Implementation of STATCOM- Control Scheme for Power Quality Improvement using PI and Fuzzy logic controller SK International Journal of Multidisciplinary Research Hub

ISSN: 2394­3122 (Online)  Volume 2, Issue 8, August 2015 

SK   International Journal of Multidisciplinary Research Hub

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Research Article / Survey Paper / Case Study  Published By: SK Publisher (www.skpublisher.com) 

Implementation of STATCOM- Control Scheme for Power Quality Improvement using PI and Fuzzy logic controller

Rakesh S. Kumbhare¹ Dept. of Electrical Engineering

TGPCET, Mohgaon Nagpur, India

Dr. Harikumar Naidu² Head Dept. of Electrical Engineering

TGPCET, Mohgaon Nagpur, India

Abstract:

Keywords: Fuzzy logic controller (FLC), International Electro-technical Commission (IEC), Point of common coupling , PI Controller, Power Quality,, STATCOM, Total harmonic Distortion (THD), Wind Generating System .

I. INTRODUCTION

With the increase in demand for Electricity due to increase in population and industrialization, the generation of power is really a challenge now a days. It is necessary to meet the energy needs by utilizing the renewable energy resources like wind, biomass, hydro co-generation, etc. Both electric utilities and end users of electric power are increasingly concerned about the quality of power. Power quality can be defined as “any power problem manifested in voltage, current and frequency those results in failure or maloperation of the customer equipment”. Injection of the wind power into an electric grid affects the power quality. The main power quality issues are voltage sag, swell, flickers; harmonics etc. [1].The power quality is an essential customer-focused measure and is greatly affected by the operation of a distribution and transmission network. The issue of power quality is of great importance to the wind turbine [2].One of the simple methods of running a wind generating system is to use the induction generator connected directly to the grid. The induction generator has inherent advantages of cost effectiveness and robustness. However, induction generators require reactive power for magnetization. When the generated active power of an induction generator is varied due to wind, absorbed reactive power and terminal voltage of an induction generator can be significantly affected. Here proposing a STATCOM based control technology for mitigating the power quality issues when we are integrating wind turbine to the grid [1-2].

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             29 | P a g e   A STATCOM based control technology has been proposed for improving the power quality which can technically manages the power level associates with the commercial wind turbines. The proposed STATCOM control scheme for Grid connected wind energy generation for power quality improvement has following objectives.

» Unity power factor at the source side.

» Reactive power support only from STATCOM to wind Generator and Load [2].

The work analyses the performance of Static Compensator (STATCOM) with a wind energy generating system connected at the point of common coupling with the existing power system to mitigate the power quality issues [1].

Conventionally, PI, PD, and PID controller are most popular controller and widely used in most power electronic appliances however recently there are many researchers reported successfully adopted Fuzzy Logic Controller (FLG) to become one of intelligent controller to their appliances. With respect to their successful methodology implementation, this kind of methodology implemented this paper is using fuzzy logic controller with feedback by introduction of voltage respectively. The introduction of change in voltage in the circuit will be fed to fuzzy controller for this proposes. This study demonstrates the power quality problems due to installation of wind turbine with the grid.

Here proposing a STATCOM based control technology for mitigating the power quality issues when we are integrating wind farms to the grid. In the event of increasing grid disturbances, a battery energy storage system is required to compensate the fluctuation generated by wind turbine. Here two control schemes for STATCOM is designed and compared: Bang-Bang Current controller and fuzzy logic controller. PI controller plays an important role in reducing fluctuating voltage error signal efficiently. Simulation result shows that the proposed SVC and STATCOM with PI controller is efficient in mitigating voltage sags and thus improving the power quality of the power grid. Fuzzy logic technique has been used as it has advantage of robustness, easily adaptive fast technology is also used and best results are achieved when compared to conventional PI technique.

II. POWER QUALITY PROBLEMS,STANDARDS,ISSUES AND ITS CONSEQUENCES

2.1The various power quality problems are:

» Voltage sags

» Micro-interruptions

» Long interruptions

» Voltage spikes

» Voltage swells

» Voltage fluctuations

» Voltage unbalance

» Noise

» Harmonic distortion

2.2 International Electro Technical Commission Guidelines

The guidelines are provided for measurement of power quality of wind turbine. The International standards are developed by the working group of Technical Committee-88 of the International Electro-technical Commission (IEC), IEC Standard 61400-21 describes the procedure for determining the power quality characteristics of the wind turbine.

