International Journal on Electrical Engineering and Informatics - Volume 7, Number 4, Desember 2015

Effect of Grid-Connected Wind Turbine Generators on Power

System Transient Stability

Shaon Ahmed1, Mohd Abdur Rashid

2, Shamshul Bahar YAAKOB

3,

Adawati Yusof3, and Mohd Fareq

3

1Department of Electrical and Electronic Engineering, Hamdard University Bangladesh, Bangladesh

2Faculty of Design Arts and Engineering Technology, Universiti Sultan Zainal Abidin, Kuala Terengganu, Malaysia 3School of Electrical Systems Engineering, Universiti Malaysia Perlis, Kubang Gajah, Perlis, Malaysia

Abstract: A huge number of wind turbine generators will be integrated into the existing

power systems in the near future because it has been identified as one of the most

promising field of energy industry. Wind turbines are required to remain connected to

the grid during a fault condition so as to support constant power supply. It is therefore

necessary to investigate the impact of wind turbine generators on the stability of power

systems. This paper presents a comparative study of available wind generator types and

examines the effect of penetration level on the power system. Simulations have been

performed to compare and demonstrate the transient behavior of a typical 5-machine 22-

bus system with and without wind power integration. The simulation results reveal that

the transient behavior of wind generators has significant effect on the overall stability of

power systems and the increase in penetration level may induce the instability into the

systems.

Keywords: Wind Energy Conversion System, Wind Generator, Transient Response,

Transient Stability Index

1. Introduction

Over the past few decades the electrical power generations from wind turbines has received

substantial interest from manufacturers and researchers in order to reduce fossil fuel

dependency and rising environment concerns. Global wind energy council (GWEC) estimates

that, as of 2013, the global wind power production has reached 318 MW. The market forecast

suggests that it could go as high as 600GW by 2018, which would mean that almost 8%

world’s total electrical energy consumption would be supplied by wind turbines[1-2]. As a

result a large number of wind turbines are going to be connected to the existing network in the

near future.

One of the significant decisions in designing the wind energy conversion (WECS) is what

type of generators is to be used along with the wind turbine. Induction generators (IG) have

been used widely due to their robustness, low cost and rugged construction. However, several

other types of generators have also been trialed and used on wind turbines. So, researchers are

often forced to mark some subtle indicators to decide among the available options. The

transient stability of a particular generator type and the impact it has on the power system

stability often serves as one of those key indicators.

A power system is said to be transiently stable if it is capable of maintaining synchronism

even after sustaining a large disturbance. Often, these faults are caused by equipment outage,

sudden load change of equipment faults and the time frame of a transient study is usually 3-

5seconds [3]. These faults results in a change of rotor angle position and impedes natural

operating conditions. The ability to restore equilibrium between mechanical torque and

electrical torque of a machine in interconnected system is determined by the rotor angle of the

machine. The transient stability problem of generators and machines is a thoroughly

investigated and now a fully understood topic in power system study. However transient

stability study of wind generator is still an evolving issue, since the nature of problem posed by

these generators are not same as that of conventional generators. Unlike conventional

generators the transient fault behavior of a wind generator depends largely on power electronic

Received: November 17th

, 2014. Accepted: November 16th

, 2015

DOI: 10.15676/ijeei.2015.7.4.8

644

controllers along with the inertial response. As a result, a grid fault into the power system does

not always accompanied by loss synchronism.

The dynamic characteristic of a power system is largely influenced by the presence of wind

turbines into it. A fault at the grid causes change in electromagnetic torque of a wind machine.

This change in electromagnetic torque can be characterized as synchronizing torque and

damping torque. If the synchronizing torque is reduced by fault current machine will show

non-oscillatory instability. One the other hand, if damping torque is reduced it will show

oscillatory instability. The impact of wind generator on the power system is determined by the

response of their controller. The oscillatory instability of a wind generator is the prime concern

of this paper.

There are several reports investigating the transient stability of individual wind generators

[4-8]. The effect of wind generators on an interconnected power system has also been analyzed

[9]. However none of them had focused on the comparative study of available types of wind

generators. This paper presents a comparative analysis of transient behavior of two of the most

popular types of wind generators, the squirrel cage induction generator (SCIG) and

synchronous generators (SG). The impact of increased penetration of wind power on an

interconnected power system has also been analyzed. Firstly, the characteristics and typical

model of wind turbine is presented. Then the ground for comparative study has been

established. Four different fault scenarios’ has been modeled in order to understand and

scrutinize the transient response of both generator types. The simulation is performed on

PSS/U. After the simulation, it is found that SG’s performs better in faulty condition.

