Research Article MATLAB Simulation of UPQC for Power

Research ArticleMATLAB Simulation of UPQC for Power Quality MitigationUsing an Ant Colony Based Fuzzy Control Technique

N Kumarasabapathy1 and P S Manoharan2

1University VOC College of Engineering Thoothukudi 628008 India2Thiagarajar College of Engineering Madurai 625015 India

Correspondence should be addressed to N Kumarasabapathy nkspathygmailcom

Received 10 June 2015 Accepted 7 July 2015

Academic Editor Gnana Sheela

Copyright copy 2015 N Kumarasabapathy and P S Manoharan This is an open access article distributed under the CreativeCommons Attribution License which permits unrestricted use distribution and reproduction in any medium provided theoriginal work is properly cited

This paper proposes a fuzzy logic based new control scheme for theUnified PowerQuality Conditioner (UPQC) forminimizing thevoltage sag and total harmonic distortion in the distribution system consequently to improve the power quality UPQC is a recentpower electronic module which guarantees better power quality mitigation as it has both series-active and shunt-active powerfilters (APFs) The fuzzy logic controller has recently attracted a great deal of attention and possesses conceptually the quality ofthe simplicity by tackling complex systems with vagueness and ambiguity In this research the fuzzy logic controller is utilized forthe generation of reference signal controlling the UPQC To enable this a systematic approach for creating the fuzzy membershipfunctions is carried out by using an ant colony optimization technique for optimal fuzzy logic control An exhaustive simulationstudy using the MATLABSimulink is carried out to investigate and demonstrate the performance of the proposed fuzzy logiccontroller and the simulation results are compared with the PI controller in terms of its performance in improving the powerquality by minimizing the voltage sag and total harmonic distortion

1 Introduction

Power quality is one of the major concerns in the present eraIt has become important especially with the introduction ofsophisticated devices whose performance is very sensitiveto the quality of power supplied Power quality problem isan occurrence manifested as a nonstandard voltage currentor frequency that results in a failure of end use equipment[1] The main objective of devising UPQC is the com-bined use of series-active and shunt-active filters chieflyto compensate negative-sequence current and harmonicsas the SCR controlled capacitor banks compensate reactivepower in power frequency [2] Modeling and simulation ofcustom power conditioners happen to be inevitable as powerelectronics-based equipment in use for augmenting powerquality in distribution networks [3] Extended merit of theUPQC includes the following it has a similar feature to SCRcontrolled capacitor banks of achieving load compensationresulting in drawing the balanced sinusoidal currents in

the current control mode [4 5] In addition it is also themost comprehensive power quality enhancing device forsusceptible nonlinear loads which need exact sinusoidalinput supply [6]

UPQC can also be operated in different possible configu-rations for single-phase (2-wire) and 3-phase (3-wire and 4-wire) networks diverse compensation approaches and recentdevelopments are also found in the field [7] Thus this con-ditioner can achieve reasonable power quality improvementreducing the power disturbances that are supplied to thecustomers by the mains using the series unit Additionalfacilities for PQ (ie mains power interruptions) can beoffered to the customers (custompower) from the shunt units[8] To reiterate again the main principle of UPQC is toensure quality supply voltage and load current disturbancesnamely sags swell imbalance harmonics reactive currentsand current unbalance produced by the nonlinear loads [910]

Hindawi Publishing Corporatione Scientific World JournalVolume 2015 Article ID 304165 9 pageshttpdxdoiorg1011552015304165

2 The Scientific World Journal

The control signal given to the UPQC plays a significantrole in establishing a better operation of the device Con-ventional control schemes are widely used in addition to thecontrol schemes derived from artificial intelligence which isalso recorded in the literature Applications of some advancedmathematical tools in general and wavelet transform inparticular in power quality are also applied An extensivecollection of literature covering applications of fuzzy logicexpert systems neural networks and genetic algorithms inpower quality is also growing [11]The ANN-based controlleris designed for the current control of the shunt-active powerfilter and trained offline using data from the conventionalproportional-integral controller [12] Similarly a fully digitalcontroller based on the TMS320F2812 DSP platform which isimplemented for the reference generation as well as controlpurposes is proposed [13]

In another attempt [14] the authors propose the applica-tion of fuzzy logic (FL) technique within microgrid energysystem based on the most modern power conditioningequipment devices such as Unified Power Quality Condi-tioner (UPQC) Similarly [15 16] a linear quadratic regulator(LQR) control technique embedded with the ANN is used tocoordinate the operation of the series and shunt VSIs of theUPQC In another development a control algorithm based onwavelet transform for UPQC to suppress current harmonicsand voltage sags is proposed [17] Subsequently in [18] theauthors emphasize enhancement of power quality by usingUPQC with fuzzy logic controller (FLC) and artificial neuralnetwork (ANN) controller on the conventional proportional-integral (PI) controller In [19] the determination of voltagereferences for series-active power filter is done based on arobust three-phase digital phase locked loop (PLL) systemusing fuzzy regulator

In [20] a particle swarm optimization (PSO) method isused to find the solution of the objective function derivedfor minimizing real power injection of UPQC along withthe constraints Adaptive neurofuzzy inference systems havebeen used to make the proposed methodology online forminimum real power injection with UPQC by using thePSO-based data for different voltage sag conditions A fuzzylogic with PWM technique for UPQC for power qualityimprovement is discussed in [21] In another extension[22] a fuzzy-expert system for automated detection andclassification of power quality disturbances is presented Thepaper [23] focuses on the application of wavelet transformtechnique to extract features from power quality disturbancewaveforms and their classification using a combination ofartificial neural network and fuzzy logic Simulations arecarried out with PI as well as fuzzy logic controller for both119901-119902 and 119868119889-119868119902 control strategies by considering differentvoltage conditions and adequate results were presented in[24] Thus the main focus of this proposed system is toimprove the power quality by compensating the voltage sagand eliminating the harmonics in the distribution networkusing a fuzzy logic [25 26] based technique In this researchthe fuzzy membership functions are carried out by usingan ant colony optimization [27] technique for optimal fuzzylogic control

