5 425.8 0.3%

Type 2 (wt2g) 1.5 1479.6 1.3%

Type 3 Generic 

(wt3g)

5.4 4145.7 3.5%

Type 4 Generic 

(wt4g)

15.6 8631.7 7.4%

Type 3 and 

Type 4 GE 

Model (gewtg)

4.9 3238.5 2.8%

All simulations were conducted using the PSLF

simulation tool. Each interconnection has a target Resource 

Contingency Protection Criteria based on the largest N-2 

loss-of-resource event [10]. For the WI, that would be the 

loss of the two largest generating units in the Palo Verde 

nuclear facility totaling 2,625 MW [20].

Additional details on a development of a base case for 

this study are described in [16]. The simulations performed 

in [16] were to investigate sensitivity of various active power 

control parameters of wind generation on the performance 

metrics discussed above. In particular, the sensitivities to 

wind power providing only PFR or only inertial controls 

were investigated at 20%, 30%, and 40% penetration levels. 

In this work, we present cases with combined inertial and 

PFR response by wind power for various wind power

penetration levels up to 50%. 

A wind turbine must operate in curtailed mode to provide 

enough reserve for PFR response during under frequency 

conditions. Under normal operating conditions with nearnominal system frequency, the control is set to provide a 

specified margin by generating less power than is available 

from the unit. The reserve margin (or headroom) determines 

what is specified as the operational point of a wind turbine, as 

shown in the Fig. 2.

 Fig. 2. Wind power droop

The inertial control provides an inertial response 

capability for wind turbines, emulating inertial response 

similar to conventional synchronous generators, for large 

under frequency events. The response is provided by 

temporarily increasing the power output of the wind turbines 

in the range of 5% to 10% of the rated turbine power by 

extracting the inertial energy stored in the rotating masses. 

This quick power injection can benefit the grid by essentially 

limiting the rate of decline of frequency at the inception of 

the load/generation imbalance event.

Another characteristic that influences system frequency 

behavior is the fraction of generators participating in 

governor control. This fraction (Kt) is a primary metric for 

expected performance first introduced by Undrill in [5]. The 

exact definition of Kt is not standardized. For this report, we 

conducted simulations to show the impact of Kt in the WI 

simulations using the following definition:

Kt = MW Generation Capability of Units with Governor Response

Total MW Capability of Conventional Generation 
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The lower Kt corresponds to the smaller fraction of 

generation providing PFR. Note that all synchronous 

machines will still provide inertia regardless of the Kt value.

The 15% base case has a number of enabled governors that 

corresponds to Kt=54.9%. 

Table III provides a summary of the simulations 

performed to investigate the sensitivity of various active 

power control parameters of wind generation on the 

performance metrics discussed above. For each simulated 

case, the grid frequency was calculated at 10 key 500-kV 

buses in the WI. For visual clarity, only the average of 10 

frequencies is shown in the plots.

TABLE III. SIMULATIONS PERFORMED

Cas

e Simulation Scenarios

15%

20% 

30% 

40% 

50%

No inertia,

no PFCa

Inertia 

only 

PFC only (5% 

headroom; 4% 

droop) 

Inertia + PFC (5% 

headroom; 4% droop) 

50% 

No inertia, no 

PFC, 

Kt=68%, 60%, 

50%,40%

Inertia 

only, 

Kt=40%

PFC only (5% 

headroom; 4 

droop), 

Kt=40%

Inertia + PFC (5% 

headroom; 4% 

droop), Kt=40%

IV. SIMULATION RESULTS

A. Impact of Wind Power Penetration Levels and Active 

Power Control Strategies on Frequency Response

Figs. 3–7 show simulated frequency response for five 

different wind power penetration levels (15%, 20%, 30%, 

40%, and 50%), and different active power control strategies

from the wind power fleet. As shown, the increase of wind

power penetration has a visible impact on the performance 

metrics: the frequency nadir and settling frequency decline 

with penetration levels for the base case (blue plots) as a 

result of non-frequency responsive wind power replacing the 

responsive conventional generation.

Fig. 3. WI frequency response for 15% wind power penetration

Fig. 4. WI frequency response for 20% wind power penetration

Fig. 5. WI frequency response for 30% wind power penetration

Fig. 6. WI frequency response for 40% wind power penetration

Fig. 7. WI frequency response for 50% wind power penetration

Further analysis of Figs. 3–7 reveals the impact of 

different active power control strategies. The inertial control 

by wind power (red trace) shows marginal improvement in 
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frequency nadir compared to the base case for lower 

penetration levels (Figs. 3–5). At higher penetration levels, 

the frequency nadir is essentially the same as the base case at 

40% penetration (Fig. 6), and is lower than the base case at 

50% penetration (Fig. 7). Also, the nadir transition time shifts 

farther and farther right with penetration levels. This is 

because inertial control alone only helps reduce the initial rate 

of decline of the frequency, which comes at the expense of 

slowing down wind turbine rotors. Because of this slowdown, 

the wind turbines depart from their maximum power point, 

thus creating a deficiency of active power (period of 

underproduction relative to the initial pre-fault operating 

point), and resulting in slower frequency recovery time. In 

addition, as shown in Figs. 3–7, the recovery is of oscillatory 

nature with overshoots and takes longer to settle at a steadystate frequency (i.e., there is a longer transition to Point B).

