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Efficiency of VSC-HVDC System With

Various Fuzzy Models.

Mrs. Sonali R dasguptaElectrical Engineering Department

J.D.C.O.E.

Nagpur, India.

Dr.(Mrs.) Gayatri Agnihotri

Department of Electrical engineering

MANIT Bhopal

Bhopal (M.P.), India

Abstract - This paper suggests a Shrinking Span Membership function to be utilized in very fact changing system just like

VSC- HVDC system. In this particular work Mamdani controller as well as the Takagi-Sugeno controller are compared with

exact same input function(Shrinking Span Membership) in simulation as well as on prototype hardware. Simulation result

justify the.Takagi-Sugeno Controller gives better dynamic response then the Mamdani controller

Keywords- Fuzzy Controller, Pulse width modulation,HVDC transmission.

1. INTRODUCTIONPower electronics technology development along with the relatively high switching frequency of Pulse Width

Modulation, HVDC transmission system based upon VSC HVDC is applied in a number of special occasions

like connection of off-shore wind farms or oil drilling platforms to the mainland electrical network as well as for

underground transmission or distribution system within crowded cities.

VSC HVDC system has a number of benefit in comparison with the traditional thyristor based HVDC, for

example

- Capability to connect with weak AC system and even inactive systems,- Fast response resulting from enhanced

switching frequency (SPWM)- Minimum natural environment impact- No requirement of reactive power by converter- No add-on to Short circuit ratio

On the other hand, VSC HVDC transmission comes with quite a few drawbacks, such as probably large

electrical power loss along with substantial investment cost compared with traditional HVDC, however the

technological innovation is constantly grow. VSC has got the capability to rapidly management both active and

reactive power independently of one another, to maintain the voltage and frequency steady. This provides

overall flexibility with regards to the location of the converters in the AC system. The VSC layout draws on a

modular strategy. For any highest DC voltages the equipment is set up in architectural structures. The desired

sizes of the site areas for that Converter stations are usually compact. All equipment apart from the power

transformer are indoors. Well-proven and tested equipment along at the factory make installation and

commissioning speedy and efficient.

Control method and control strategy have notable effect on the characteristics of the VSC-HVDC system. Agood control method depends upon an accurate mathematic model. The VSC-HVDC operating characteristics

can be controlled through a closed loop consists of control units and the control system (PI controller)[1]. At

present there is no direct analytic expression model presented of VSC-HVDC system. There are actually very

few papers about quantitative optimization method of PI parameters. Conventional method utilized, to set PI

parameters are as follows, Smith, Z-N and pole assignment method etc [2]. However for all these method

transfer function is necessary, VSC-HVDC system is a double-input and double-output nonlinear coupling

object and its particular transfer function is hard to describe, so it is difficult to make use of such conventional

setting methods to optimize PI parameters of VSC-HVDC control system. In order to meet the dynamic overall

performance requirement of the VSC-HVDC system, the paper [3] use estimation method to set k and Tn based

on PSCAD/EMTDC software, but the estimation method doesn't have theoretical foundation and there is no

index chart to evaluate the control system performance while using estimated parameters. In recent years most

of the papers have proposed methods for developing VSC controllers applying linear control techniques, in

which the system equations are line razed in a specific operating point and based on the linearization model, PIor PD controllers are tuned at that point in order to provide the best possible performance[7[-[8].

Sonali R dasgupta et al. / International Journal of Engineering Science and Technology (IJEST)

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The drawback of such PI/PD controllers is that their parameters are mostly tuned based on a learning from their

errors; additionally their performance degrades as the system working condition change. Nonlinear adaptive

controller on the other hand can provide good control capability over a wide range of operating condition;

however they have a more sophisticated structure and more challenging implementation as compared to linear

controllers.

This paper designs a conventional and two modified Mamdani controller and Takagi-Sugeno controller for VSC

HVDC system with shrinking span membership function. Simulation results are provided in order to theperformance of both the conventional (PI) and the modified controllers. The simulation results ensure that thecontrol strategy has fast response, strong stability and reduction of losses.

This paper is organized as follow. In Section II, VSC HVDC system is described, in Section III the two types of

fuzzy controller are described with their comparison, in Section IV represents the simulation results,

Conclusions are given in Section V.

II. VSC HVDC SYSTEM DESCRIPTIONBasic principles of VSC HVDC transmission operations could be demonstrate by taking into consideration each

terminal as being a voltage source coupled to the AC transmission network via a three phase reactor. Each

terminals are interconnected with a DC link, as shown in fig 1.While in the document Station 1 is chosen to

manage reactive power Q 1 and DC-bus voltage Udc, which is used as being a rectifier station, and Station 2 is

scheduled to manage reactive power Q 2 and active power P2, which is used being an inverter station

.VSCHVDC converter is added in with pre and post filters. The purpose of pre filter is always to normalizingthe input signals in accordance with the respective domain, and the purpose of post filter is always to maintain

the output within the limit value by saturation limiter, this block is just not shown within the schematic diagram

however it is consider as internal block of converter.

