An Approach to Improve Power System Resiliency in Grid-Connected

Wind Turbine Generator Power System

KUNAL A. BHATT1, ASHESH M. SHAH2, VISHAL KUMAR GAUR3

1Department of Electrical Engg.,

L. D. College of Engineering,

Ahmedabad, Gujarat,

INDIA

2Department of Electrical Engg.,

Government Engg. College,

Bharuch, Gujarat,

INDIA

3Department of Electrical Engg.,

Motilal Nehru National Institute of Technology,

Allahabad, UP,

INDIA

Abstract: - A new concept of optimal Point-on-wave (PoW) switching to curtail the power system resiliency of

the wind power plant connected with a transformer is presented. Optimal PoW switching targets are determined

using mathematical analysis and tested on the simulation model. The said simulation model has been developed

using PSCAD/EMTDC software for system parameters of the existing wind power plant electrical network of

Gujarat, India. The proposed optimal PoW-based method is capable of reducing the magnetizing inrush current

exceptionally. Further, the proposed technique is also efficient in smoothening the voltage profile and

decreasing harmonic contents in the supply, which improves the power quality of the wind power plant

electrical network. Afterwards, to demonstrate the proposed technique based on optimal PoW, a hardware

model has been developed in a laboratory environment. The result of the hardware model provides a promising

outcome as proof of the proposed technique. In the end, a comparative evaluation with a recently developed

technique is also carried out where it has been observed that the proposed technique is providing superior

results.

Key-Words: - Point on the wave, Wind power, switching transients, Wind turbine to grid-connected

transformer, the magnetizing inrush of the transformer, harmonic contents in magnetizing

inrush.

Received: August 27, 2023. Revised: February 22, 2024. Accepted: March 19, 2024. Published: May 31, 2024.

1 Introduction

To minimize the level of greenhouse emissions and

other environmental problems, power engineers

around the globe are continuously improving

sustainable solutions to promote green energy, [1].

In this regard, solar, wind, and biomass power

plants have been found the most trustworthy

options to replace as a substitute for the fossil fuel-

based conventional energy sources, [2]. It is to be

noted that wind power plants have achieved huge

growth in the field of sustainable energy across the

world. Further, asynchronous Wind Turbine

Generators (WTG) have attained higher priority in

comparison with other peer generators in recent

decades due to exponential growth in power

electronic devices. [1], [3], [4],. However, the main

disadvantage of such types of WTGs is their poor

responses to voltage and frequency profiles during

switching and load variation, [5], [6].

Owing to uncertainty in the weather conditions,

the power generation of the wind plants varies by a

large amount. Subsequently, the penetration of the

wind power plant-based energy sources in the

conventional grid causes frequent switching

operations. These frequent switching operations

cause power quality issues at the distribution level

WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

[1], [7], [8]. Thereafter, an approach to improve

power quality for wind-based distributed

generation systems using Lorentzian norm-based

adaptive filters has been discussed in [7]. However,

the selection of parameters for adaptive features is

very critical in this method. Though the above-

proposed methods have provided power quality

solutions, these methods have not brought out a

reliable solution in the case of magnetizing inrush

which has been produced during switching of

WTG.

Afterward, CIGRE working group carried out a

detailed study of power resiliency problems on

WTG considering the real-time system in the UK,

[9]. In the above discussion, it is to be observed

that WTG has been connected to a conventional

grid at an extra high voltage level using a step up

transformer. In this case, the transformer causes a

high magnetizing inrush current during

energization which is drawn from the WTG.

Subsequently, this event leads to the development

of a voltage dip in the distribution network which

may cause adverse effects on the equipment

working in the same network, [9]. Additionally, the

level of harmonic contents at the Point of Common

Coupling (PCC) in the distribution network also

increases owing to high inrush current, [10].

Moreover, the dc component of inrush current

further causes saturation in the instrument

transformer connected to the bus of the distribution

network, which may lead to the mal-functioning of

the protective system.

To minimize the level of inrush current (LIC)

during the energization of the transformer in the

grid-connected WTG network, PoW switching

techniques have been suggested in [11], [12], [13].

The application of PoW technique to minimize the

switching transient levels during the energization of

various power system equipment have also been

discussed in [14], [15], [16], [17]. Further, the

effect of operating time variation of circuit breaker

has been considered during the application of PoW

switching for energization of power system

components as explained in [18].