On the other hand, enabling the PFR feature creates 

visible improvement in frequency response, resulting in better 

nadir and higher steady-state frequency, as shown in Figs. 3–

7 (green trace). The frequency nadir of the PFR-only case 

does not change significantly with penetration levels because 

of the same 5% headroom in all simulation scenarios. 

However, it is consistently higher than the base case nadir for 

all penetration cases. The recovery of frequency is almost as 

fast as in the base case, with some oscillatory behavior 

depending on penetration level. The biggest improvement is 

in settling frequency level, which in the 50% case increases 

from 59.84 to 59.95.

Combining inertial and PFR controls gives the most 

superior performance (magenta trace on Figs. 3–7). This 

control strategy results in a significantly higher frequency 

nadir with somewhat slower recovery time compared to the 

PFR-only case.

Fig. 8 shows the consolidated results of the simulations 

and the impact on frequency nadir for all penetration cases 

and wind power control strategies. Combining inertial and 

PFR controls for wind power results in a frequency nadir that 

is constantly increasing with penetration level (magenta trace 

in Fig. 8), and has the best nadir performance at any wind

power penetration level compared to other control strategies.

Fig. 8. Impact of wind power controls on frequency nadir

Another conclusion (mentioned earlier), also shown in 

Fig. 8, is that by providing inertial control only does not give 

significant improvements compared to the base case. In fact, 

starting at approximately 36% to 37% wind power 

penetration, inertial control leads to lower frequency nadir 

compared to the base case. One important conclusion from 

Fig. 8 is that the wind power inertial control by itself is not a 

significant contributor to frequency nadir improvements on 

the interconnection level; however, the impact of inertial 

control on nadir performance is beneficial when it is 

combined with PFR control.

It is important to note that, despite the significant decline 

in frequency nadir for the base case, as wind power

penetration increases (blue trace in Fig. 8) it still stays above

the highest UFLS setting of 59.5 Hz in WI after the loss of 

the two Palo Verde units. The highest wind power penetration 

level, 50%, is still approximately 0.l1Hz above the UFLS 

setting. However, it is conceivable that some extreme 

conditions were not envisioned in the study that may result in 

unsatisfactory performance. In this regard, the advanced 

controls by wind power can help provide improved frequency 

response and reliability of the power system. Advantages of 

inertial control by wind power can be more obvious in 

smaller island systems experiencing inertia response 

deficiencies caused by high levels of inverter-based variable 

generation. In such an island system, the wind power inertia 

may play an important role in arresting the initial rate of 

change of frequency. The role of wind power inertia in 

islands systems is a subject of separate studies and will be 

investigated in future work.

Fig. 9. Impact of wind power controls on settling frequency

The impact of wind power control on settling frequency is 

shown in Fig. 9. The combination of inertial and PFR 

controls results in significant improvements of settling 

frequency at all penetration levels. Similar to frequency nadir, 

the settling frequency also increases with penetration level

when wind power provides control. The frequency response 

of WI was calculated from these settling frequencies and is 

shown in Table IV. Both MW/0.1 Hz and CBR metrics show 

sufficient improvements in overall frequency response of the 

WI. It is worth noting again that both metrics improve with 

penetration level when wind power provides a combination of 

inertial and PFR response during the contingency event.

TABLE IV. Impact of WI Frequency Response

Case

Base Case Inertia + PFR

MW/0.1 Hz CBR MW/0.1 Hz CBR

15% 1737 2.035 2616 2.439 

20% 1690 2.105 2830 2.592 

30% 1623 2.250 3500 2.944 

40% 1546 2.259 4232 3.208

50% 1544 2.317 4908 3.247 
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B. Impact of Wind Power Penetration Levels and Active 

Power Control Strategies on Generation Response

The active power controls by wind power will have a 

profound impact on frequency response of conventional 

generation. Such impact will become more obvious at higher 

penetration levels. The performance impact for selected WI 

conventional units during the same event is shown in Figs. 9–

13. These figures allow for estimating the evolution of 

frequency response by combined-cycle, combustion, hydro, 

and nuclear units, respectively, depending on wind power

penetration level and active power control strategy by wind 

power.

