ANFIS-Fuzzy Logic-based Hybrid DFIG and PMSG Grid

Connected System with TCSC

K.KARTHI, A. RAMKUMAR

Dept of EEE., Kalasalingam Academy of Research and Education (KARE), Srivillliputhu,

Tamilnadu, INDIA

Abstract: Variable-speed wind turbines might provide green electricity. Grid operators' grid

regulations require wind turbines to recover from grid disruptions and help maintain electricity

networks. Having wind turbines equipped with fault current limiters (FCLs) may ensure their

continued functioning in the event of a power loss. In this piece, we will talk about how to improve

the two most common types of variable-speed wind turbines: the Doubly Fed Induction Generator

(DFIG) and the Permanent Magnet Synchronous Generator (PMSG). Both wind generators were

evaluated using the Thyristor Controlled Series Compensator (TCSC) with ANFIS and Fuzzy Logic.

It is important to understand the dynamic behavior of wind turbines, hence models of their FCLs were

built for steady state and grid disruptions. Power interruptions switched the FCLs in both wind

turbines utilising grid voltage variation. Both wind turbines underwent a no-control FCL scenario.

Both wind turbines' FCLs were measured and compared under load from a severe three-phase to

ground failure at their terminals. Both wind turbines were operated under similar circumstances to

examine FCL control tactics during power interruptions.

Keywords: ANFIS, Fuzzy Logic, Total Harmonic Distortions, Wind Energy conversion system, DFIG, and

PMSG Control.

Received: February 23, 2023. Revised: November 15, 2023. Accepted: December 15, 2023. Published: January 30, 2024.

1. Introduction

It is crucial to acquire new methods of

power grid stabilization for smooth operation

[1,2] since wind energy penetration into existing

power grids develops day by day, with an

average projection of 75 GW per year during the

2021-2026 timeframe. Wind farms are an

emerging industry that requires sophisticated

voltage and frequency control to meet their grid

requirements. As a result of the broad operating

window afforded by variable-speed wind turbine

technology [3], these machines are more

common. The two most common types of

variable-speed wind turbines used in current

wind farms are the DFIG and the PMSG.

The development of power electronics

and drives in control mechanisms has greatly

facilitated the transition of wind turbines from

fixed speed to variable speed technology [4,5].

Advantages of fixed-speed wind turbines

include their simplicity, durability, affordability,

and minimal maintenance requirements.

However, there are significant challenges

associated with this type of wind turbine, which

prevent it from being widely used in wind

energy applications. These include a lack of

control over voltage and frequency and the need

for substantial reactive power during grid

disturbances to survive air-gap flux recovery.

Thus, variable-speed wind turbines are

employed in the building of contemporary wind

farms because of their high energy capture

efficiency, effective voltage management, and

lower mechanical drive train stress [6]. Both the

DFIG and PMSG wind turbine technologies use

a series connections of power converters. The

PMSG's high initial cost is owing to its full-rated

power converters, whereas the DFIG's gearbox

system has a lower power converter rating of 20-

30 percent. Active and reactive power

management is simplified by the DFIG

technology's architecture, which links the Rotor

Side Converter (RSC), also known as the

Machine Side Converter (MSC), and the Stator

Side Converter (SSC), also known as the Grid

Side Converter (GSC), through the DC-link

voltage.

These wind turbines have a great pitch

adjustment system that allows them to recover

their voltage after grid disturbances [9,10] and

operate in a broad range to maximize energy

absorption [7,8]. However, the back-to-back

power converter in a PMSG wind turbine is fully

rated, whereas that in a DFIG wind turbine is

only rated at 50%. This kind of wind turbine is

thus more likely to provide optimal adaptability

International Journal of Electrical Engineering and Computer Science

DOI: 10.37394/232027.2024.6.6

K. Karthi, A. Ramkumar

E-ISSN: 2769-2507

Volume 6, 2024

and superior control over active and reactive

power. However, the PMSG's prohibitive

upfront cost is a major drawback. Numerous

control schemes, such as FCLs in DFIG wind

turbines [11–14], reactive power compensation,

crowbar, and DC chopper [15–16], and sliding

mode control for Maximum Power Point

Tracking (MPPT) [17–18], have previously

been reported in the literature. Methods for wind

energy conversion were provided in [22] and the

Fault Ride Through (FRT) assessment of a

DFIG wind turbine was conducted using several

control topologies in [19-21].