2. Characteristics and Modeling of Wind Generators

The proper use of power electronic controllers allows several generator types to be

employed in wind power production. The main distinction between available wind generator

types is, whether they are fixed speed or variable speed. The variable speed configuration of

wind generator has been popular over the last decade due to its capability of running at

optimum power coefficient for a wind range of wind speed. Although conventional Squirrel

Cage Induction Generators (SCIG) has the advantage of robustness and simple mechanical

configuration, the converter driven Synchronous Generators (SG) and doubly fed induction

generators have been widely used as wind generators in recent years since they provide more

control over power conversion [10]. The present paper, however, only considers the effect of

SCIG and SG in transient stability of the grid.

The basic configuration of a wind turbine driving SG is shown in Figure 1 [11]. The

generator is decoupled from the grid by a power converter that is actually connected to the

grid. The SCIG configuration is similar to that but; it has a mechanical drive train with one

high speed shaft and a low speed shaft between turbine and generator [12]. The advantage of

SG configuration is that it does not require external excitation sources and at the same time it

can eliminate the mechanical loss associated with gearbox [13-17].

In order to find the overall stability behaviour of a power system both steady state analysis

and dynamic analysis has to be performed. The power flow analysis provides the initial

conditions for dynamic analysis of a grid connected wind turbine. Although the total wind

power generation from the wind farm is distributed among small single unit of wind generator,

the collective power from them is still connected at a single point to the main grid line. So, the

wind farm is modelled as a single equivalent machine of same MW rating as the summation of

the MW rating of the individual machine. Including large number of individual wind turbines

into the simulation will increase unnecessary computational complexity. The assumption of

single large unit is more reasonable when the power system under consideration is relatively

large and penetration level of wind power is adjusted according to the size of the total system.

The dynamic behaviour of the wind turbine is influenced by several components as listed

below:

Pitch control; it controls the mechanical power delivered to the generator shaft. In this

study a PI system is used to control the pitch of the blade.

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645

Aerodynamic model of the turbine; aerodynamic model of the turbine can be defined by a

three dimensional curve of power coefficient-pitch angle and tip speed ratio [18]. The

performance of a wind turbine is characterized by the non-dimensional curves of power co-

efficient, Cp. The power coefficient of wind turbine is a function of both tip speed ratio and

the blade pitch angle. The tip speed ratio is defined as the ratio of linear speed at the tip of

blades to the speed of the wind. It can be expressed by Equation (1).

𝜆 =𝑅𝛺𝑤

𝑉𝑤. (1)

Where, 𝑉𝑤. is wind speed, 𝛺𝑤 is the angular velocity of the turbine and R is the radius of

the blade. The pitch angle of the turbine blade is expressed as β and is depended on the

angle of attack of the wind.There are quite few mathematical expressions of Cp although the

theoretical basis remains similar for all [19]. For the wind turbine used in this study, the

following form approximates Cp as a function of 𝜆 and β.

𝐶𝑝(𝜆, 𝛽 ) = 𝑐1 (𝑐2

𝜆𝑖−𝑐3𝛽−𝑐4) 𝑒−

𝑐5𝜆𝑖 + 𝑐6𝜆 (2)

Here, c1=0.5167, c2=116, c3=0.4, c4=5, c5=21 and c6= 0.0068. Tip speed ratio and pitch

angle are related by the following equation:

1

𝜆𝑖=

1

𝜆+0.08𝛽−

0.035

𝛽3+1 (3)

The wind speed is assumed to be constant during the transient analysis to avoid complexity.

The mechanical power converted by the wind turbine is given by the following equation,

𝑃𝑚𝑒𝑐ℎ =1

2⍴𝜋𝑅2𝑉𝑤

3𝐶𝑝(𝜆, 𝛽 ) (4)

here, ⍴ is the air density and is a function of air pressure and temperature.

Figure 1. Typical outfit of a wind turbine

Dynamic model of the shaft; here a two mass shaft is considered, one mass represents

the turbine blade and another represents generator. The motion equation of shaft is

given by equations (5) to (7).