A closer look at Figs. 9–11 reveals significant reduction 

in the active power output of single thermal and hydro units 

for the cases in which wind power was providing only PFR or 

a combination of PFR and inertial controls. These units were 

selected to represent a typical response of conventional 

generation units for each fuel type. The power contribution 

from each unit type was calculated as a percentage of its 

installed capacity, and increases with wind power penetration 

level for a base case (blue trace) when all frequency response 

is provided by the conventional fleet. The magnitude of 

power contribution by conventional units is higher when 

wind power is providing only inertial control (red trace). This 

is because conventional units have to provide additional 

energy to compensate for periods of underproduction by wind 

power caused by the deceleration of wind turbine rotors. 

However, PFR and combined controls by wind power reduce 

the burden of frequency response by conventional units 

significantly, as shown in Figs. 9–11 (green and magenta 

traces).

Fig. 9. Impact on combined-cycle units

Fig.10. Impact on combustion units

Fig. 11. Impact on hydro units

Fig. 12. Impact on nuclear units

Fig. 13. Impact on wind power plants

The impact on nuclear units is less obvious (Fig. 13), 

because in this modeled case the nuclear power was not 

providing any PFR. The response of nuclear plants is only 

inertial and is not associated with governor response. The 

magnitude of such inertial response by synchronous 

generators is determined by the initial rate of change of the 

frequency immediately following generation loss.

The impact of wind power control strategies on the power 

output of the selected wind power plant is shown in Fig. 13. 

The active power magnitudes do not change significantly 

with penetration when wind power is providing only inertial 

response (red trace in Fig. 13). It does change, however, in 

the cases in which wind power is providing PFR or combined 

inertial and PFR response (green and magenta traces). In fact, 

the burden of frequency response on individual wind power

plants decreases with penetration level because such response 

is spread among a larger number of wind power plants that 

are online.

Base case

Inertia only

PFR only

Inertia + PFR
8 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

It is important to note that the results presented here do 

not consider the economic impact of curtailing wind power to 

have 5% reserve margin to provide PFR. Based on above 

results, such controls tend to improve the PFR of the system. 

Further analysis on providing rules during unit commitment 

or economic dispatch procedures can help ensure sufficient 

response at minimal cost [21]. 

C. Impact of Conventional Generation Frequency Response 

Participation on Frequency Response

It was mentioned earlier that the simulated frequency 

nadir of the WI stays above the highest UFLS setting even at 

50% wind power penetration with wind power providing no 

frequency response. Further simulations were conducted to 

determine the impact of Kt (as specified in Section III) on 

frequency nadir. Simulations demonstrated that even for the 

50% wind power penetration case, it takes Kt=40% for 

frequency nadir to go below the UFLS setting of 59.5 Hz. 

This finding is illustrated in Fig. 14, in which the frequency 

response of the WI at 50% wind power penetration was 

simulated for different values of Kt. (UFLS features were 

disabled in these simulations.) 

Fig. 14. Impact of Kt for the 50% penetration base case 

Fig. 15. Impact of wind power controls (50% penetration and Kt=40 %) 

As a next step, we conducted simulations for the case with 

50% penetration and Kt=40% to evaluate the impact of wind 

power active power control strategies on frequency response 

of the WI with reduced governor response by conventional 

units. The results of these simulations are illustrated in 

Fig.15. As expected, the inertia-only control (red plot) 

demonstrates significantly lower performance compared to 

the base case when wind power was not providing any 

frequency response (blue trace). Such a high level of wind

power penetration combined with fewer governor-enabled 

conventional generators causes a much deeper frequency 

nadir, slower nadir transition and recovery time, and 

potentially a large overshoot during frequency recovery. This 

simulation used the default model parameters for wind power 

inertial control. The inertial response from wind can be 

somewhat modified by further tuning these control 

parameters. Such parameter tuning is beyond the scope of this 

study, and is subject of future work.

On the other hand, both PFR and combined controls 

(green and magenta traces) show significant improvements 

compared to the base case. In particular, the combined control 

shows the most superior performance, resulting in shallow 

nadir and fast recovery time. This hypothetical simulated case 

demonstrates the capability of wind power controls to provide 

frequency response under conditions with reduced PFR

capabilities by conventional generation (Kt=40%) at 

extremely high levels of wind power penetration, when wind 

power can assist in ensuring UFLS relays are not triggered. 

V. CONCLUSIONS

The above insights of frequency response of the WI under 

various penetration levels of wind power are by no means 

comprehensive. They are, however, an attempt to provide 

additional contributions to ongoing industry wide discussions 

on the topic of frequency response of power systems with 

larger penetrations of variable generation. This simulation 

effort was conducted specifically to investigate the frequency 

response of the WI after a large loss of generation and was 

not intended to address any stability-related impacts on 

transmission. Many factors and constraints (both technical 

and economic) affect the operation of the power system with 

high levels of wind generation. The depth of frequency 

excursions followed by generation loss can be improved by 

inertial and/or governor-like controls of variable-speed 

WTGs. The industry is concerned about having inadequate 

frequency response in light of this changing generation mix 

because of the increasing penetration of variable generation 

and planned retirements of fossil-fueled generation. 