However, in [23,24], the DC-link voltage

was maintained at its limit during a grid failure,

and the maximum current and MPPT power

converters for the PMSG wind turbine were

investigated. [25] bolstered the performance of

the PMSG turbine with the aid of a

superconducting fault current limiter (SFCL)

control mechanism. This study investigated the

permanency problems of DFIG and PMSG wind

turbines and how their augmentation evaluations

compare to existing FCLs. Similar studies can be

found in [26-28]. Both types of wind generators'

control topologies and wind turbine-modeling

elements were detailed. Both wind turbines had

a severe bolted three-line-to-ground failure with

no FCL control or augmentation strategy to test

the controllers' robustness. The mathematical

dynamics of inserting SDBR, BFCL, and

CBFCL at the stator of both wind turbines under

similar operating circumstances were also

supplied for fair comparison. Each wind turbine

system used an SDBR with the same effective

size and the same BFCL and CBFCL

parameters. During a grid failure, the grid

voltage was utilized as the switching signal.

Only a small number of articles in the scholarly

literature investigate the presence of these FCLs

in both types of wind turbines. FRT

enhancement of both wind turbines has only

been briefly touched on in a few of the

aforementioned papers.

2. The System Model

2.1 Modelling of DFIG

To simplify, the DFIG may be seen as a

conventional induction generator with a nonzero

rotor [8]. Both the rotor converter, which

regulates the rotational speed of the generator,

and the grid converter, which injects reactive

energy into the grid, make up the power

converter of a wind turbine. The actual and

reactive power components of the grid-side

converter(GSC) are shown in Figure 1.

According to [9], in a synchronously rotating

direct-quadrature (d-q) reference frame, the

dynamic equation of a three-phase DFIG's

voltages and flux connections may be written as

(1) through (8):

2.2. DFIG Control Model

and reactive power is regulated by the

RSC controller, while DC-link voltage and

reactive power injection into the grid are

managed by the grid-side converter (GSC)

controller. In a Graetz bridge configuration,

snubber resistance and capacitance are added to

the RS of a three-phase IGBT-diode rectifier to

dampen vibrations. The DC bus capacitor

voltage is controlled by the grid-side converter

[11]. By adjusting the pitch angle, we can

determine how much energy can be harvested in

strong winds. A torque controller is used in the

control system to maintain a consistent velocity.

The reactive power of the wind turbine is

likewise kept at 0 MVAR. The control

equations, as seen from the rotor, might be

represented in the form of Figure 2.

2.3 Grid Side Controller

Maintaining a fixed DC-link voltage

regardless of the magnitude or direction of the

rotor's power flow [12] is the primary goal of the

GSC. To accomplish this, we use the hysteresis

current control approach shown in Figure 2,

which uses a reference frame that is co-linear

with the stator voltage position. The reactive

power and the DC-link voltage between the

converter and the grid may thus be

independently controlled.

In a voltage vector-oriented reference

frame, the current regulates the DC-link voltage.

Therefore, as illustrated in Figure 2, a reference

current value is calculated by tuning a PI

controller using the DC-link voltage error e and

the error variation.

International Journal of Electrical Engineering and Computer Science

DOI: 10.37394/232027.2024.6.6

K. Karthi, A. Ramkumar

E-ISSN: 2769-2507

Volume 6, 2024

Fig. 1: General block diagram of the proposed system

Fig. 2: Mathematical modeling of Hybrid system

International Journal of Electrical Engineering and Computer Science

DOI: 10.37394/232027.2024.6.6

K. Karthi, A. Ramkumar

E-ISSN: 2769-2507

Volume 6, 2024

3. Thyristor Controlled Series

Compensator

The benefits of series capacitors over

shunt capacitors are substantial. The reactive

power of a series capacitor is proportional to the

square of the line current, whereas the reactive

power of an inductor-capacitor is related to the

square of the short circuit in a bus circuit. The

reactive power rating of a shunt capacitor

typically has to be three to six times higher than

that of a series capacitor to provide the same

system advantages as those of a series capacitor.

Additionally, shunt capacitors often need to be

linked in the middle, while series capacitors have

no such need.