+

Shunt APF

+

Series APF

DC link capacitor

voltage

Load

Vinj

IseVDC

minus

minus

Lsh Ish

Figure 1 Schematic diagram of the UPQC

The simulation is done using MATLAB and SimulinkToolbox for both control schemes used for the generationof control signals for the UPQC The rest of the paper isorganized in such a way that UPQC is revisited in Section 2Control strategy and necessary equations of the UPQC arediscussed in Section 3 Fuzzy logic and its features used in thisresearch are presented in Section 4 The proposed FL-ACOmethod is discussed in Section 5 Numerical simulationsare shown in Section 6 and the discussions and conclusionsfollow finally

2 Unified Power Quality ConditionerAn Overview

UPQC is one of the custom power devices used at the electri-cal power distribution systems to improve the power qualityof distribution system customers [2] UPQC could be used tocancel current harmonics to compensate reactive power toeliminate voltage harmonics to improve voltage regulationto correct voltage and current imbalances to correct voltagesag or swell and to avoid voltage interruptions [3] UPQCconsists of both shunt and series compensators A shuntcompensator is used to cancel the disturbances in currentwhereas series compensator is used to cancel disturbances involtage Shunt compensator could be connected to the left orright of the series compensator Ideally shunt compensatorinjects current to achieve purely balanced sinusoidal sourcecurrents in phase with the supply voltages at rated magnitudeand frequency On the other hand series compensation isused to inject voltage to maintain terminal voltage at ratedmagnitude and frequency

The schematic diagram of a three-phase UPQC is shownin Figure 1 Voltage source inverters are used for shunt andseries compensation One may note that both voltage sourceinverters are supplied froma commonDC link capacitor Oneof the voltage source inverters is connected in parallel withthe AC system while the other one is connected in series withthe AC system through injection transformers The inverterconnected in parallel together with its control circuit formsthe shunt compensation circuit On the other hand theinverter connected in series with appropriate control circuitforms the series compensation circuit For the successfuloperation of the UPQC the DC capacitor voltage should beat least 150 of the maximum line-line supply voltage To

The Scientific World Journal 3

DC link capacitor

Series APF Shunt APF

Combination ofreference voltages

PWM controller PWM controller

Fuzzy controller

Reference currentgeneration


Load

Vsa

Vsa

Vsb

Vsb

Vsc

Vsc

VsaVsbVsc

Vla

Vla

Vlb

Vlb

Vlc

Vlc

Via

Vib

Vic

Isa

IsaIsa

Isb

IsbIsb

Isc

IscIsc

Isea

I sea

IsebIsec

Iseb

I sec

Isealowast Iseb

lowast Iseclowast

Vialowast

Viblowast Vic

lowast

Isalowast Isb

lowast Isclowast

Isplowast

VDC

VDC

VDClowast

I shb

I sha

Lsh

Figure 2 Control scheme of UPQC

regulate the capacitor voltage constant either a PI controlleror a fuzzy logic controller could be usedThus in this researcha fuzzy logic integrated with ACO is proposed for the controlof UPQC The expression is given by

1198812

inj = 1198812

op1199092+ 21198812op (1minus119909) (1minus cos120573) (1)

where 119881op is the output required voltage and 120573 is the angle ofvoltage Hence

VAminusUPQC = 119881op119868op (1198661 (120579 119909 120573) +1198662 (120579 120573))

+ 1198682

op1198662

2 (120579 120573)119885SLC(2)

This is the final apparent power expression for the UPQC

3 Control Strategy of UPQC

The control scheme of three-phase UPQC is shown inFigure 2 It consists of shunt APF and series APF Both theshunt and series APFs are current controlled The shunt APFis indirect current controlled

31 Fundamental Phasor Configuration The fundamentaldescription of the UPQCwith an ideal voltage source and thefuzzy logic is modeled as an ideal current source The UPQCsource voltage (119881

119878) is taken as the reference and is given by

[28]

119881inang120579 = 119881penang120573+119881phang120575 (3)

where 119881ph is the load voltage and 119881pen is the penetratedvoltage of the UPQC Note that for a power factor given loadand voltage sag requirement to determine the magnitude and

constant phase angles of 119881pen to maintain the load voltageconstant at its rated valued There are an infinite number ofsolutions for119881penThe novel control strategy proposed in thispaper precalculated this angle of injection 120574 to optimize theloading of the UPQCThe load current is given by

119868phang120575minus 120579 = 119868inang120579+ 119868119862ang120575 (4)

The angle 120601 represents the lagging angle of the load current(119868ph) with respect to 119881ph As assumed power supply onlyactive component of the load current 120575 = 0 The current119868119862is preferably the reactive load current component The

operation of the UPQC by means of a phasor diagram is easyto understandThe suffix ldquophrdquo denotes the load terms and ldquoinrdquodenotes the supply terms Suffixes 1 and 2 denote two stagesin time on the other state of the power supply for UPQCtaking action Initially in Stage 1 the supply voltage has nodeficiency

119881in = 119881ph1 = 119881in1 = Constant = 1198810 (5)

Corresponding to that situation the SLCVC current is givenby 1198681198621 where angle 120573 = +90 in advance of the supply voltage

it is assumed that the power factor is laggingIn Stage 2 the supply voltage magnitude has reduced to

119881in2 which requires the UPQC to take action such that 119881ph2is restored to its original magnitude (|119881ph1| = |119881ph2|) Thisis achieved by injecting the series voltage 119881injang120574 and loadvoltage can be obtained by selecting 120574 in a range from 0 to90∘ together with the appropriate magnitude of 119881inj In Stage2 according to Figure 3

119868in2 cos120573 = 119868ph2 cos 120579 (6)

1198681198622 =

119868ph2 sin (120579 minus 120573)cos120573

(7)


+ Fuzzy logiccontroller

Consideredsystem

minus

r e Q

d

dt

120579Σ

e

Figure 3 Fuzzy logic controller for system under consideration

If 120572 lt 120601 the two active filters inject the load reactive powerInterestingly this sagging voltage is such that for a loadpower factor given the angle 120573 becomes equal to 120579 and thenfrom (6) it can be inferred that 119868

1198782 = 1198681198712The load current isunderstood to be constant

1198681198711 = 1198681198712 = 1198680 (8)

with a fundamental lagging power factor of cos120601 The activedemand for power in the load is constant and equal to whatto do with the source

119881119878119868119878= 119881119871119868119871cos120601 = Constant (9)