Brunke and his team members have presented

the application of a PoW strategy to mitigate the

inrush current during the energization of the power

transformer based on residual flux levels, [19],

[20]. Thereafter, Chandrasena et. al performed the

PoW switching technique for the energization of

the transformer on a real-time platform, [21].

However, the effect of statistical and systematic

variations of the circuit breaker is required to

minimize the inrush current in above proposed

techniques. In [22] and [23], heuristic search-based

algorithms have been presented to mitigate the mal-

operation of the differential relay during the

energization of a transformer. Though these

algorithms offer high accuracy, the choice of

parameters is the key limitation of the heuristic-

based techniques and also increases the protection

cost for the distribution network. In the above

methods, the level of residual flux in the core,

resistances of the primary and secondary windings,

magnetizing characteristic of the iron core, and

switching instant of the source side voltage play a

vital role in deciding the amount of inrush current,

[24].

Owing to the low moment of inertia and low

level of short circuit current capacity compared to

conventional power stations, the wind farm has

been considered a weak source of power

generation, [24]. During random energization, a

wind farm to grid-connected transformer draws

high inrush current and subsequently, it develops

voltage dip and other power resiliency problems in

the distribution network. Further, the dc offset

component of the inrush current causes saturation

in the core of the instrument transformer, which

further leads to the development of mal-operation

in the protection system. Thus, to mitigate the

magnetizing inrush current in the wind power plant,

an application of PoW for the energization of Wind

Farm to a connected Transformer has been

discussed in this paper. Initially, the frequency of

supply has been determined using the zero-crossing

technique. Afterward, the first phase to be closed

has been decided based on the peak of the reference

phase for different types of transformer

configuration, which results in a reduction in inrush

current, voltage dip, and harmonic contents. Thus,

the proposed method indicates improvement of the

power resiliency problems in grid-connected wind

power system networks.

2 Effect of Random Energization of

the Transformer Connected with

WTG

A wind farm to grid-connected transformer draws

high inrush current during random energization. In

turn, it also produces voltage dip and other power

resiliency problems in the distribution network.

Further, the dc offset component of the inrush

current may also lead to saturation in the core of

the instrument transformer. Henceforth, to

determine the LIC, voltage dip harmonic contents

& dc offset, a simulation study in the

PSCAD/EMTDC software package has been

WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

carried out and the results have been depicted in

Figure 1. Figure 1(a), (b) and (c) show the LIC,

voltage dip and fundamental, harmonic & dc

contents respectively. It is to be noted that the first

phase has been switched on at zero crossing instant

and the remaining two phases after 5 ms. Further,

the short circuit capacity of the source has been

considered as 5 kA for WTG during the simulation

study.

It has been observed from Figure 1(a) and (b)

that the LIC and voltage dip during the energization

have been found as 2.89 pu and 0.827 pu,

respectively. Further, Figure 1 (c) shows the level

of fundamental component (I1), 2nd to 7th harmonic

contents (Ih2 to Ih7), and dc offset (Idc) of the

magnetizing inrush current of phase-c which attains

the highest level of inrush current in a simulation

study. It has been observed from Figure 1 (c) that

the levels of Ih2 and Idc attain high levels of

magnitude. Thus, from Figure 1, it has been

observed that LIC, harmonic components, and dc

offset lead to create voltage dip, power quality

issues, and power system resiliency problems in the

distribution network.

Fig. 1: Level of (a) inrush current, (b) voltage dip,

and (c) harmonics contents during energization of

wind to grid connected transformer

3 Optimal PoW-based switching

Techniques

To illustrate the Optimal PoW-based switching

technique for improving power system resiliency,

the network configuration, mathematical derivation

of PoW targets, and proposed techniques have been

described in the following sub-sections.

3.1 Network Configuration

The Single Line Diagram (SLD) of WTG

connected with the grid existing in Gujarat, India

has been shown in Figure 2. The whole system

illustrated in Figure 2 has been implemented in the

PSCAD/EMTDC software package. As shown in

Figure 2, the wind farm consists of ten units of 1.5

MW each. Hence, the total generation offered by

the wind farm has been considered as 15 MW.

Further, the voltage generated by WTG is 0.4 kV

which is stepped up to 11 kV using transformer T1,

which is connected in Δ/Y configuration. Then, to

connect this wind farm to the grid, two other

transformers T2 (11/400 kV) and T3(11/230 kV)

are connected in parallel. The parameters of these

transformers have been mentioned in the Table 1. It

is to be noted that at any instant, only one of the

secondaries (either 400 kV or 230 kV) remained in

connection, and at any point in time, any

transformer (either T2 or T3) remained in the

circuit.