3.1 Operation of TCSC controller.

Continuous control of power on the AC

line is made possible by a TCSC, a series-

regulated capacitive reactance. Analyzing the

operation of a TCSC may be reduced to a few

simple steps by considering the effects of a

variable induction linked in series with a constant

capacitor, as seen in Fig. 3. This combination's

equivalent impedance, Zeq, may be written as

  󰇡 

󰇢󰇛󰇜   



 (1)

If   󰇛 

󰇜    󰇛 

󰇜 , Since

the FC's reactance is below the along a variable

reactor's, the resulting reactance is adjustable

capacitance. If   󰇛 

󰇜  , Inadequate

conditions include the development of a

resonance leading to infinite capacitive

impedance. If   󰇛 

󰇜  , Therefore the

inductance provided by the combination is greater

than that of a fixed inductor. In this case, the

TCSC is operating in its inductive micrometre

mode.

Analysis of a TCSC behaves similarly to that of

an LC parallel combination when the voltage and

current in the circuit are pure sinusoids. In

contrast, thyristor switching causes non-

sinusoidal voltage and current in a TCSC's fuel

cell (FC) and thyristor-controlled reactor (TCR).

Further sections elaborate on how TCSC operates

in detail.

The DFIG and PMSG generator data tables 1

and 2 each include information for one turbine

used in simulations.

TABLE 1: The Design Parameters Of DFIG

Generator Data for one Turbine

Nominal Electrical Power

1.5MVA

Stator Resistance, Rs

0.23p.u.

Rotor Resistance, Rr

0.016 p.u.

Stator Inductance, Ls

0.18 p.u.

Rotor Inductance, Lr

0.16 p.u.

Magnetizing inductance, Lm

2.9 p.u.

Inertia Constant, H

0.685

Pole Pair, p

TABLE 2: The Design Parameters Of PMSG

Generator Data for one Turbine

Nominal Electrical Power

1.5MVA

GS coupling impedance

0.00 p.u.

D.C. Capacitor (V)

1150

Number of pole pairs

Feedback time Constant (s)

2.9 p.u.

Inertia Constant, H

0.005

Pole Pair, p

4. Discussion of the Findings

The PMSG rating system is identical to

the DFIG rating system. Figure 4 depicts the

Simulink equivalent circuit diagram for this

system. To assess the performance of Hybrid

PMSG and DFIG in terms of output powers

(P&Q), voltages and current, THD, and dynamic

responses with ANFIS and with Fuzzy based

TCSC, a failure (time = 1 Sec to 1.75 Sec) is

simulated for both machine side bus (B575). The

active and reactive powers are given in Figs. 5,

6, and 7, respectively, for comparison. The

oscillations in DFIG+PMSG with ANFIS-based

TCSC active power are demonstrated in Figure

10 to be substantially lower than those in

DFIG+PMSG with Fuzzy based TCSC during

fault. DFIG and PMSG with ANFIS based

TCSC attain steady-state values after 3.5

seconds, however, with Fuzzy based TCSC, they

continue to fluctuate even after 5 seconds. In

addition, Figure 11 depicts the reaction of DFIG

and PMSG reactive power with ANFIS based

and with Fuzzy based TCSC. Reactive power

regulation with ANFIS based TCSC at zero

International Journal of Electrical Engineering and Computer Science

DOI: 10.37394/232027.2024.6.6

K. Karthi, A. Ramkumar

E-ISSN: 2769-2507

Volume 6, 2024

MVAR is much superior than that with Fuzzy

based TCSC during a malfunction. During a

fault, the reactive power deviation from zero

MVAR is substantially lower with ANFIS based

TCSC than with Fuzzy based TCSC, but once

the fault is cleared, the reactive power of with

Fuzzy based TCSC recovers to zero in a much

shorter time than with ANFIS based TCSC. As

a result, if a system requires that reactive power

be controlled at zero MVAR for an extended

period and abrupt large deviations are permitted,

then a system with Fuzzy based TCSC may be a

preferable solution. Still, if a system requires

that reactive power not move too much from

zero MVAR, TCSC may be a preferable

alternative. Figure 8 shows a voltage

comparison with ANFIS based and with Fuzzy

based TCSC. During the fault, the voltage of

DFIG and PMSG with ANFIS based TCSC

oscillates roughly 10% more than the voltage of

DFIG and PMSG with Fuzzy based TCSC

owing to flux oscillations necessary to supply

the reactive power. This is because speed is

inversely related to flux. Furthermore, DFIG and

PMSG with ANFIS based TCSC have greater

inertia due to their heavier weight than DFIG

and PMSG with Fuzzy based TCSC. The

voltage and current of DFIG and PMSG with

ANFIS based TCSC achieve steady-state in a

much shorter time than DFIG and PMSG with

Fuzzy based TCSC. DFIG and PMSG with

ANFIS based TCSC achieve a steady-state value

at t = 2.5 seconds, but DFIG and PMSG with

Fuzzy based TCSC fluctuate even at t = 4.5

seconds. As a result, if the voltage and current

control are more important, DFIG and PMSG

with ANFIS based TCSC should be utilized;