In the case of sag where |1198811198782| lt |119881

1198781| and 119909 is the per unitvoltage sag

1198811198782 = (1minus119909)1198811198781 = (1minus119909)1198810 (10)

Tomaintain a constant active power in a voltage sag11988111987811198681198781 =

11988111987121198681198712 and

1198681198782 =

1198810119868119871 cos1206011198810 (1 minus 119909)

= 1198680cos120601(1 minus 119909)

(11)

Thus

1198811198712 sin120572 = 119881inj sin 120574 (12)

1198811198712 cos120572 = 1198811198782 +119881inj cos 120574 (13)

or

sin 120574 = 1198811198712119881inj

sin120572

cos 120574 =radic(1198812inj minus 119881

2

1198712sin2120572)

119881inj

(14)

From (7) and (12)

1198812

inj = 1198812

0 1199092+ 211988120 (1minus119909) (1minus cos120572) (15)

The apparent power of the series compensator is expressed by

10038161003816100381610038161003816119881inj

1003816100381610038161003816100381610038161003816100381610038161198681198782

1003816100381610038161003816 = 11988101198680 cos120601radic1199092 + 2 (1 minus 119909) (1 minus cos120572)

(1 minus 119909)(16)

which yields

1198681198622 cos120572 = 1198681198712 +119881inj sin (120601 minus 120572) (17)

Therefore the apparent power rating is modeled by

11986811986221198811198712 + 119868

2

1198622119885SLC

= 1198681198712(1198810

sin (120601 minus 120572)cos120572

+ 1198681198712(

sin (120601 minus 120572)2

cos120572)119885SLC)

(18)

where 119885SLC is impedance of the synchronous link converterin pu summing up (16) and (18) the total apparent powerrating of the UPQC is expressed as


+ 1198682

op1198662

2 (120579 120573)119885SLC

1198661 (120579 119909 120573) = cos 120579radic1199092 + 2 (1 minus 119909) (1 minus cos120573)

(1 minus 119909)

1198662 (120579 120573) =sin (120601 minus 120573)

cos120573

(19)

Therefore for a given load power factor angle 120601 and voltagesag 119909 pu the VA loading will be a function of the advanceangle 120572 of 119881

119871 The minimum VA occur when 120601 = 120572 so that

1198681198782 = 119868

1198712 and 1198681198622 = 0 Under these conditions the optimalinjected voltage is given by

119881inj = 1198810radic1199092 + 2 (1 minus 119909) (1 minus cos120601) (20)

And the voltage advance angle for the SC is given by

sin 120574 =radic(1 minus cos2120572)

radic1199092 + 2 (1 minus 119909) (1 minus cos120601) (21)

Therefore (20) and (21) are the control equations which willdecide that the optimum angle of voltage injection by theUPQC could be obtained through the proposed ACO-FLcontrol technique (Figure 12)

4 Fuzzy Logic Controller

In FLC basic control action is determined by a set of linguis-tic rules These rules are determined by the system Since thenumerical variables are converted into linguistic variablesmathematical modelling of the system is not required in FLC

The FLC comprises three parts fuzzification interferenceengine and defuzzification

41 Fuzzification Membership function values are assignedto the linguistic variables using seven fuzzy subsetsNB (Negative Big) NM (Negative Medium) NS (Nega-tive Small) ZE (Zero) PS (Positive Small) PM (PositiveMedium) and PB (Positive Big) The partition of fuzzysubsets and the shape of membership function adapt theshape up to appropriate systemThe values of input error119864(119896)and change in error CE(119896) are normalized by an input scalingfactor shown in Figure 3


Table 1 Fuzzy rules base

119890119890

NL NM NS ZE PS PM PLNL NL NL NL NM NS NS ZENM NL NM NM NM NS ZE ZENS NM NM NS NS ZE ZE PSZE NS NS ZE ZE ZE PS PSPS NS ZE ZE PS PS PM PMPM ZE ZE PS PM PM PM PLPL ZE PS PM PM PL PL PL

In this system the input scaling factor has been designedsuch that input values are between minus1 and +1 The triangularshape of the membership function of this arrangementpresumes that for any particular input there is only onedominant fuzzy subset The input error 119864(119896) for the FLC canbe calculated from themaximumpower point as given in (20)and (21)

119864 (119896) =119875ph(119896) minus 119875ph(119896minus1)

119881ph(119896) minus 119881ph(119896minus1)

CE (119896) = 119864 (119896) minus 119864 (119896 minus 1)

(22)

42 Interference Method Several composition methods suchas Max-Min and Max-Dot have been proposed in the liter-ature In this paper Max-Min method is used The outputmembership function of each rule is given by the minimumoperator and maximum operator Table 1 shows rule base ofthe FLC

43 Defuzzification As a plant usually requires a nonfuzzyvalue of control a defuzzification stage is needed To computethe output of the FLC height method is used and the FLCoutput modifies the control output Further the output ofFLC controls the switch in the inverter

The FLC uses a rule base as shown in Table 1 and themembership function as shown in Figure 4 The FLC ischaracterized as (i) seven fuzzy sets for each input andoutput (ii) triangular membership functions for simplicity(iii) fuzzification using continuous universe of discourse(iv) implication using Mamdanirsquos ldquominrdquo operator and (v)defuzzification using the ldquoheightrdquo method In UPQC theactive power reactive power terminal voltage of the lineand capacitor voltage are required to be maintained In orderto control these parameters they are sensed and comparedwith the reference values To achieve this the membershipfunctions of FLC are error change in error and output Inthe present work for fuzzification nonuniform fuzzifier hasbeen used If the exact values of error and change in error aresmall they are divided conversely and if the values are largethey are divided coarselyThe set of FLC rules is derived from

119906 = minus [120572119864+ (1minus120572)119862] (23)

where 120572 is called the self-adjustable factor which can regulatewhole region of operation 119864 is the error of the system