Fig. 2: Single line diagram of WTG existed in

Gujarat, India

3.2 Mathematical Derivation of PoW

Targets

To determine the PoW closing targets for the

energization of Wind Farm to Grid Connected

Transformer, a Resistance-Inductance (R-L) series

circuit connected with an ac source supply has been

considered. In this case, the supply voltage at any

instant is represented by eq. (1).

󰇛󰇜 󰇛󰇜

(1)

Where,  is maximum voltage, is phasor

rotating frequency and  is the energization

instant of the circuit.

In case of R-L series circuit, the power factor

angle (󰇜 of the circuit is determined by eq. (2)

WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

  



(2)

When an R-L series circuit has been switched on, it

develops two components namely (i) steady-state

component and (ii) exponentially decaying

transient component as indicated in eq. (3).

󰇛󰇜

󰇥󰇟󰇛󰇜󰇠

󰇛󰇜

󰇦

(3)

It is to be noted from eq. (3) that the transient

turns to be zero when =. This indicates that

when the switching angle is becoming equal to the

power factor angle, the transient term attaints zero

magnitude. Hence, to minimize the level of the

switching transient, the switching instant is to be

determined from the power factor angle. In the case

of a transformer, the inductive reactance () of

the winding is very high in comparison to winding

resistance (R). Hence, power factor angle 

becomes equal to π/2 as per eq. (2). Therefore, if

the switching instant has to be made equal to

π/2 (i.e. instant to attend the peak of reference

voltage), the magnitude of current becomes almost

equal to steady state current during switching on

the instant. This criterion has been utilized in the

proposed technique to mitigate the magnetizing

inrush for improving power system resiliency.

Table 1. Details of wind farm to grid-connected

transformer

Knee point voltage

1.1 pu

Magnetizing current

1% of rated current

3.3 Proposed Technique

Figure 3 shows a flowchart of the proposed

technique. Whenever a change-over command is

detected by the circuit breaker, the data regarding

the transformer connection is collected. To decide

the deliberated time delay by the PoW device for

the circuit breaker closing instant, it is essential to

find the zero-crossing instant of the reference

voltage (i.e. voltage of phase-a for three-phase

system in this paper). Finding the zero-crossing

instant is not only deciding the time delay for the

circuit breaker closing instant but it also benefits in

finding accurate frequency whose variation is

found continuously during power system operation.

Thus, the frequency has been found based on the

time lapse between two consecutive zero crossing

instants.

After finding the frequency and converting this

frequency into a timestamp, the deliberate time

delay between the first peak to be closed on phase –

a and the last zero crossing instant has been

calculated, [25]. Subsequently determining the

deliberate time delay, the PoW based closing

targets for different types of connection of the

transformers have been identified. Thereafter,

based on the type of transformer connection, the

PoW closing commands have been given to the

closing coils of the different phases of the circuit

breaker. As mentioned, firstly, phase–a has been

energized, and thereafter, the remaining two phases

have been switched on after 5 ms depending upon

the type of transformer connection.

Fig. 3: Flowchart of Proposed method

4 Results and Analysis

4.1 Simulation Results

To test the performance of the proposed technique,

a simulation study on SLD shown in Figure 2 has

been carried out using PSCAD/EMTDC software.

As shown in Figure 2, transformer T1 has been

energized by closing the circuit breaker CB1.

Before providing a closing command to coils of

CB1, the frequency of the supply has been

determined by using the zero-crossing technique.

Hence, based on the measured frequency, the time

delay between the first peak of phase – a has been

found out. After the said time delay, the PoW

WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

command to the circuit breaker CB1 has been given

for energization of Δ/Y connected transformer T1

on phase – a. Further, the remaining two phases

(phase – b and then phase – c) have also been

energized as mentioned in the proposed method.

The obtained results of magnetizing inrush,

voltage, and harmonic contents have been depicted

in Figure 4. As shown in Figure 4 (a), the LIC has

been observed to be 0.025 pu which is quite less

than 2.89 pu which has been found during random

switching. Moreover, the voltage profile has also

been found to be 1 pu in all phases of the

transformer during energization compared to 0.827

pu in the case of random energization. Hence, the

voltage dip has been reduced in this case and power

system resiliency has been improved. Furthermore,

the fundamental, harmonic contents and dc

decaying has been also observed as indicated in

Figure 4 (c). As shown in Figure 4 (c), the

magnitude of all the mentioned quantities has been

reduced drastically using the proposed PoW

technique.