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The standard norms are specified.

1. IEC 61400-21: Wind turbine generating system, part-21.Measurement and Assessment of power quality characteristic of grid connected wind turbine.

2. IEC 61400-13: Wind Turbine—measuring procedure in determining the power behavior.

3. IEC 61400-3-7: Assessment of emission limits for fluctuating load IEC 61400-12: Wind Turbine performance.

The data sheet with electrical characteristic of wind turbine provides the base for the utility assessment regarding a grid connection.

2.3 Voltage Variation

The voltage variation issue results from the wind velocity and generator torque. The voltage variation is directly related to real and reactive power variations. The voltage variation is commonly classified as under:

» Voltage Sag/Voltage Dips.

» Voltage Swells.

» Short Interruptions.

» Long duration voltage variation.

The voltage flicker issue describes dynamic variations in the network caused by wind turbine or by varying loads. Thus the power fluctuation from wind turbine occurs during continuous operation. The amplitude of voltage fluctuation depends on grid strength, network impedance, and phase-angle and power factor of the wind turbines. It is defined as a fluctuation of voltage in a frequency 10–35 Hz.

2.4 Harmonics

The harmonic results due to the operation of power electronic converters. The harmonic voltage and current should be limited to the acceptable level at the point of wind turbine connection to the network. To ensure the harmonic voltage within limit, each source of harmonic current can allow only a limited contribution, as per the IEC-61400-36 guideline. The rapid switching gives a large reduction in lower order harmonic current compared to the line commutated converter, but the output current will have high frequency current and can be easily filter-out.

2.5Wind Turbine Location in Power System

The way of connecting the wind generating system into the power system highly influences the power quality. Thus the operation and its influence on power system depend on the structure of the adjoining power network.

2.6 Self-Excitation of Wind Turbine Generating System

The self-excitation of wind turbine generating system (WTGS) with a synchronous generator takes place after disconnection of wind turbine generating system (WTGS) with local load. The risk of self-excitation arises especially when WTGS is equipped with compensating capacitor. The capacitor connected to induction generator provides reactive power compensation. However the voltage and frequency are determined by the balancing of the system. The disadvantages of self- excitation are the safety aspect and balance between real and reactive power .

2.7 Consequences of the Issues

The voltage variation, flicker, harmonics causes the malfunction of equipment namely microprocessor based control system, programmable logic controller; adjustable speed drives, flickering of light and screen. It may leads to tripping of

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             31 | P a g e   contractors, tripping of protection devices, stoppage of sensitive equipment like personal computer, programmable logic control system and may stop the process and even can damage of sensitive equipment. Thus it degrades the power quality in the grid.

III. TOPOLOGY FOR POWER QUALITY IMPROVEMENTS

The STATCOM is a three- phase voltage source inverter having the capacitance on its DC link and connected at the point of common coupling. The STATCOM injects a compensating current of variable magnitude and frequency component at the bus of common coupling. The STATCOM based current control voltage source inverter injects the current into the grid in such a way that the source current are harmonic free and their phase-angle with respect to source voltage has a desired value. The injected current will cancel out the reactive part and harmonic part of the load and induction generator current, thus it improves the power factor and the power quality. To accomplish these goals, the grid voltages are sensed and are synchronized in generating the current command for the inverter. The proposed grid connected system is implemented for power quality improvement at point of common coupling (PCC), as shown in Fig 1

Fig. 1 Grid connected System for power quality Improvement

3.1. Wind Energy Generating System

In this configuration, wind energy generation is based on constant speed topologies with pitch control turbine. The induction generator is used in the proposed scheme because of its simplicity; it does not require a separate field circuit, it can accept constant and variable loads, and has natural protection against short circuit. The available power of wind energy system is presented as:

P wind = ½ ρAV³wind ……… (1)

Where ρ = air density (kg/m3) , A = area swept out by turbine blade (m ), Vwind = wind speed ( m/s).

It is not possible to extract all kinetic energy of wind. Thus extracts a fraction of the power called power coefficient ‘Cp’ of the wind turbine, and is given by:-

P mech = Cp P wind --- (2) The mechanical power produced by wind turbine is given by:-

P mech = ½ ρΠR²V³wind Cp --- (3) Where, R = Radius of the blade (m).