otherwise, DFIG and PMSG with Fuzzy based

TCSC might be employed. THDs of voltages of

DFIG and PMSG with Fuzzy based TCSC and

DFIG and PMSG with ANFIS based TCSC are

shown in Figs. 8 and 9, respectively, owing to

fault. They demonstrate that harmonic distortion

is lower in DFIG and PMSG with ANFIS based

TCSC than in DFIG and PMSG with Fuzzy

based TCSC; hence, power quality is optimum

when DFIG and PMSG with ANFIS based

TCSC are used with ANFIS based an innovative

power electronic interface. As a result, it is

determined that DFIG and PMSG with ANFIS

based TCSC are more effective as wind turbine

generators than DFIG and PMSG with Fuzzy

based TCSC, and that unconventional power

electronic interfaces are more effective as

interfaces than standard power electronic

interfaces

Fig. 3: The Simulink equivalent circuit diagram of DFIG and PMSG with ANFIS based TCSC

system

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Volume 6, 2024

Fig. 4: Simulink diagram of DFIG system

Fig. 5: Simulink diagram of PMSG with machine side and grid side controller

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Fig. 6: Simlink diagram of TCSC controller

(a)

(b)

Fig. 7: Grid Side Output Voltage Fault created from 1 Sec to 1.75 Sec (a) DFIG and PMSG with

Fuzzy based TCSC (b) DFIG and PMSG with ANFIS based TCSC

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(a)

(b)

Fig. 8: Grid Side Output Current during the fault condition (Fault created from 1 Sec to 1.75 Sec) (a)

with ANFIS based TCSC (b) with ANFIS based Fuzzy based TCSC

(a)

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(b)

Fig. 9: Real power during the fault condition (Fault created from 1 Sec to 1.75 Sec) (a)with ANFIS

based TCSC (b) with Fuzzy based TCSC

(a)

Fig. 10: Reactive power during the fault condition (Fault created from 1 Sec to 1.75 Sec) (a) with

ANFIS based TCSC (b) with Fuzzy based TCSC

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(a)

(b)

Fig. 11: DC link voltage with ANFIS based TCSC (b) with Fuzzy based TCSC

Fig. 12: Gate pulse

(a)

(b)

Fig. 13: THD Values (a) with Fuzzy based TCSC (b) with ANFIS based TCSC

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Fig. 14: Fuzzy logic rule viewers

(a)

(b)

(c)

Fig. 15: ANFIS based output (a) Surface

Window (b) ANFIS Designer Window (c)

ANFIS Structure Window

5. Conclusion

As a consequence, DFIG and PMSG with

ANFIS based TCSC are more effective wind

turbine generators than those with FUzzy based,

and unconventional power electronic interface is

more effective than standard power electronic

interface. The comparison may be summed up

by noting that during a fault, DFIG and PMSG

with FUzzy based TCSC both use more reactive

power than DFIG and PMSG with ANFIS based

TCSC consume under the same circumstances,

even after the improvement. The modifications

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Volume 6, 2024

made to the DFIG and PMSG with Fuzzy based

TCSC control assist in the oscillation reduction

part of the machine's dynamic behavior. It takes

far longer for DFIG and PMSG with Fuzzy

based TCSC to recover their permanence than it

does for DFIG and PMSG with ANFIS based

TCSC, which implies that DFIG and PMSG

with ANFIS based TCSC are more dependable

than DFIG. On the other hand, the performance

of the DFIG and PMSG with ANFIS based

TCSC wind turbine was improved utilizing the

TCSC with 9% overshoot and 2.35 s settling

time for the actual and reactive power. The THD

values were with ANFIS based TCSC at 1.67%

with Fuzzy based TCSC at 28.35%. Moreover, a

quicker settling time was also seen employing

the TCSC for DFIG and PMSG. Except for the

terminal grid voltage variable, the ANFIS based

TCSC improved the performance of the DFIG

and PMSG. To achieve optimal fault ride-

through performance for a given application, it

is advised to couple TCSC-based variable speed

wind turbines with the DFIG and PMSG.

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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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International Journal of Electrical Engineering and Computer Science

DOI: 10.37394/232027.2024.6.6

K. Karthi, A. Ramkumar

E-ISSN: 2769-2507

Volume 6, 2024