Effect of Grid-Connected Wind Turbine Generators on Power

646

2 𝐻𝑡𝑑𝜔𝑡

𝑑𝑡= 𝑇𝑚 − 𝐷𝑡𝜔𝑡 − 𝐷𝑡𝑔(𝜔𝑡−𝜔𝑟) − 𝑇𝑡𝑔 (5)

2 𝐻𝑔𝑑𝜔𝑟

𝑑𝑡= 𝑇𝑡𝑔 − 𝐷𝑔𝜔𝑟 − 𝐷𝑡𝑔(𝜔𝑡−𝜔𝑟) − 𝑇𝑒 (6)

𝑑𝑇𝑡𝑔

𝑑𝑡 = 𝐾𝑡𝑔 (𝜔𝑡−𝜔𝑟) (7)

Where, 𝜔𝑡 and 𝜔𝑟 are the turbine and generator rotor speed, respectively; 𝑇𝑚 and Te

are the mechanical torque applied to the turbine and the electrical torque of the

generator, respectively; 𝑇𝑡𝑔 is an internal torque of the model; 𝐻𝑡 and 𝐻𝑔 are the

inertia constants of the turbine and the generator, respectively; 𝐷𝑡 and 𝐷𝑔 are the

damping coefficients of the turbine and the generator, respectively; 𝐷𝑡𝑔 is the damping

coefficient of the shaft.

Electrical control; it regulates active/reactive power and maximizes the power

absorption from wind energy.

protection relay settings

The European grid code requirement for wind power integration defines the tolerance for

under voltage and overvoltage. According to regulations, a fault sustaining 250ms at rated

power generation will increase the frequency by 1.9 Hz. If the AC network does not recover by

the time generator over speed limit is reached, the turbine should trip [12, 19]. In this paper it is

assumed that the protection relays are set according to the mandate and the bus fault created for

simulation purpose is also kept below the estimated time limit so that the protection relays are

not triggered.

3. The Proposed Approach

The relative position of rotor axis with respect to synchronously rotating magnetic field is

considered as one of the parameters to examine stability of the system. The angle between the

two is known as the power angle or torque angle.

Figure 2. Single line diagram of 5-machine 22-bus test system with a large wind farm

Under normal operating condition and fixed load, the rotor angle should stay constant.

When a fault occurs into the system, the machine will either accelerate or decelerate depending

with respect to the synchronously rotating field. Thus a relative motion between the two starts

and this is described by the swing equation. After this oscillatory period the rotor angle must

Shaon Ahmed, et al.

647

go back to normal operating condition, if not, the machine will drive into an unstable condition.

If the fault is created by making a change in the generation, load or network condition, the

machine may come to new angular position and still behave stable. Observing the severity and

contingency of the trajectory of rotor angle following a faulty condition, it is possible to

conclude on system stability. This is measured by the Transient Stability Index (TSI). The TSI

is found in transient security assessment tool which calculates the angle margin by the

following equation [10].

𝑇𝑆𝐼 = 360−𝛿𝑚𝑎𝑥

360+𝛿𝑚𝑎𝑥× 100, −100 < 𝑇𝑆𝐼 < 100 (8)

In the above equation,𝛿𝑚𝑎𝑥 represents the maximum angle separation between any two

generators of the system after a fault has occurred. If TSI>0, it can be concluded that the

system has sustained the fault condition and remained stable. Similarly, a negative value for

TSI would imply that the system has become unstable due to sudden rise of fault current.

In this paper some scenarios are designed to investigate the transient stability of a power

system that has significant wind power penetration. The angle response from each generators

of the system would be examined. Figure 3 shows the single line diagram of the test system. It

is a 22-bus system with 5 different type of plant. It includes two nuclear power plant and one of

diesel plant, hydro power plant, wind farm, coal plant. The total generation capacity of the

system is 3258 MW with a wind power penetration of is 3.06%. The estimated active power

load is 3200MW. Figure 3 shows the swing bus -3011 and a large wind farm of 100 MW

connected to bus-3018.

Figure 3. Single line diagram of swing bus (3011) and wind bus (3018) of the test system

The four different scenarios are applied on bus-3018 as described below:

Case A constitutes of a scenario where the system under consideration has no wind

farm into it. The generator connected to bus-3018 is a normal diesel generator of

100MW rating.

In Case B, the diesel generator in the previous scenario is replaced by a wind farm of

same MW rating. Here, all the wind turbines are of variable speed configuration and

are coupled with a squirrel cage induction machine.