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

3.2. STATCOM

Fig. 2 Basic Statcom Scheme

A STATCOM is analogous to an ideal synchronous machine, which generates a balanced set of three sinusoidal voltages at minimizing its environmental impact. the fundamental frequency with controllable amplitude and phase angle. This ideal machine has no inertia, is practically instantaneous, does not significantly alter the existing system impedance, and can internally generate reactive (both Capacitive and inductive) power. Fig 2. Basic model of a STATCOM

Figure 2 shows the basic model of a STATCOM which is connected to the ac system bus through a coupling transformer.

The STATCOM is a shunt-connected reactive-power compensation device that is capable of generating and/ or absorbing reactive power and in which the output can be varied to control the specific parameters of an electric power system. It is in general a solid-state switching converter capable of generating or absorbing independently controllable real and reactive power at its output terminals when it is fed from an energy source or energy-storage device at its input terminals.

Specifically, the STATCOM, which is a voltage-source converter which when fed from a given input of dc voltage, produces a set of 3-phase ac-output voltages, each in phase with and coupled to the corresponding ac system voltage through a relatively small reactance (which is provided by either an interface reactor or the leakage inductance of a coupling transformer).

The DC voltage is provided by an energy-storage capacitor.

A STATCOM can improve power-system Performance like:

1. The dynamic voltage control in transmission and distribution systems, 2. The power-oscillation damping in power transmission systems, 3. The transient stability;

4. The voltage flicker control; and

5. The control of not only reactive power but also (if needed) active power in the connected line, requiring a dc energy source.

Furthermore, a STATCOM does the following:

1. It occupies a small footprint, for it replaces passive banks of circuit elements by compact electronic converters;

2. It offers modular, factory-built equipment, thereby reducing site work and Commissioning time; and 3. It uses encapsulated electronic converters, thereby

3.3. System Operation

The shunt connected STATCOM with battery energy storage is connected with the interface of the induction generator and non-linear load at the PCC in the grid system. The STATCOM Compensator output is varied according to the controlled strategy, so as to maintain the power quality norms in the grid system. The current control strategy is included in the control scheme that defines the functional operation of the STATCOM compensator in the power system. A single STATCOM using insulated gate bipolar transistor is proposed to have a reactive power support, to the induction generator and to the nonlinear load in the grid system. The main block diagram of the system operational scheme is shown in fig 3.

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Fig.3.System operational schemes in grid system.

IV. CONTROL SCHEME

The first control scheme approach is based on injecting the currents into the grid using hysteresis current controller. The controller uses a hysteresis current controlled technique as shown in Fig 4. Using such a technique, the controller keeps the control system variable between the boundaries of hysteresis area and gives correct switching signals for STATCOM operation.

The current controller block receives reference current and actual current as inputs and are subtracted so as to activate the operation of STATCOM in current control mode.

The control algorithm needs the measurements of several variables such as three-phase source current , source voltage , inverter current with the help of sensor. The current control block, receives an input of reference current and actual current are subtracted so as to activate the operation of STATCOM in current control mode.

Fig.4 Control system scheme

4.1. Grid Synchronization

In the three-phase balance system, the RMS source voltage amplitude is calculated from the source phase voltages (Vsa, Vsb, Vsc) and is expressed as sample template (sampled peak voltage),Vsm :

Vsm =√{2/3(V²sa+V²sb+V²sc)} --- (4)

The in-phase unit vectors are obtained from source voltage in each phases and the RMS value of unit vector is shown below.

Usa =Vsa/Vsm

Usb =Vsb/Vsm --- (5) Usc =Vsc/Vsm

The in-phase reference currents generated are derived using in-phase unit voltage template as shown below.

i*sa=I* usa, i*sb=I*usb, i*sc= I* usc ---- (6)

Where ‘I’ is proportional to magnitude of filtered source voltage for respective phases. This ensures that the source current is controlled to be sinusoidal.

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

4.2 Hysteresis Current Controller

It is implemented in the current control scheme. The reference current is generated as in equation (6) and actual current are detected by current sensors and are subtracted for obtaining a current error for a hysteresis based current controller. Thus the ON/OFF switching signals for IGBTs of STATCOM are derived from hysteresis controller.