NL NM NS PLPMPS1 ZE

Error

Error

NL NM NS PLPMPS1 ZE

Output

NL NM NS PLPMPS1 ZE

e

Q

e

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

Figure 4 Membership functions of 119890 119890 and 119876

119862 is the varying ratio error and 119906 is the control variableA large value of error 119864 indicates that the given systemis not in the balanced state If the system is unbalancedthe controller should enlarge its control variables to balancethe system as early as possible One the other hand smallvalue of the error 119864 indicates that the system is near tobalanced state Overshoot plays an important role in thesystem stability Less overshoot is required for system stabilityand in restraining oscillations In such conditions 119862 in (11)plays an important role while the role of119864 is diminishedTheoptimization is done by 120572 During the process it is assumedthat the UPQC neither absorbs active power nor suppliesactive power during normal conditions So the active powerflowing through the UPQC is assumed to be constant Thecontrol surface of the proposed FLC is shown in Figure 4It indicates two inputs one output and a surface showinginput-outputmappingThe proposed defuzzificationmethodis briefed in the next section

44 Weighted Average Method This is a method that cannotbe used for asymmetrical output membership functions andcan be used only for symmetrical output membership func-tions Weighting each membership function in the obtainedoutput by its largest membership value forms this methodThe evaluation expression for this method is

119911lowast=

sum120583119888

(119911) 119911

sum120583119888

(119911) (24)

where sum is used for algebraic sum


1

08

06

0 a b z

120583

Figure 5 Weighted average method

From Figure 5 the defuzzified value can be calculatedusing (23) as follows

119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)

5 Ant Colony Optimization Algorithm

Ant Colony Optimization (ACO) algorithm is essentially asystem based on agents which simulate the natural behaviorof ants includingmechanisms of cooperation and adaptationIt is designed to reproduce the ability of ant colonies to deter-mine the shortest paths to food Real ants can indirectly com-municate by pheromone information without using visualcues and are capable of finding the shortest path between foodsources and their nests The ant deposits pheromone on thetrail while walking and the other ants follow the pheromonetrails with some probability which are proportioned to thedensity of the pheromoneThrough thismechanism ants willeventually find the shortest path Artificial ants imitate thebehavior of real ants of how they forage the food but can solvemuch more complicated problems than real ants can

ACO algorithms are based on the following ideas

(i) Each path followed by an ant is associated with acandidate solution for a given problem

(ii) When an ant follows a path the amount ofpheromone deposited on that path is proportional tothe quality of the corresponding candidate solutionfor the target problem

(iii) When an ant has to choose between two or morepaths the path(s) with a larger amount of pheromonehave a greater probability of being chosen by the ant

This algorithm ismost simple and involves only a few steps forfinding challenging solutions even in complex domain ACOis used to find the fuzzymembership functions for the controlof UPQC

51 The Proposed Flow Diagram for the ACO-FL ControlTechnique Figure 6 is implemented in MATLABSimulinkand the results are summarized in the next section

6 Simulation and Results

In order to test the performance of the UPQC using theproposed FLC it has been simulated for a 400V 50Hz three-phase AC supply using MATLABSimulink A three-phasediode rectifier feeding an RLC load is considered as nonlinearload The maximum load power demand is considered as11 kW + j12 kVAR The value of source resistance 119877

119878= 02Ω

and value of source inductance 119871119878= 02mH DC link

capacitor value is 10mF To test the operation of UPQCunderthe voltage sag condition 20 sag in line voltage has beencreated and simulated the corresponding voltage waveforms119881a 119881b and 119881ab are taken and shown in Figure 6 and theTHD in the system is 417 as shown in Figure 7 Againunder 20 voltage sag condition the performance of UPQChas been simulated using the PI controller (Figure 8) andits corresponding output voltage waveforms 119881a 119881b and 119881abare taken and shown in Figure 9 the voltage sag has beencompensated and THD have reduced to 049 as shown inFigure 10 When the proposed FLC incorporated UPQC isconnected to the system at 01 s the simulations are carriedout its corresponding output voltage waveforms 119881a 119881b and119881ab are taken and shown in Figure 10 the voltage sag has beencompensated and THD have reduced to 013 as shown inFigure 11The DC link capacitor voltage is held constant at itsreference value by the FLC

61 Discussion By observing Figure 6 it can be noted thatthe voltage at 119881b is sagging without the UPQC beingconnected This situation will be very serious in a powersystem and leads to imbalance in the system and maycause severe power quality issues in the overall distributionsystem To justify the robustness of the control algorithmfor voltage harmonic mitigation a three-phase SCR rectifierwith resistive load on the DC side is connected Thus thedistortion voltage across the load is introduced To envisagethe performance of the shunt APF and series APF indepen-dently bothAPFs aremade towork at different time intervalsInitially the shunt APF is connected for operation As shownin Figure 6 the supply currents are normal sinusoidal andphase line with the voltages even under unbalanced systemvoltage condition The source current THD in phase ldquocrdquo isenhanced from 1228 to 415 Later the series APF is madeto operate for conditioning The series-active power filterstarts compensating for the voltage harmonics by penetratinginstantaneously the phase harmonic voltage confirming thatthe load voltage gets no distortion

To substantiate this in Figure 9 a small distortion in theDC voltages is introduced but the DC link is able to regulatethe DC voltage only to its past magnitude Figure 10 conveysthat a flow of current in the neutral conductor is circulatingwhich has to be suppressed by the neutral phase of the shuntAPF thus forcing the supply-neutral current to zero Table 2summarizes the voltage sag mitigation of various methods

Due to the operation of the UPQC the shunt AF current(ica) compensates the reactive power and the harmonics ofthe load thus the source current follows the sinusoidal refer-ence currents The THD of the supply current is 319 whilethe load current THD is 1273 as shown in Figures 10 and 11


ACO based membershipfunction generation

Knowledge base about controlsignal for UPQC with

fuzzification and defuzzification

Input fuzzy inference fromUPQC control signal

Output control signal forcontrolling the UPQC

Figure 6 The proposed flow diagram for the ACO-FL control technique

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab

Figure 7 Output waveform without UPQC connected to thesystem

Table 2 Voltage sag mitigation performance

System withoutUPQC

UPQC with PIcontroller

System with ACO-FLCcontroller

Voltage sag persists Voltage sagmitigated

Voltage sag mitigatedwith high accuracy

respectively Moreover the peak value of the supply currentafter compensation is less than the peak value of the loadcurrent thereby increasing the loading capability of the ACmains The RMS value of phase ldquoardquo supply current aftercompensation is reduced to 2762A and before compensationits value is 3952A as observed from simulation results TheUPQC effectively maintains the sinusoidal supply currentsand a constant DC bus voltage when the load is reduced at052 sec and increased at 08 sec as shown in Figure 10 Dueto the connection of a single-phase diode rectifier a currentof 179 A flows in the load neutral conductor This currentis compensated for by the fourth leg of the shunt AF thusreducing the supply-neutral current to zero Table 3 shows thecomparison of THD produced by various methods