Case C is constituted by replacing the induction type wind generators by synchronous

types.

In Case D the penetration level of wind farm is increased by another 3% to observe if

that has any effect on Case C. This increase in wind power production is compensated

Effect of Grid-Connected Wind Turbine Generators on Power

648

by concomitant reduction from other plants so that the total power generation is kept

constant.

The objective of transient response analysis here is to inspect if any of the above mentioned

scenarios are can be triggered by a large bus fault of 100ms duration at bus-3011. All the

scenarios are scrutinized for transient response in time domain. The electrical control system of

the wind turbines are designed to operate with the specified power factor and the machines

active power settings is used to set the reactive power limit.

4. Results for Transient Stability Analysis

The system under consideration is designed in Siemens PSS/U interface. Simulations are

conducted for a bus fault at bus-3011. The fault is created after five seconds of stable run and

cleared after 100ms. If the disturbance causes the electrical torque to fall behind mechanical

torque, the rotor will try to increase the speed and move the position of the flux vector in the

positive direction. An increase in rotor angle will result in an increase in generator load torque.

For stable run the generator torque has to meet the turbine torque. The following scenarios are

designed to understand the transient response of wind generators:

Case A:

In Case A, the presence of wind firm is ignored and a conventional diesel generator is

placed at bus-3018. In Case A, the presence of wind firm is ignored and a conventional diesel

generator is placed at bus-3018. The rotor angle response to the transient fault of the all the

generators are shown in Figure4. As seen from the figure, the generators have been operating

for five seconds in stable condition before the fault has occurred. The generators respond to the

bus fault by increasing the speed and attempts to catch up to fault current. However, the as

fault is cleared within next 100ms, the generators goes back to its normal operating condition

within next three seconds. But the fault is created by causing a change in the network, therefore,

although the generators are still behaving stable, a shift of rotor angle has appeared in all the

generators. The maximum angle separation between the generators is 50 degrees, hence

TSI=0.75. So, it can be concluded that the Case A is stable.

Figure 4. Rotor angle response of the system to transient fault without wind turbine

Case B:

a wound rotor induction generator at bus-3018. The fault response is shown in Figure 5.

From the figure it is seen that the wind generator goes to stability but five seconds after the

fault has occurred. The maximum angle separation is found to be 65 degree and TSI is equal to

0.69. The oscillation produced in the supplied power by the fault current is shown in Figure 6.

Angle

(D

egre

es)

Time (seconds)

Shaon Ahmed, et al.

649

Figure 5. Rotor angle response of the system to transient fault with Induction wind generator

Figure 6. Power curve of Induction wind generator showing post fault performance

Case C:

Figure 7. Rotor angle response of the system to transient fault with Synchronous wind

generator

Figure 8. Change of rotor angle in synchronous wind generator due to a large

fault at the system

Angle

(D

egre

es)

Pow

er

(PU

)

Angle

(D

egre

es)

Angle

(D

egre

es)

Time (seconds)

Time (seconds)

Time (seconds)

Time (seconds)

Effect of Grid-Connected Wind Turbine Generators on Power

650

In Case C the generator at 3018 is a permanent magnet synchronous wind generator

(PMSWG). The transient response of this configuration is shown in Figure 7. From the figure it

is can be seen that a PMSWG responded much better than any other cases described above.

The effect of transient fault on the wind generator is very little and although there is an initial

disruption in stable condition, it goes to normal operation as soon as the fault is cleared. The

TSI level in this case is 0.6. Figure 8 is the zoomed view of the angle response of PMSWG.

The associated active and reactive power of the generator is shown in Figure 9.

Case D:

In Case D, the generation capacity of the wind generator is increased by another 100MW,

whereas the generation from other sources was reduced to keep the total active power

generation constant. This is done to investigate that whether scenario C can be triggered by

increasing the penetration level. So, the wind power penetration level is now increased to

6.13%. The rotor angle response is presented in Figure 10. As seen from the figure, a fault after

five seconds of stable run has caused all the generators to decelerate except the wind generator.

Although the TSI value is still in the stable region, the trajectory of the rotor angle is still

unconvincing. So the simulation is continued for another 10 seconds. This is shown in Figure

11.