Fig 1 Schematic diagram of VSC HVDC system

Fig 2 shows a simplified single line diagram with the converter attached to AC system. The converter is

modeled as being a controlled voltage source uv on the AC side along with a controlled current source idc on the

DC side.

The controlled voltage source could be explained the subsequent equation

)1()sin(2

1++= rmsharmonictetMuu DCv

Where M is a modulation index which can be understood as be the ratio of the peak value of the modulating waveand the peak value of the carrier wave. The variables M, and d could be adjusted through the VSC controller. Theactive power flow between the AC system and the converter could be managed by altering the phase angle ()between the fundamental frequency voltage (uv) generated by VSC and AC voltage (uf) on the secondary side ofthe transformer by

V

Vf

dcdcfX

uuIUP

sin== ------- (2)

V

Vff

fX

uuu

Q)cos(

= --------- (3)


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Fig 2. single line diagram of the converter connected to AC system

The active and reactive power are going to be take into account as positive in case the power flow through the

AC network towards the converter. The phase displacement angle will likely then be positive when the

converter output voltage lags behind the AC voltage in phase.

Equation (2) gives the fact that active power is proportional to the DC current as well as the DC voltage.

Additionally it can be primarily determined by the phase displacement angle d. A positive phase shift results in

the fact that active power flows from the AC network to the converter. However the reactive power is mainly

determined by the difference between the magnitudes of the AC bus voltage and the converter output voltage in

accordance with the equation (3). The reactive power is fed through the voltage with greater magnitude towards

voltage with the lower magnitude. Theses characteristic enable the independent management of the reactive and

active power which is a significant benefit for the VSCHVDC. P-Q diagram is actually a circle in accordance

with equation (4) with the center situated at origin the way it does for the line commutated converters as per fig.4.

22

2 .

=

+

L

VL

L

L

X

UU

X

UQP ------ (4)

The magnitude of AC output is controlled using the SPWM deviation, active power (P) is dependent primarily

on the angle, or the phase shift and reactive power (Q) is dependent on the modulation index. Any active and

reactive power inside the circle is achievable.

The VSC HVDC interconnected together with the AC grid is really a nonlinear coupled double-input double

output control object, in which the power flow between the DC and AC side can be managed by handling both,the phase as well as the amplitude of the ac voltage wave generated through the converter. Therefore, the

development of a mathematical analysis to obtain a model along with a subsequent design of independents

controllers for the active and reactive power flow is just not a simple task [10].

Fuzzy controllers has demonstrated to have great adaptability in presence of high non-linearity as this systemrequires. In VSC-HVDC system modulation index m and phase shift are output of the controller which can

be control by controlling the error in active and reactive power and the rate of change of these errors.

III. FUZZY CONTROLLERS

Fuzzy logic systems offer a nonlinear mapping from the set of crisp input to the set of crisp outputs, utilizingboth intuition and mathematics. Using different fuzzifiers for example Singleton, Gaussian and Triangular

fuzzifiers, any set of crisp input is mapped into a fuzzy set. Numerous rules in rule base are placed on the fuzzy

input to be able to produce a fuzzy output. This output subsequently defuzzified to create a crisp output value.Actually, Defuzzification is a ultimate step in approximate reasoning also it comprises in the replacing of a


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fuzzy set having a suitable non-negative real number. Their are wide and varied ways of Defuzzification for

instance

- Center of Area- Maximum Center of Gravity- Centroid- Fuzzy Mean- First of Maximum- Last of Maximum- Middle of Maximum- Quality Method- Semi-linear Defuzzification- Weighted Fuzzy MeanMaximum Center of Gravity and Middle of Maximum are preferred defuzzifiers put on to fuzzy logic

techniques.

Triangular fuzzifiers as well as the centroid defuzzifier are being used in this particular paper as the mapping

techniques.

Two distinct fuzzy logic techniques for developing controllers are Mamdani method as well as the Takagi-

Sugeno technique both of them are possessing these benefit

a) Mamdani Method- Is user-friendly

- Has wide-spread acknowledgement

- Is well suited to human input

b) Takagi-Sugeno Method- Is computationally efficient

- Works effectively linear, adaptive and

optimization techniques

- Has guaranteed a continual of the

output surface

- Suitable for mathematical evaluation.

Takagi-Sugeno is much better with regard to dynamic system which in turn changes very quickly in comparison

to Mamdani technique.

A Conventional Takagi-Sugeno Controller

Fuzzy variables are P, Q, ep, eq and fuzzy set with linguistic characteristics are negative very big,

negative big, negative large, negative small zero, positive small, positive large, positive big, positive very big

are allotted to each variable and equal - span triangular function have been chosen as being the fuzzy

membership function as shown in fig 4.

For Mamdani and Takagi-Sugeno input to controller is identical to explained above, however the subintervals

are heuristically selected depending on the best damping performance. A same kind of fuzzy rule base is been

assigned for every combination of input/output variable to each forms of controller like:

Rule1: IF (P is NVB) AND (ep is LNC)

THEN (M is BI)

Rule2: IF (Q is NVB) AND (eq is LNC)

THEN ( is BI)

Fig 4(a) Shrinking Span Membership function


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Fig 4(b) Equal Span Triangular functions Membership function

In which the fi is standard functions whose coefficients are chosen in a manner that provides best performance.