The switching function SA for phase ‘a’ is expressed as

isa < (i*sa –HB) →SA =0

isa > (i*sa –HB) →SA =1 ---(7) This is same for phases ‘b’ and ‘c’

4.3 PI controller

The PI controller is traditionally suitable for second and lower order system. It can also be used for higher order plants with dominant second order behavior. The Ziegler-Nichols (Z-N) methods rely on open-loop step response or closed loop frequency tests, are usually used to determine the values of PI controller. In our case, the values of tuning parameters obtained are Kp=

350 , Ki= 85. Usually, these obtained values are only initial values of PI controller and need to be adjusted repeatedly through computer simulation until the closed loop system performs or compromises are satisfied.

The STATCOM control block diagram is shown in Fig. The voltage regulator is of proportional plus integral type.

The integral term in a PI controller causes the steady error to zero. The Proportional Integral (PI) algorithm computes and transmits a controller output signal every sample time to the final control element. The gains of the PI controller can be selected by trial and error method. It performs lack of derivative action may make the system steadier in the steady state in the case of the noisy data. PI controller to eliminate offset, a major weakness of a P-only controller. It is shown in fig.5 as,

Fig.5 STATCOM model with PI – Voltage Regulator block diagram

4.4 Fuzzy Controller

Fuzzy logic controller, approaching the human reasoning that makes use of the tolerance, uncertainty, imprecision and fuzziness in the decision-making process, manages to offer a very satisfactory performance, without the need of a detailed mathematical model of the system, just by incorporating the expert’s knowledge into fuzzy rules. In addition, it has inherent abilities to deal with imprecise or noisy data; thus, it is able to extend its control capability even to those operating conditions where linear control techniques fail (i.e., large parameter variations). A fuzzy controller converts a linguistic control strategy into an automatic control strategy, and fuzzy rules are constructed by expert experience or knowledge database. Firstly, input voltage Vdc and the input reference voltage Vdc-ref have been placed of the angular velocity to be the input variables of the fuzzy logic controller. Then the output variable of the fuzzy logic controller is presented by the control Current Imax. To convert these numerical variables into linguistic variables, the following seven fuzzy levels or sets are chosen as: NB (negative big), NM (negative medium), NS (negative small), ZE (zero), PS (positive small), PM (positive medium), and PB (positive big) as shown in Figure 6. The fuzzy controller is characterized as follows:

» Seven fuzzy sets for each input and output;

» Fuzzification using continuous universe of discourse;

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» Implication using Mamdani's min operator;

» De-fuzzification using the “centroid” method.

Fuzzification: The process of converting a numerical variable (real number) in to a linguistic variable (fuzzy number) is called fuzzification.

Fig.6 Fuzzy control block diagram

Fig. 7 STATCOM model with FLC- Voltage Regulator block diagram

Fuzzy logic controller manages to offer a very satisfactory performance, without the need of a detailed mathematical model of the system, just by incorporating the expert’s knowledge into fuzzy rules. In addition, it has inherent abilities to deal with imprecise or noisy data thus, it is able to extend its control capability even to those operating conditions where linear control techniques fail. FLC voltage regulator is fed by one input that is voltage error (V) and another one is change in error (ΔE). The rules for the proposed FLC voltage controller are given in table I.

Table I Control Rules

ΔI/ΔV NB NM NS ZE PS PM PB

NB NB NB NB NB NM NB ZE

NM NB NB NM NM NS ZE PS

NS NB NM NS NS ZE PS PM

ZE NM NM NS ZE PS PM PB

PS NM NS ZE PS PS PM PB

PM NS ZE PS PM PM PB PB

PM ZE PS PM PB PB PB PB

Fig.8 Membership function for ΔI

Rakesh et al., urnal of Multidisciplinary Research Hub SK International JoVolume 2, Issue 8, August 2015 pg. 28-47

Fig.9. Membership function for ΔV

De-fuzzification: It is the Process of converting fuzzifiedoutput into a crisp value. In the defuzzification operation alogical sum of the results from each of the rules performed.This logical sum is the fuzzy representation of the change in firing angle (output). A crisp value for the change in firing angle is calculated. Correspondingly the grid current changes and improves the power quality.

V. SYSTEM PERFORMANCE

5.1Voltage Source Inverter Operation

The three phase injected current into the grid from STATCOM will cancel out the distortion caused by the nonlinear load and wind generator. The IGBT based three-phase inverter is connected to grid through the transformer. The generation of switching signals from reference current is simulated within hysteresis band of 0.08. The choice of narrow hysteresis band switching in the system improves the current quality.

The control system scheme for generating the switching signals to the STATCOM is shown in Fig. The control algorithm needs the measurements of several variables such as three-phase source current iSabc , source voltage VSabc and inverter current.