7 Conclusion

The confrontation in improving the power quality hasbecome a promising area of research amongst power system

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104

Figure 8 Output waveform with UPQC connected to the systemcontrolled by PI controller

Table 3 Total harmonic distortion for the proposed system

THD withoutUPQC

THD with PIcontroller

THD with ACO-FLCcontroller

417 049 013

and power electronic engineers and researchers With theever increasing advent of nonlinear loads and also due to highfrequency switching characteristics suitable conditionersare always a demand Unified Power Quality Conditioner(UPQC) is one of the promising power electronic circuitmodules to overcome voltage sag and total harmonic distor-tion problems as the circuit is modeled using both series-active and shunt-active power filters Thus the benefits ofboth the power filters are integrated for better power qualitymitigation is realized This paper considers the advantagesof the fuzzy logic and proposes a new control schemefor the Unified Power Quality Conditioner (UPQC) forminimizing the voltage sag and total harmonic distortion inthe distribution system The reference signal generated bythe fuzzy logic controller was given as input to the UPQCswitching module Exhaustive simulation experiments usingMATLABSimulink have been done and based on the resultsand output received it is observed that the proposed fuzzylogic controller is better in improving the power quality by


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104

Figure 9 Output waveform with UPQC connected controlled byACO-FLC technique

FFT analysis

Mag

(

of f

unda

men

tal) Fundamental (50Hz) = 4782 THD = 417

Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000

Figure 10 THD when UPQC is not connected to the system

FFT analysis

Mag

(

of f

unda

men

tal)

Fundamental (50Hz) = 4781 THD = 049

Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000

Figure 11 THD when UPQC is tuned by PI

FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020

Figure 12 THD when UPQC is tuned by ACO-FLC technique

minimizing the voltage sag and total harmonic distortionwhen compared to the conventional PI controller To enablethis a systematic approach for creating the fuzzymembershipfunctions is carried out by using an ant colony optimizationtechnique for optimal fuzzy logic control In this researchthe UPQC is only simulated for minimizing the voltage sagand total harmonic distortion in the distribution system butthe main purpose of UPQC is to compensate for voltageimbalance reactive power negative-sequence current andharmonics and these parameters will be considered in thenear future

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] E W Gunther and H Mehta ldquoA survey of distribution systempower quality-preliminary resultsrdquo IEEE Transactions on PowerDelivery vol 10 no 1 pp 322ndash329 1995

[2] Y Chen X Zha J Wang H Liu J Sun and H Tang ldquoUnifiedpower quality conditioner (UPQC) the theory modeling andapplicationrdquo in Proceedings of the International Conference onPower System Technology (PowerCon rsquo00) vol 3 pp 1329ndash1333IEEE 2000

[3] A Ghosh and G F Ledwich Power Quality Enhancement UsingCustom Power Devices Kluwer Academic Publishers 2002

[4] M Basu S P Das and G K Dubey ldquoComparative evaluationof twomodels of UPQC for suitable interface to enhance powerqualityrdquo Electric Power Systems Research vol 77 no 7 pp 821ndash830 2007

[5] V Khadkikar ldquoEnhancing electric power quality using UPQCa comprehensive overviewrdquo IEEE Transactions on Power Elec-tronics vol 27 no 5 pp 2284ndash2297 2012

[6] M Brenna R Faranda and E Tironi ldquoA new proposal forpower quality and custom power improvement OPENUPQCrdquoIEEE Transactions on Power Delivery vol 24 no 4 pp 2107ndash2116 2009

[7] D Graovac V Katic and A Rufer ldquoPower quality compensa-tion using universal power quality conditioning systemrdquo IEEEPower Engineering Review vol 20 no 12 pp 58ndash60 2000

[8] A Ghosh and G F Ledwich Power Quality Enhancement UsingCustom Power Devices Kluwer Academic 2002

[9] L H Tey P L So and Y C Chu ldquoUnified power quality condi-tioner for improving power quality using ANN with hysteresiscontrolrdquo in Proceedings of the International Conference on PowerSystem Technology (PowerCon rsquo04) vol 2 pp 1441ndash1446 IEEENovember 2004

[10] V G Kinhal P Agarwal and H O Gupta ldquoPerformanceinvestigation of neural-network-based unified power-qualityconditionerrdquo IEEE Transactions on Power Delivery vol 26 no1 pp 431ndash437 2011

[11] F Mekri M Machmoum N A Ahmed and B Mazari ldquoAfuzzy hysteresis voltage and current control of an unifiedpower quality conditionerrdquo in Proceedings of the 34th AnnualConference of the IEEE Industrial Electronics (IECON rsquo08) pp2684ndash2689 IEEE Orlando Fla USA November 2008

[12] M B I Reaz F Choong M S Sulaiman and F Mohd-YasinldquoPrototyping of wavelet transform artificial neural network and


fuzzy logic for power quality disturbance classifierrdquo ElectricPower Components and Systems vol 35 no 1 pp 1ndash17 2007

[13] M George ldquoArtificial intelligence based three-phase unifiedpower quality conditionerrdquo Journal of Computer Science vol 3no 7 pp 465ndash477 2007

[14] I Axente J N GaneshM BasuM F Conlon andK GaughanldquoA 12-kVADSP-controlled laboratory prototype UPQC capableof mitigating unbalance in source voltage and load currentrdquoIEEE Transactions on Power Electronics vol 25 no 6 pp 1471ndash1479 2010

[15] C Benachaiba A M Haidar M Habab and O AbdelkhalekldquoSmart control of UPCQ within microgrid energy systemrdquoEnergy Procedia vol 6 pp 503ndash512 2011

[16] A Elnady A Goauda and M M A Salama ldquoUnified powerquality conditioner with a novel control algorithm based onwavelet transformrdquo in Proceedings of the Canadian Conferenceon Electrical and Computer Engineering vol 2 pp 1041ndash1045IEEE 2001