Since the membership functions are symmetrically. The weighted sum of a characteristic value by centroid

defuzzifier will be as

y =

=

=

9

1

9

1

)(

ii

i

ii

w

Pfw

---- (5)

Where the iw are the membership values of each rule for a certain value of the input signal P.

The identical rule base is employed for another controller to manage Q.

B Shrinking Span Membership function

Fuzzy logic controller is really a combination of four segment 1) Fuzzification, 2) Rule bas3) Inference and 4)

Defuzzification, each of which play an important role in the performance of the controller. Choosing the

appropriate fuzzy membership function. Subintervals as well as the Defuzzification method are a few of them.

Most researchers often design the input/output fuzzy membership function with all the equal span triangular

functions. However, these types of function do not really provide optimum solution for everyone problems. In

equal span triangular functions the controller produces exactly the same output with constant speed regardless to

the severity of disturbance, but in shrinking span membership function controller produced significant and quickcontrol action when the system output is far from the set point and makes mild and gradual change when it is

near to the set point. This can be concluded by the simulation result. The main points of designing a shrinking

span fuzzy controller in a multiple input with multiple output is rigorously explained in [7].

Different triangular function for any input variable could be expressed as

Fi = ( x; x i-1,x i, x i+1) ----- (6)

For i = - m to m

Where m is a index for any input set, producing 2m+1 linguistic terms for the input variable x. In this particular

paper m is consider to be 9 therefore 19 shrinking span membership function are allotted to the input variable.

The x i can be understood to be

x i =im

sm

i ------- (7)

Where [ ]1,0s is the shrinking factor for the input variable x. By applying different shrinking spans to aninput variable, different results are achieved. A typical shrinking span of 0.5 is selected for this proto type

model.

Using a similar approach, membership function can be defined for the output variable.

VI SIMULATIOM

In order to illustrate and compare the fuzzy methods proposed, a simulation model is developed using Simulink

and the FIS toolbox of MatLab, for Mamdani controller as well as for Takagi-Sugeno controller.

The SMPS fly back with PIC 18F 4431 was used to design the fuzzy logic controller. It support all deign step

for fuzzy system engineering structure design, linguistic variables and rule definition. This tool generates C-


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code for Intel MCS-96 microcontrollers. It also produces M code which is used in MatLab. Mamdani controller

as well as for Takagi-Sugeno controller. formulas are first created in C-code and then tested in MatLab.The system parameters are selected as per the actual existing HVDC (conventional/classic) bipolar line betweenCHANDRAPUR and PADGHE.

4.1 Primary RatingThe Chandrapur-Padghe HVDC bipolar is rated for 1500MW continuous power flow; a two-hour overload

rating of 1650MW .The minimum power flow is scheduled at 75MW in monopolar functioning. The link isoperated at the direct voltage of 500kV. On the AC side the link is connected to the 400kV system in both

Chandrapur and Padghe. The AC voltage is permitted to very in between 380kV to 430kV in Chandrapur and in

between 360kV to 420kV in Padghe. The frequency can differ in between 47.5Hz and 51.5Hz.There are four AC filter banks at both station. Each bank is with a rating of 200MVAR. There are two DC filter

branches per pole and per station as shown in fig 5.

Simple VSC- HVDC 6-pulse transmission system1500 MW (400kV) Chandrapur-Padghe

Station 1Station 2

RectifierInverter

+-

v

vdL

+i-

id

A

B

C

Three-Phase

V-I Measurement

A BC

AC filters

(800 Mvar)

A

B

C

pulses

+

-

RECTIFIER

LsRLsI

Iabc

Vabc

Id

VdL

Fuzzy Logic

Controller

with Ruleviewer

a

k m

Diode

1 1

DC line 300 km

400kV

A

B

C

A

B

C

A

B

C

A

B

C

a

b

c

1200MVA

400/500 kV

Fig 5. VSC HVDC System

4.2 Step Response

In order to test the dynamic responses of the VSC HVDC system, four test cases have been studied.

Case 1 : The simulation includes power reversion from

-0.5 pu to +0.5 pu of station 1 at t = 1.3s, then active power step change from 0.5pu to 1.o pu at t = 2.5s,

Case 2: At t= 2.0s, the reactive power step change from 0pu to -0.3pu of station 1, then set to +0.3pu at t = 2.7s

The system hardware prototype implementation designed provides as 103.2 W and 120 VAR fig 6 present just

one of the two converter implemented due to the stations are identical. This prototype system gives fast and real

time response.


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Fig 6 One converter of proto type VSC HVDC System

Fig 7 presents the two methods tested on the hardware system built with the same input functions in all cases

the proposed control Shrinking Span Membership function with Takagi-Sugeno Controller gives improvement

and very fast response,.

Fig 7. Dynamic response of the system under two fuzzy controllers.


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