The current control block, receives an input of reference i*Sabc current and actual current iSabc are subtracted so as to activate the operation of STATCOM in current control mode.

The proposed control scheme is simulated using MATLAB/SIMULINK in power system block set. The simulation parameters used for the system is given TABLE II.

Table II System Parameters

Sr. No. Parameter Rating

1 Grid voltage 3phase ,415 volt 50Hz

2 Induction Motor/Generator

3.35 KVA , 415 volt 50 Hz speed 1440 rpm P=4, Rs=0.01Ω, Rr=0.015 Ω, Ls=0.06H,Lr=0.06H.

3 Line Series inductance 0.05 mH

4 Inverter parameter DC link voltage =800V,

Switching frequency =2KHz, DC Link Capacitance= 100 µf.

5 Load Parameter Non Linear Load 25kW

6 IGBT Rating Collector Voltage= 1200 V, Forward

Current=50A, Gate Voltage=20V, Power Dissipation= 310W.

5.2.STATCOM- Performance under Various Load variations

The wind energy generating system is connected with grid having the nonlinear load. The performance of the system is measured by switching the STATCOM at time t= 0.3 s in the system. When STATCOM controller is made ON, without change

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             37 | P a g e   in any other load condition parameters, it starts to mitigate for reactive demand as well as harmonic current. This additional demand is fulfil by STATCOM compensator. Thus, STATCOM can regulate the available real power from source. The results of source current are shown in Fig. and respectively. While the result of injected current from STATCOM are shown in Fig.10.

5.3.POWER QUALITY IMPROVEMENT

It is observed that the source current on the grid is affected due to the effects of nonlinear load and wind generator, thus purity of waveform may be lost on both sides in the system. The source current with and without STATCOM operation is shown in Fig. and . This shows that the unity power factor is maintained for the source power when the STATCOM is in operation. The current waveform before and after the STATCOM operation is analysed. The Fourier analysis is expressed and the THD of this source voltage at PCC with and without STATCOM is 7.72% and 11.52% respectively , as shown in Fig.13(a) and 13(b) respectively

5.4 MATLAB Simulink Model:

Fig.9. Simulink diagram of the Wind Energy Generating system Fig.10. STATCOM Simulink Model

Fig.11 Control scheme Simulink model Using PI Controller Fig.12 STATCOM Control Scheme Using FUZZY Logic Controller.

VI. SIMULATION WAVEFORM

The current waveform before and after the STATCOM operation is analyzes. Without using fuzzy controller for STATCOM the source THD is 1.23% and using fuzzy controller the source current (grid current) THD is reduced to 0.81% as shown in Table. It indicates that when we are using fuzzy controller the harmonics are reduced more as compared to PI controller.

A) SIMULATION WAVEFORM USING PI CONTROLLER

All the below figure shows the Current at PCC, Source Current, Wind generating Current, load current and Inverter injected Current with conventional PI controller. Here compensator is tuned on at 0.3 seconds, before we get some harmonics coming from non-linear load, then distorts our parameter and get sinusoidal when compensator is in ON.

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

Fig.13 Current at PCC with and without STATCOM using PI controller Fig.14 Source Current with and without STATCOM using PI Controller

Fig.15 Current after connecting wind system with and without STATCOM

using PI controller Fig.16 Load current with and without STATCOM using PI controller

Fig.17 Injected inverter current with and without STATCOM using PI

controller Fig. 18 Voltage at PCC with and without STATCOM using PI controller

Fig.19 Source Voltage with and without STATCOM using PI Controller Fig.20 Voltage after connecting wind system with and without STATCOM using PI controller

Fig.21 Load voltage with and without STATCOM using PI

controller Fig.22 Real and Reactive Power at Source Side before and after STATCOM using PI Controller

Fig.23 Real and Reactive Power at Load Side before and after STATCOM using PI Controller

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             39 | P a g e   B) SIMULATION WAVEFORM USING FUZZY LOGIC CONTROLLER

All the below figure shows the Current at PCC, Source Current, Wind generating Current, load current and Inverter injected Current with Fuzzy Logic controller. Here compensator is tuned on at 0.3 seconds, before we get some harmonics coming from non-linear load, then distorts our parameter and get sinusoidal when compensator is in ON. It is compared with PI controller and shows better results.