[17] D Graovac V A Katic and A Rufer ldquoPower quality problemscompensation with universal power quality conditioning sys-temrdquo IEEE Transactions on Power Delivery vol 22 no 2 pp968ndash976 2007

[18] K S R Kumar and S V A R Sastry ldquoApplication of PI fuzzylogic and ANN in improvement of power quality using UPQCrdquoin Proceedings of the International Conference on SustainableEnergy and Intelligent Systems (SEISCON rsquo11) pp 316ndash319 July2011

[19] G S Kumar B K Kumar and M K Mishra ldquoMitigationof voltage sags with phase jumps by UPQC with PSO-basedANFISrdquo IEEE Transactions on Power Delivery vol 26 no 4 pp2761ndash2773 2011

[20] J Jayachandran N Muthu Preethi and S Malathi ldquoApplicationof fuzzy logic in PWM technique and dc link voltage controlfor a UPQC systemrdquo International Review on Modelling andSimulations vol 6 no 4 pp 1198ndash1204 2013

[21] W R A Ibrahim andMMMorcos ldquoArtificial intelligence andadvanced mathematical tools for power quality applications asurveyrdquo IEEE Transactions on Power Delivery vol 17 no 2 pp668ndash673 2002

[22] Y Liao and J-B Lee ldquoA fuzzy-expert system for classifyingpower quality disturbancesrdquo International Journal of ElectricalPower amp Energy System vol 26 no 3 pp 199ndash205 2004

[23] A E Leon S J Amodeo J A Solsona and M I Valla ldquoNon-linear optimal controller for unified power quality condition-ersrdquo IET Power Electronics vol 4 no 4 pp 435ndash446 2011

[24] S Mikkili and A K Panda ldquoReal-time implementation of PIand fuzzy logic controllers based shunt active filter controlstrategies for power quality improvementrdquo International Journalof Electrical Power and Energy Systems vol 43 no 1 pp 1114ndash1126 2012

[25] LA Zadeh ldquoFuzzy logic neural networks and soft computingrdquoCommunications of the ACM vol 37 no 3 pp 77ndash84 1994

[26] T J Ross Fuzzy Logic with Engineering Applications JohnWileyamp Sons 2009

[27] MATLABamp Simulink Toolbox Release TheMathWorks NatickMass USA 2012

[28] M Basu M Farrell M F Conlon K Gaughan and E CoyleldquoOptimal control strategy of UPQC for minimum operationallossesrdquo in Proceedings of the 39th International UniversitiesPower Engineering Conference (UPEC rsquo04) vol 1 pp 246ndash250IEEE September 2004

Submit your manuscripts athttpwwwhindawicom

Computer Games Technology

International Journal of

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Distributed Sensor Networks


Advances in

FuzzySystems

Hindawi Publishing Corporationhttpwwwhindawicom

Volume 2014


ReconfigurableComputing

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014


Applied Computational Intelligence and Soft Computing

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Advances inSoftware EngineeringHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Electrical and Computer Engineering

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Journal of

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httpwwwhindawicom Volume 2014

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Multimedia


Biomedical Imaging


ArtificialNeural Systems

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Computational Intelligence and Neuroscience

Industrial EngineeringJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Human-ComputerInteraction

Advances in

Computer EngineeringAdvances in



The control signal given to the UPQC plays a significantrole in establishing a better operation of the device Con-ventional control schemes are widely used in addition to thecontrol schemes derived from artificial intelligence which isalso recorded in the literature Applications of some advancedmathematical tools in general and wavelet transform inparticular in power quality are also applied An extensivecollection of literature covering applications of fuzzy logicexpert systems neural networks and genetic algorithms inpower quality is also growing [11]The ANN-based controlleris designed for the current control of the shunt-active powerfilter and trained offline using data from the conventionalproportional-integral controller [12] Similarly a fully digitalcontroller based on the TMS320F2812 DSP platform which isimplemented for the reference generation as well as controlpurposes is proposed [13]

In another attempt [14] the authors propose the applica-tion of fuzzy logic (FL) technique within microgrid energysystem based on the most modern power conditioningequipment devices such as Unified Power Quality Condi-tioner (UPQC) Similarly [15 16] a linear quadratic regulator(LQR) control technique embedded with the ANN is used tocoordinate the operation of the series and shunt VSIs of theUPQC In another development a control algorithm based onwavelet transform for UPQC to suppress current harmonicsand voltage sags is proposed [17] Subsequently in [18] theauthors emphasize enhancement of power quality by usingUPQC with fuzzy logic controller (FLC) and artificial neuralnetwork (ANN) controller on the conventional proportional-integral (PI) controller In [19] the determination of voltagereferences for series-active power filter is done based on arobust three-phase digital phase locked loop (PLL) systemusing fuzzy regulator

In [20] a particle swarm optimization (PSO) method isused to find the solution of the objective function derivedfor minimizing real power injection of UPQC along withthe constraints Adaptive neurofuzzy inference systems havebeen used to make the proposed methodology online forminimum real power injection with UPQC by using thePSO-based data for different voltage sag conditions A fuzzylogic with PWM technique for UPQC for power qualityimprovement is discussed in [21] In another extension[22] a fuzzy-expert system for automated detection andclassification of power quality disturbances is presented Thepaper [23] focuses on the application of wavelet transformtechnique to extract features from power quality disturbancewaveforms and their classification using a combination ofartificial neural network and fuzzy logic Simulations arecarried out with PI as well as fuzzy logic controller for both119901-119902 and 119868119889-119868119902 control strategies by considering differentvoltage conditions and adequate results were presented in[24] Thus the main focus of this proposed system is toimprove the power quality by compensating the voltage sagand eliminating the harmonics in the distribution networkusing a fuzzy logic [25 26] based technique In this researchthe fuzzy membership functions are carried out by usingan ant colony optimization [27] technique for optimal fuzzylogic control