Currently, the PFRs from generation sources are not 

technology neutral. To consider all options toward improving 

the frequency performance, the industry needs to research, 

develop, and demonstrate newer and less familiar sources to 

provide frequency support. 

The focus of the research work presented in this paper 

was to assess the impact of different active power control 

strategies on the frequency response of an interconnection 

with a high level of wind power penetration. Inertial and PFR

control from WTGs can be tuned to improve frequency 

response of the system and can become an additional source 

of flexibility for power system operators.

Finally, although not addressed in this paper, we simply 

note that both inertial response and PFR as provided by wind 

generation is inherently stochastic. This is because the wind 

resource is highly variable. As such, future work will need to 

assess the impact of the stochastic nature of this resource as 

UFLS

UFLS
9 

This report is available at no cost from the 

National Renewable Energy Laboratory (NREL) 

at www.nrel.gov/publications.

provided by wind power as opposed to inertial response and

PFR provided by conventional generation, which is much 

more deterministic. 

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BIOGRAPHIES

Yingchen(YC) Zhang (S’07-M’10) received his B.S. from 

Tianjin University, Tianjin, China, in 2003, the Ph.D. degree from 

Virginia Polytechnic Institute and State University, Blacksburg, in 

2010. He is currently with the National Renewable Energy 

Laboratory. His research interests include power system stability 

with large scale integration of renewable energies, power system 

wide-area monitoring, and PMU applications for renewable 

integrations. Yingchen previously worked for the California ISO 

developing and implementing steady states and dynamic analysis 

tools to improve power system situational awareness. Yingchen is a 

member of IEEE and the Power and Energy Society.

Vahan Gevorgian (M’97) graduated from the Yerevan 

Polytechnic Institute (Armenia) in 1986. During his studies, he 

concentrated on electrical machines. His thesis research dealt with 

doubly-fed induction generators for standalone power systems. He 

obtained his Ph.D. in Electrical Engineering from the State 

Engineering University of Armenia in 1993. His dissertation was 

devoted to a modeling of electrical transients in large wind turbine 

generators. Dr. Gevorgian He is currently working with 

Transmission and Grid Integration group focused on renewable 

energy impacts on transmission and interconnection issues, and 

dynamic modeling of variable generation systems.

Vikas Singhvi (M’00) received his MS degree from the 

Mississippi State University in 2003. He joined EPRI in 2010 

where he is currently a Sr. Project Engineer in the Power Delivery 

and Utilization sector. His current research activities focus on 

transmission system modeling and simulation, increasing efficiency 

of transmission and distribution systems, impacts of Plug-in Hybrid 

and Electric Vehicles and other distributed resources. Formerly, he 

served as a Consultant engineer at Siemens Power Technologies 

International (PTI). At Siemens, he provided analytical network 

consulting to client including utilities, independent power 

producers, merchant developers and research institutions. He has 

performed numerous reliability and impact studies for systems 

falling under SPP, PJM, MISO and NYISO footprints. Mr. Singhvi 

is member of IEEE Power Engineering Society and Industrial 

Application Society.

Erik Ela (M ’06) received the B.S.E.E degree from Binghamton 

University and the M.S. degree in power systems from the Illinois 

Institute of Technology. He joined the National Renewable Energy 

Laboratory (NREL), Golden, CO, grid integration team to work on 

different wind integration issues. His experience lies mostly in 

different topics relating to grid operations and market operations. 

His research is on ancillary service impacts, unit commitment and 

dispatch, energy pricing impacts of wind in restructured markets, 

and topics related to the proper use of wind forecasts. He previously 

worked for the New York ISO developing and improving products 

in the energy markets and operations areas.

Pouyan Pourbeik (M’93–SM’02–F’10) received the B.E. and 

Ph.D. degrees in electrical engineering from the University of 

Adelaide, Adelaide, South Australia, Australia, in 1993 and 1997, 

respectively. From 1997 to 2000, he was with GE Power 

Systems. From 2000 to 2006, he was with ABB, Inc. Since June 

2006 he has been with EPRI, Cary, NC, USA. Throughout his 

career he has performed and led studies related to many aspects of 

power system modeling, dynamics, and control. Dr. Pourbeik is 

presently the Vice Chairman of the IEEE PES Power System 

Dynamic Performance Committee and Chairman of the CIGRE 

Study Committee C4. He has authored/co-authored more than 60 

technical publications, is a registered professional engineer in the 

state of North Carolina, USA, and a Fellow of the IEEE.