Fig. 24 Current at PCC with and without STATCOM using Fuzzy logic Controller

Fig.25 Source Current with and without STATCOM using Fuzzy logic Controller

Fig.26 Current after connecting wind system with and without STATCOM

using Fuzzy logic Controller Fig.27 Load current with and without STATCOM using Fuzzy logic Controller

Fig.28 Injected Inverter Current with and without STATCOM using Fuzzy logic Controller

Fig.29 Voltage at PCC with and without STATCOM using Fuzzy logic controller

Fig.30 Source Voltage with and without STATCOM using Fuzzy Logic

Controller Fig.31 Voltage after connecting wind system with and without STATCOM using Fuzzy logic controller

Fig.32 Load Voltage with and without STATCOM using Fuzzy logic controller

Fig.33 Real and Reactive Power at Source Side before and after STATCOM using Fuzzy Logic Controller

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

Fig.34 Real and Reactive Power at Load Side before and after STATCOM using Fuzzy Logic Controller

C) COMPARATIVE ANALYSIS OF TWO CONTROL SCHEME FOR STATCOM

Result of two control schemes are summarized in the table below. From this table we can conclude that the % THD reduces more with Fuzzy logic controller.

Without load variations, by using PI controller the THD in the source current reduced to 1.19% and using Fuzzy logic controller the THD is reduced to 0.81%.

a) THD ANALYSIS OF SYSTEM USING PI CONTROLLER.

Fig.35 Current at PCC without STATCOM using PI controller Fig. 35 shows FFT analysis of Current at PCC for balanced Non-linear

load without any compensation, here we get 6.59%

Fig.36 Current at PCC with STATCOM using PI controller Fig.36 shows FFT analysis of Current at PCC for balanced Non-linear

load, here we get 1.66%.

Fig.37 Source current without STATCOM using PI controller Fig.37 shows FFT analysis of Source Current for balanced Non-linear load

without any compensation, here we get 2.30%.

Fig.38 Source current with STATCOM using PI controller Fig.38 shows FFT analysis of Source Current for balanced Non-linear

load, here we get 1.19%.

Fig.39 Voltage at PCC without STATCOM using PI controller Fig.39 shows FFT analysis of Voltage at PCC for balanced Non-linear load

without any compensation, here we get 16.64%.

Fig.40 Voltage at PCC with STATCOM using PI controller Fig.40 shows FFT analysis of Voltage at PCC for balanced Non-linear load,

here we get 4.09%.

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Fig.41 Source voltage without STATCOM using PI controller Fig.41 shows FFT analysis of Source Voltage for balanced Non-linear lad

without any compensation, here we get 16.64%.

Fig.42 Source voltage with STATCOM using PI controller Fig.42 shows FFT analysis of Source Voltage for balanced Non-linear load,

here we get 4.09%.

Table.III % THD content in Current at PCC, Source Current, Voltage at PCC, Source voltage Total Harmonic Distortion % THD

Without STATCOM With STATCOM

Current at PCC 6.59% 1.66%

Source Current 2.30% 1.19%

Voltage at PCC 16.64% 4.09%

Source Voltage 16.64% 4.09%

Table.III shows % THD content in Current at PCC, Source Current, and Voltage at PCC, Source voltage without STATCOM and with STATCOM. It is observed from the Table shows that current at PCC is improved from 6.59%to 1.66%, source current THD in phases are improved from 2.30%to 1.19%.Similarlly for the voltage at PCC THD improved from 16.64% to 4.09% and for the source voltage THD improved from 16.64% to 4.09%.

b) BAR CHART USING PI CONTROLLER

Table. IV Frequency Vs % THD for Current at PCC Using PI Controller

Frequency Before

STATCOM After

STATCOM 250 4.45 1.45 350 1.88 0.54 550 0.98 0.26 650 0.23 0.16

Fig.43 Bar Chart of Current at PCC before and After STATCOM Using PI Controller

In fig.43 Bar chart shows Current at PCC at different frequencies showing that with STATCOM and without STATCOM how % THD is minimize Using PI Controller.

0 1 2 3

250 350 550 650

Magnitude %

Frequency in Hz

4 5

of Fundamental

Before STATCOM After STATCOM

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

Table.V Frequency Vs % THD for Source Current Using PI Controller Frequency Before

STATCOM After

STATCOM 250 2.04 1.06 350 0.95 0.37 550 0.21 0.09 650 0.14 0.08

Fig.44 Bar chart of Source Current Before and After STATCOM Using PI Controller

In fig.44 Bar chart shows Source Current at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using PI Controller.