+

Shunt APF

+

Series APF

DC link capacitor

voltage

Load

Vinj

IseVDC

minus

minus

Lsh Ish

Figure 1 Schematic diagram of the UPQC

The simulation is done using MATLAB and SimulinkToolbox for both control schemes used for the generationof control signals for the UPQC The rest of the paper isorganized in such a way that UPQC is revisited in Section 2Control strategy and necessary equations of the UPQC arediscussed in Section 3 Fuzzy logic and its features used in thisresearch are presented in Section 4 The proposed FL-ACOmethod is discussed in Section 5 Numerical simulationsare shown in Section 6 and the discussions and conclusionsfollow finally

2 Unified Power Quality ConditionerAn Overview

UPQC is one of the custom power devices used at the electri-cal power distribution systems to improve the power qualityof distribution system customers [2] UPQC could be used tocancel current harmonics to compensate reactive power toeliminate voltage harmonics to improve voltage regulationto correct voltage and current imbalances to correct voltagesag or swell and to avoid voltage interruptions [3] UPQCconsists of both shunt and series compensators A shuntcompensator is used to cancel the disturbances in currentwhereas series compensator is used to cancel disturbances involtage Shunt compensator could be connected to the left orright of the series compensator Ideally shunt compensatorinjects current to achieve purely balanced sinusoidal sourcecurrents in phase with the supply voltages at rated magnitudeand frequency On the other hand series compensation isused to inject voltage to maintain terminal voltage at ratedmagnitude and frequency

The schematic diagram of a three-phase UPQC is shownin Figure 1 Voltage source inverters are used for shunt andseries compensation One may note that both voltage sourceinverters are supplied froma commonDC link capacitor Oneof the voltage source inverters is connected in parallel withthe AC system while the other one is connected in series withthe AC system through injection transformers The inverterconnected in parallel together with its control circuit formsthe shunt compensation circuit On the other hand theinverter connected in series with appropriate control circuitforms the series compensation circuit For the successfuloperation of the UPQC the DC capacitor voltage should beat least 150 of the maximum line-line supply voltage To


DC link capacitor




Fuzzy controller



Load

Vsa

Vsa

Vsb

Vsb

Vsc

Vsc

VsaVsbVsc

Vla

Vla

Vlb

Vlb

Vlc

Vlc

Via

Vib

Vic

Isa

IsaIsa

Isb

IsbIsb

Isc

IscIsc

Isea

I sea

IsebIsec

Iseb

I sec

Isealowast Iseb

lowast Iseclowast

Vialowast

Viblowast Vic

lowast

Isalowast Isb

lowast Isclowast

Isplowast

VDC

VDC

VDClowast

I shb

I sha

Lsh



1198812

inj = 1198812




+ 1198682

op1198662

2 (120579 120573)119885SLC(2)






[28]







119881in = 119881ph1 = 119881in1 = Constant = 1198810 (5)




119868in2 cos120573 = 119868ph2 cos 120579 (6)

1198681198622 =

119868ph2 sin (120579 minus 120573)cos120573

(7)



Consideredsystem

minus

r e Q

d

dt

120579Σ

e




1198681198711 = 1198681198712 = 1198680 (8)


119881119878119868119878= 119881119871119868119871cos120601 = Constant (9)



1198811198782 = (1minus119909)1198811198781 = (1minus119909)1198810 (10)


11988111987121198681198712 and

1198681198782 =

1198810119868119871 cos1206011198810 (1 minus 119909)

= 1198680cos120601(1 minus 119909)

(11)

Thus

1198811198712 sin120572 = 119881inj sin 120574 (12)

1198811198712 cos120572 = 1198811198782 +119881inj cos 120574 (13)

or

sin 120574 = 1198811198712119881inj

sin120572


2

1198712sin2120572)

119881inj

(14)

From (7) and (12)

1198812

inj = 1198812

0 1199092+ 211988120 (1minus119909) (1minus cos120572) (15)


10038161003816100381610038161003816119881inj

1003816100381610038161003816100381610038161003816100381610038161198681198782


(1 minus 119909)(16)

which yields

1198681198622 cos120572 = 1198681198712 +119881inj sin (120601 minus 120572) (17)


11986811986221198811198712 + 119868

2

1198622119885SLC

= 1198681198712(1198810

sin (120601 minus 120572)cos120572

+ 1198681198712(

sin (120601 minus 120572)2

cos120572)119885SLC)

(18)



+ 1198682

op1198662

2 (120579 120573)119885SLC


(1 minus 119909)

1198662 (120579 120573) =sin (120601 minus 120573)

cos120573

(19)



1198681198782 = 119868













119890119890



119864 (119896) =119875ph(119896) minus 119875ph(119896minus1)

119881ph(119896) minus 119881ph(119896minus1)

CE (119896) = 119864 (119896) minus 119864 (119896 minus 1)

(22)




119906 = minus [120572119864+ (1minus120572)119862] (23)


NL NM NS PLPMPS1 ZE

Error

Error

NL NM NS PLPMPS1 ZE

Output

NL NM NS PLPMPS1 ZE

e

Q

e

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10




119911lowast=

sum120583119888

(119911) 119911

sum120583119888

(119911) (24)



1

08

06

0 a b z

120583



119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)











119878= 02Ω













0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




DC link capacitor




Fuzzy controller



Load

Vsa

Vsa

Vsb

Vsb

Vsc

Vsc

VsaVsbVsc

Vla

Vla

Vlb

Vlb

Vlc

Vlc

Via

Vib

Vic

Isa

IsaIsa

Isb

IsbIsb

Isc

IscIsc

Isea

I sea

IsebIsec

Iseb

I sec

Isealowast Iseb

lowast Iseclowast

Vialowast

Viblowast Vic

lowast

Isalowast Isb

lowast Isclowast

Isplowast

VDC

VDC

VDClowast

I shb

I sha

Lsh



1198812

inj = 1198812




+ 1198682

op1198662

2 (120579 120573)119885SLC(2)






[28]







119881in = 119881ph1 = 119881in1 = Constant = 1198810 (5)




119868in2 cos120573 = 119868ph2 cos 120579 (6)

1198681198622 =

119868ph2 sin (120579 minus 120573)cos120573

(7)



Consideredsystem

minus

r e Q

d

dt

120579Σ

e




1198681198711 = 1198681198712 = 1198680 (8)


119881119878119868119878= 119881119871119868119871cos120601 = Constant (9)



1198811198782 = (1minus119909)1198811198781 = (1minus119909)1198810 (10)