Fig. 4: Level of (a) inrush current, (b) voltage dip,

and (c) harmonics contents during energization of

wind to grid connected transformer using proposed

technique

4.2 Hardware Setup

A prototype to validate the proposed technique has

been developed in the laboratory and the obtained

result is shown in Figure 5. Figure 5(a) illustrates

the block diagram of the hardware setup. As shown

in Figure 5 (a), the current signal has been collected

and they are sent to the zero crossing detection

circuit. The said circuit consists of a combination

of a rectifier and optocoupler which rectifies the

input current signal and finds the interruption of

input current at zero crossing. This zero crossing is

sensed by Arduino and processed to calculate the

frequency. In Arduino, software coding has already

been executed for zero crossing detection,

calculation of frequency, determination of optimal

closing instant, and triggering signal to solid state

device using IDE open-source software in

computer system. Hence, after determining the

frequency of the supply accurately, the time taken

to reach the peak of voltage has been calculated

and the optimal switching instant has been found.

At this instant, Arduino provides trigger commands

to the solid state switch at the peak of the voltage

wave in the transformer.

Figure 5(b) illustrates the snapshot of the

hardware setup which shows the computer system,

zero crossing detector circuit, Arduino circuit, solid

state switching, transformer (which is to be

energized), and digital signal oscilloscope. On

receiving the triggering signal, the solid-state

device turns on and the transformer energizes. This

energized current signal has been captured in a

digital signal oscilloscope and is shown in Figure 5

(c). As depicted in Figure 5 (c), the LIC is found to

be 0.085 pu which indicates the satisfactorily low

value of inrush in comparison to random

energization of the transformer. The details about

apparatus used for hardware set up is shown in

Table 2.

Table 2. Details about hardware setup

Apparatus

Specifications

Transformer

1.5 KVA, 440/230 volts

Solid state device

Triac, BTA41, 600 volts

Microcontroller

Arduino controller

4.3 Comparative Analysis

The proposed method based on Optimal PoW-

based technique has been examined in connection

with other published research articles based on [10]

and the results are depicted in Table 3. It has been

noticed from Table 3 that LIC is relatively lower in

the proposed technique in comparison with

published articles for simulation as well as

hardware results. In addition, it is also observed

that the voltage profile has also been improved

satisfactorily during simulation. The same result

has also been achieved with hardware setup.

WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

Fig. 5: Hardware setup: (a) Block diagram, (b) Snapshot of setup, and (c) LIC

Table 3. Comparative analysis of suggested

scheme with published research article, [10]

Sr.

No.

Nomenclature

Proposed

Technique

Published

research

article in [10]

Simulation Results

LIC (pu)

0.025

1.44

Voltage level

(pu)

0.993

Hardware Results

LIC (pu)

0.085

0.54

5 Conclusion

A new optimal PoW-based technique is presented

to improve the power system resiliency in the wind

power plant connected with the transformer.

Initially, optimal PoW instant has been found using

mathematical analysis. Afterwards, a simulation

model for the wind power plant electrical network

of Gujarat, India has been developed in the

PSCAD/EMTDC software package. During

simulation, the application of optimal PoW instant

is remarkably reducing magnetizing inrush,

improving voltage profile, and decreasing harmonic

contents of current. Further, the analysis of the

proposed technique has also been carried out with

the help of hardware setup in a laboratory

environment whose outcome exceptionally

increases the reliability of the proposed method. In

the end, a comparative analysis of the proposed

technique with the recently presented method

provides improved results. In the future, work will

be performed to develop an algorithm for carrying

out PoW switching using the Internet of Things and

Artificial Intelligence.

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E-ISSN: 2224-266X

Volume 23, 2024

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DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024

Contribution of Individual Authors to the

Creation of a Scientific Article (Ghostwriting

Policy)

The authors equally contributed in the present

research, at all stages from the formulation of the

problem to the final findings and solution.

Sources of Funding for Research Presented in a

Scientific Article or Scientific Article Itself

No funding was received for conducting this study.

Conflict of Interest

The authors have no conflicts of interest to declare.

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(Attribution 4.0 International, CC BY 4.0)

This article is published under the terms of the

Creative Commons Attribution License 4.0

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WSEAS TRANSACTIONS on CIRCUITS and SYSTEMS

DOI: 10.37394/23201.2024.23.8

Kunal A. Bhatt, Ashesh M. Shah, Vishal Kumar Gaur

E-ISSN: 2224-266X

Volume 23, 2024