Table. VI Frequency Vs % THD for Voltage at PCC Using PI Controller Frequency

Before STATCOM

After STATCOM 250 13.27 3.68 350 7.03 1.55 550 1.54 0.6 650 0.62 0.42 850 0.62 0.25 950 0.33 0.19

Fig.45 Bar Chart of Voltage at PCC before and After STATCOM Using PI Controller

In fig.45 Bar chart shows Voltage at PCC at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using PI Controller.

0 0.5 1 1.5 2 2.5

250 350 550 650

Magnitude % of Fundamenatal

Frequency in Hz

Before STATCOM

After STATCOM

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             43 | P a g e   Table.VII Frequency Vs % THD for Source Voltage Using PI Controller

Frequency Before

STATCOM After STATCOM 250 13.27 3.68 350 7.03 1.55 550 1.54 0.6 650 0.62 0.42 850 0.62 0.25 950 0.33 0.19

Fig.46 Bar chart of Source Voltage Before and After STATCOM Using PI Controller

In fig.46 Bar chart shows Source Voltage at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using PI Controller.

a) THD ANALYSIS OF SYSTEM USING FUZZY LOGIC CONTROLLER.

Fig.47 Current at PCC without STATCOM using Fuzzy logic Controller.

Fig.47 shows FFT analysis of Current at PCC for balanced Non-linear load without any compensation, here we get 5.79%.

Fig.48 Current at PCC with STATCOM using Fuzzy logic controller.

Fig.48 shows FFT analysis of Current at PCC for balanced Non-linear load, here we get 1.45%.

Fig.49 Source Current without STATCOM using Fuzzy Logic controller.

Fig.49 shows FFT analysis of Source Current for balanced Non-linear load without any compensation, here we get 1.23%.

Fig.50 Source Current with STATCOM using Fuzzy Logic controller.

Fig.50 shows FFT analysis of Source Current for balanced Non-linear load, here we get 0.81%.

0 2 4 6 8 10 12 14

250350550650850950

Magniyude % of Fundamental

Frequency in Hz Before  STATCOM After  STATCOM

Rakesh et al., SK International Journal of Multidisciplinary Research Hub Volume 2, Issue 8, August 2015 pg. 28-47

Fig.51 Voltage at PCC without STATCOM using Fuzzy Logic Controller.

Fig.51 shows FFT analysis of Voltage at PCC for balanced Non-linear load without any compensation, here we get 15.74%.

Fig.52 Voltage at PCC with STATCOM using Fuzzy Logic Controller Fig.52 shows FFT analysis of Voltage at PCC for balanced Non-linear load,

here we get 3.92%%.

Fig.53 Source Voltage without STATCOM Using Fuzzy Logic Controller Fig.53 shows FFT analysis of Source Voltage for balanced Non-linear load

without any compensation, here we get 15.74%.

Fig.54 Source Voltage with STATCOM Using Fuzzy Logic Controller Fig.54 shows FFT analysis of Source Voltage for balanced Non-linear load

without any compensation, here we get 3.92%.

Table.VIII % THD content in Current at PCC, Source Current, Voltage at PCC, Source voltage Total Harmonic Distortion % THD

Without STATCOM

With STATCOM Current at

PCC 5.79% 1.45%

Source Current 1.23% 0.81%

Voltage at

PCC 15.74% 3.92%

Source

Voltage 15.74% 3.92%

TableVIII shows % THD content in Current at PCC, Source Current, Voltage at PCC, Source voltage without STATCOM, with STATCOM. It is observed from the Table shows that current at PCC is improved from 5.79% to 1.45%, source current THD in phases are improved from 1.23% to 0.81%.Similarlly for the voltage at PCC THD improved from 15.74% to 3.92% and for the source voltage THD improved from 15.74% to 3.92%.

d) BAR CHART USING FUZZY LOGIC CONTROLLER

Table.IX Frequency Vs % THD for Current at PCC Using Fuzzy Logic Controller Frequency

Before STATCOM

After STATCOM 250 4.98 1.32 350 2.78 0.54 550 0.58 0.2 650 0.44 0.14

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             45 | P a g e   0

1 2 3 4 5 6

250 350 550 650

Magnitude % of Fundamental

Frequency in Hz Before  STATCOM After STATCOM

Fig.55 Bar Chart of Current at PCC before and After STATCOM Using Fuzzy Logic Controller

In fig.55 Bar chart shows Current at PCC at different frequencies showing that with STATCOM and without STATCOM how % THD is minimize Using Fuzzy Logic Controller.