Figure 9. Active and reactive power of Synchronous wind generator

Figure 10. Rotor angle response of the system to transient fault with increased penetration level

(run time 15seconds)

Figure 11 shows that the generator speed is still decelerating even after twenty seconds of

clearing the fault and eventually drives the system into instability. So, the increase in

penetration level of wind power has derived the system into instability.

Pow

er

(PU

)

Angle

(D

egre

es)

Angle

(D

egre

es)

Time (seconds)

Time (seconds)

Shaon Ahmed, et al.

651

Figure 11. Rotor angle response of the system to transient fault with increased penetration level

(run time 25seconds)

5. Conclusion

This paper presents a simulation analysis of transient stability of a grid integrated wind

turbine. A systematic approach has been designed to demonstrate the effect of wind generators

on power system. Two different types of conventional generators are considered and their

response to a large grid fault has been analyzed and compared. The TSI has been considered as

the telling factor for transient stability. The effect of increased penetration of wind power has

also been observed. From the analysis, it can be concluded that although both induction and

synchronous generators can be used as wind generators, the synchronous generators provides

better post fault operating conditions for the power system. However, the increase in wind

power penetration may drive the system into instability. With increasing in penetration level,

the system experiences major changes in dynamics and operating conditions. In this case, when

the wind power penetration was increased from 100 MW to 200 MW, the system became

vulnerable to the grid even though it was operating stably prior to that. The doubly fed

induction generators have also become popular in the recent past but they were not included

into this study since the stability of a doubly fed induction wind generator depends mostly on

controller settings rather than on other system parameters.

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study/ Accessed on, 15/8/ 2014.

Shaon Ahmed obtained B.Sc in Electrical and Electronic Engineering from

Khulna University of Engineering and Technology, Bangladesh in 2012 and

M.Sc in Electrical Systems engineering from Unversity Malaysia Perlis,

Malaysia in 2015. He is currently working as Lecturer at the Department of

Electrical and Electronic Engineering, Hamdard University Bangladesh,

Narayangonj, Bangladesh. His research interests include Integration of

Renewable energy, Wind energy, Hybrid Power System and Power System

Reliability and stability.

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Mohd Abdur Rashid received his B.Sc. and M.Eng degrees in Electrical &

Electronics Engineering from BIT Khulna, Bangladesh in 1991 and

University of the Ryukyus, Japan in 2000 respectively. He obtained his Ph.D.

in Electrical and Information Engineering from University of the Ryukyus,

Japan in 2003. He is currently working as Associate Professor at the Faculty

of Design Arts and Engineering Technology, Universiti Sultan Zanial Abidin,

Kuala Terengganu, Malaysia. Dr. Rashid has authored more than 70 technical

papers in the international journals and conferences. He is involved in

multidisciplinary research fields including mathematical modeling, renewable energy,

electronic devices, biomedical engineering and power systems. He is a regular member of

IEEE, IEICE, IAENG and IEB.

Shamshul Bahar YAAKOB received a Bachelor’s degree in Computer

Engineering from Shizuoka University, Japan and a MEng. degree in

Electrical and Electronic Systems from Nagaoka University of Technology,

Japan. Currently he is an Associate Professor in the School of Electrical

System Engineering, Universiti Malaysia Perlis, Perlis, Malaysia. His

research interests include soft computing, reliability optimisation, and multi-

criteria optimisation.

Adawati Yusof obtained Bachelor of Industrial Electronic Engineering (Hons)

in 2009 from University Malaysia Perlis (UniMAP), and MSc in Industrial

Electronic and Control in 2011 from University of Malaya (UM), Malaysia.

She is currently a full time lecturer at the School of Electrical System

Engineering, University Malaysia Perlis (UniMAP), Perlis, Malaysia. Her

research interest includes power system efficiency, renewable energy, and

communication system. She is also a member of Board of Engineer Malaysia

(BEM) and International Association of Engineering (IAENG).

Mohd Fareq bin Abdul Malek obtained PhD in Electrical Engineering

(Radio Frequency and Microwave), University of Liverpool, UK. He

received MSc (Eng) Microelectronic Systems and Telecommunications

(Distinction), University of Liverpool, UK. He got BEng (Hons) Electronic

and Communication Engineering, University of Birmingham, UK. He is

currently working as Associate Professor and holding the position of Dean

in the School of Electrical System Engineering, UniMAP. His research

interests include communication, antenna theory, electromagnetics and so

forth.

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