11988111987121198681198712 and

1198681198782 =

1198810119868119871 cos1206011198810 (1 minus 119909)

= 1198680cos120601(1 minus 119909)

(11)

Thus

1198811198712 sin120572 = 119881inj sin 120574 (12)

1198811198712 cos120572 = 1198811198782 +119881inj cos 120574 (13)

or

sin 120574 = 1198811198712119881inj

sin120572


2

1198712sin2120572)

119881inj

(14)

From (7) and (12)

1198812

inj = 1198812

0 1199092+ 211988120 (1minus119909) (1minus cos120572) (15)


10038161003816100381610038161003816119881inj

1003816100381610038161003816100381610038161003816100381610038161198681198782


(1 minus 119909)(16)

which yields

1198681198622 cos120572 = 1198681198712 +119881inj sin (120601 minus 120572) (17)


11986811986221198811198712 + 119868

2

1198622119885SLC

= 1198681198712(1198810

sin (120601 minus 120572)cos120572

+ 1198681198712(

sin (120601 minus 120572)2

cos120572)119885SLC)

(18)



+ 1198682

op1198662

2 (120579 120573)119885SLC


(1 minus 119909)

1198662 (120579 120573) =sin (120601 minus 120573)

cos120573

(19)



1198681198782 = 119868













119890119890



119864 (119896) =119875ph(119896) minus 119875ph(119896minus1)

119881ph(119896) minus 119881ph(119896minus1)

CE (119896) = 119864 (119896) minus 119864 (119896 minus 1)

(22)




119906 = minus [120572119864+ (1minus120572)119862] (23)


NL NM NS PLPMPS1 ZE

Error

Error

NL NM NS PLPMPS1 ZE

Output

NL NM NS PLPMPS1 ZE

e

Q

e

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10




119911lowast=

sum120583119888

(119911) 119911

sum120583119888

(119911) (24)



1

08

06

0 a b z

120583



119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)











119878= 02Ω













0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in





Consideredsystem

minus

r e Q

d

dt

120579Σ

e




1198681198711 = 1198681198712 = 1198680 (8)


119881119878119868119878= 119881119871119868119871cos120601 = Constant (9)



1198811198782 = (1minus119909)1198811198781 = (1minus119909)1198810 (10)


11988111987121198681198712 and

1198681198782 =

1198810119868119871 cos1206011198810 (1 minus 119909)

= 1198680cos120601(1 minus 119909)

(11)

Thus

1198811198712 sin120572 = 119881inj sin 120574 (12)

1198811198712 cos120572 = 1198811198782 +119881inj cos 120574 (13)

or

sin 120574 = 1198811198712119881inj

sin120572


2

1198712sin2120572)

119881inj

(14)

From (7) and (12)

1198812

inj = 1198812

0 1199092+ 211988120 (1minus119909) (1minus cos120572) (15)


10038161003816100381610038161003816119881inj

1003816100381610038161003816100381610038161003816100381610038161198681198782


(1 minus 119909)(16)

which yields

1198681198622 cos120572 = 1198681198712 +119881inj sin (120601 minus 120572) (17)


11986811986221198811198712 + 119868

2

1198622119885SLC

= 1198681198712(1198810

sin (120601 minus 120572)cos120572

+ 1198681198712(

sin (120601 minus 120572)2

cos120572)119885SLC)

(18)



+ 1198682

op1198662

2 (120579 120573)119885SLC


(1 minus 119909)

1198662 (120579 120573) =sin (120601 minus 120573)

cos120573

(19)



1198681198782 = 119868













119890119890



119864 (119896) =119875ph(119896) minus 119875ph(119896minus1)

119881ph(119896) minus 119881ph(119896minus1)

CE (119896) = 119864 (119896) minus 119864 (119896 minus 1)

(22)




119906 = minus [120572119864+ (1minus120572)119862] (23)


NL NM NS PLPMPS1 ZE

Error

Error

NL NM NS PLPMPS1 ZE

Output

NL NM NS PLPMPS1 ZE

e

Q

e

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10




119911lowast=

sum120583119888

(119911) 119911

sum120583119888

(119911) (24)



1

08

06

0 a b z

120583



119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)











119878= 02Ω













0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in





119890119890



119864 (119896) =119875ph(119896) minus 119875ph(119896minus1)

119881ph(119896) minus 119881ph(119896minus1)

CE (119896) = 119864 (119896) minus 119864 (119896 minus 1)

(22)




119906 = minus [120572119864+ (1minus120572)119862] (23)


NL NM NS PLPMPS1 ZE

Error

Error

NL NM NS PLPMPS1 ZE

Output

NL NM NS PLPMPS1 ZE

e

Q

e

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10

minus10

minus09

minus08

minus05

minus04

minus02

minus01 0

01

02

04

05

08

09

10




119911lowast=

sum120583119888

(119911) 119911

sum120583119888

(119911) (24)



1

08

06

0 a b z

120583



119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)











119878= 02Ω













0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




1

08

06

0 a b z

120583



119911lowast=119886 (08) + 119887 (065)

08 + 065 (25)











119878= 02Ω













0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in










0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

2000

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1000

minus2000

Va

Vb

Vab



System withoutUPQC






7 Conclusion


0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

TimeM

agni

tude

0 005 01 015 02 025 03 035 04 045 05

0

1000

Time

Mag

nitu

de

minus1000

minus1

minus1

Va

Vb

Vab

times104

times104



THD withoutUPQC



417 049 013



0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0

1

Time

Mag

nitu

de

0 005 01 015 02 025 03 035 04 045 05

0500

1000

Time

Mag

nitu

de

minus1000minus500

minus1

minus1

Va

Vb

Vab

times104

times104


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)

10

8

6

4

2

00 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men

tal)


Frequency (Hz)

0

05

1

15

0 100 200 300 400 500 600 700 800 900 1000


FFT analysis

Mag

(

of f

unda

men


Frequency (Hz)0 100 200 300 400 500 600 700 800 900 1000

1614121

080604020





References






































Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in




























Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in










Advances in

FuzzySystems


Volume 2014












Journal of

Journal of





Advances in

Multimedia


Biomedical Imaging



Advances in


RoboticsJournal of










Advances in



Documents

Research Article MATLAB Simulation of UPQC for Power