Table.X Frequency Vs % THD for Source Current Using Fuzzy Logic Controller Frequency Before STATCOM After STATCOM

250 1.11 0.02 350 0.48 0.02 550 0.08 0.01 650 0.04 0.01

0 0.2 0.4 0.6 0.8 1 1.2

250 350 550 650

Magnitude % of Fundamental

Frequency in Hz

Fig.56 Bar Chart of Source Current before and After STATCOM Using Fuzzy Logic Controller

In fig.56 Bar chart shows Source Current at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using Fuzzy Logic Controller.

Table.XI Frequency Vs % THD for Voltage at PCC Using PI Controller Frequency Before STATCOM After STATCOM

250 13.25 0.06

350 7.94 0.06

550 1.76 0.01

650 1.36 0.02

850 1.29 0.01

950 1.23 0.01

1150 0.51 0.01

Rakesh et al., l Journal of Multidisciplinary Research Hub SK Internationa Volume 2, Issue 8, August 2015 pg. 28-47

Fig.57 Bar Chart of Voltage at PCC before and After STATCOM Using Fuzzy Logic Controller

In fig.57 Bar chart shows Voltage at PCC at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using Fuzzy Logic Controller.

Table.XII Frequency Vs % THD for Source Voltage Using Fuzzy Logic Controller Frequency Before

STATCOM After

STATCOM 250 13.25 3.5 350 7.94 1.55 550 1.76 0.6 650 1.36 0.43 850 1.29 0.24 950 1.23 0.2

0 2 46 108 1214

250 350 550 650 850 950

Magnitude % of Fundamental

frequency in Hz Before  STATCOM After  STATCOM

Fig.58 Bar Chart of Source Voltage before and After STATCOM Using Fuzzy Logic Controller

In fig.58 Bar chart shows Source Voltage at different frequencies showing that with STATCOM and without STATCOM how % THD is minimized Using Fuzzy Logic Controller.

VII. C^ONCLUSION

The operation of the STATCOM is simulated using two controllers: Bang-Bang current controller and Fuzzy controller.

STATCOM injects current to the grid and it cancel out the reactive and harmonic parts of the induction generator current and load current. When we are reducing the wind generating system output, it will not affect the source current magnitude. The hysteresis current controller is used to generate switching signal for inverter in such a way that it will cancel the harmonic current in the system.

In this project fuzzy logic controller based STATCOM is presented for grid connected wind energy generating system. The proposed FLC based STATCOM have improved the power quality of source current significantly by reducing the THD from

 © 2015, SK Publisher All Rights Reserved      ISSN: 2394‐3122 (Online)             47 | P a g e   5.79% to 1.45%.It is clearly presented that STATCOM with FLC gives better performance than STATCOM with conventional PI controller. For better voltage regulation Fuzzy-PI control technique showed better performance than the conventional controller. One of the major advantages of the proposed FLC is being less sensitive to the system parameter variation; in addition, it is characterized by a negligible response time. Simulation result analysis has shown that the proposed controller has fast dynamic response, high accuracy of tracking the DC-voltage reference, and strong robustness to load sudden variations compared to the conventional PI controller.

Table.III shows % THD content in Current at PCC, Source Current, and Voltage at PCC, Source voltage without STATCOM and with STATCOM Using PI controller. It is observed from the Table III shows that current at PCC is improved from 6.59%to 1.66%, source current THD in phases are improved from 2.30%to 1.19%.Similarlly for the voltage at PCC THD improved from 16.64% to 4.09% and for the source voltage THD improved from 16.64% to 4.09%.

Table VIII shows % THD content in Current at PCC, Source Current, Voltage at PCC, Source voltage without STATCOM, with STATCOM Using fuzzy logic Controller. It is observed from the Table VIII shows that current at PCC is improved from 5.79% to 1.45%, source current THD in phases are improved from 1.23% to 0.81%.Similarlly for the voltage at PCC THD improved from 15.74% to 3.92% and for the source voltage THD improved from 15.74% to 3.92%.From the obtained result it is clear that STATCOM with Fuzzy Logic Controller gives improved results as compared to PI Controller. Thus it shows Power quality Improvement using Fuzzy Logic Controller.

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