Design And Simulation Of Active Single-axis Photovoltaic Tracker Fed .
Sathishkumar et al., International Journal of Advanced Engineering TechnologyE-ISSN 0976-3945Research PaperDESIGN AND SIMULATION OF ACTIVE SINGLE-AXISPHOTOVOLTAIC TRACKER FED PERMANENT MAGNETBRUSHLESS MOTOR FOR COMMERCIAL APPLICATIONSSathishkumar Shanmugam1 Meenakumari Ramachandran2 Anbarasu Loganathan3Address for Correspondence1Research Scholar Anna University, Chennai & Assistant Professor, Department of EEE,Jansons Institute of Technology, Coimbatore.2Professor, Depertment of EEE, Kongu Engineering College, Erode3Assistant Professor, Department of EEE, Erode Sengunthar Engineering college, Erode.ABSTRACT—This Research paper presents the modelling and simulation of an active single axis solar tracker fed permanent magnet (PM)brushless motor for residential applications. The aim of this work is to extract the maximum available energy from the sunby tracking its irradiance through some mechanical means as well as to feed the energy to the permanent magnet brushlessmotor for consumer appliances. A photovoltaic module with sun tracking arrangement by means of a Permanent MagnetDirect Current (PMDC) motor is proposed. The solar irradiance is detected by two Light-Dependent Resistor (LDR) sensorsthat are located on the top and bottom surface of the photovoltaic panel. The position and status of the sun are detected andthe resultant signals from the sensors are fed into an electronic control system that operates a low-speed tracking motor torotate the panel. Based on the sensor signals, the microcontroller determines the optimum angle for the panel to track atvarious insolation. A battery with charge controller topology is used to store the electrical energy generated from the sun.Then the stored energy is given to the three phase inverter driven ceiling fan motor. A computer model of the standalonesolar tracker system feeding ceiling fan is modelled using MATLAB/Simulink environment.KEYWORDS—Irradiance, Smart PV Tracker, LDR Sensor, PMDC Motor, Ceiling Fan PM Brushless Motor.INTRODUCTIONThe world population is increasing day by day andthe demand for energy is increasing accordingly. Oiland coal as the main source of energy nowadays, isexpected to end up from the world during the recentcentury which explores a serious problem inproviding the humanity with an affordable andreliable source of energy. The need of the hour isrenewable energy resources with cheap runningcosts. Among the renewable energy resources, solarenergy is the most essential and sustainable energybecause of its abundance and sustainability.Irrespective of the sunlight’s intermittency, solarenergy is widely available and completely free ofcost. Recently, Photovoltaic (PV) system is wellrecognized and widely utilized to convert the solarenergy for electric power applications. It can mental impact and emission by way of solarradiation. The DC power is converted to AlternatingCurrent (AC) power with an inverter, to power localloads or fed back to the utility.MODELING OF SMART PV TRACKERA solar tracker is a device that orient photovoltaicarray towards the sun. In flat-panel PV applicationstrackers are used to minimize the angle of incidencebetween the incoming light and a photovoltaic panel.This increases the amount of energy produced by thephotovoltaic array. The main focus in this section isto simulate the single axis solar tracking systemduring the automatic mode using MATLABTM/SimulinkTM. The simulation run was performed inevery second of the entire 10 hours or 36000 secondsof experimental set up. The ODE45 solver type ofvariable step size was used throughout thesimulations.The simulation model is implemented in a way thatwhen the sun irradiance falls on the sensors, thePMDC motor moves the PV panel in an incrementalway till the sunset. The LDR sensors signal providethe input to the microcontroller for the PMDC motorto rotate the PV panel. The charging and dischargingmechanism of the battery uses the charger subsystem.The PV tracking panel with the two LDR sensorsInt J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198generates the voltage outputs (i.e. V LDR B andV LDR T) based on the corresponding sunirradiance data used in the simulation. The irradiancefrom the sun model was obtained by dividing thepower obtained from the tracker by the surface areaof the PV cells. The PMDC motor rotates the panel atan angle based on the microcontroller PWM signal.This process repeats again until the sunset. Duringthe process, the PV panel generates direct current thatkeeps the 12V battery charged. The battery getscharged or discharged depending on the state of thecharger.SMART TRACKER PV PANELThe smart tracker panel was installed with two LDRsensors. Assuming both sensors are placed in parallelwith the PV panel, the effective irradiance is similar.As the results, the smart tracker is unable to performthe proposed sun tracking algorithm. To circumventthis, the top and bottom sensors were positioned at45 and 135 respectively as seen in Fig.1. When thesunlight falls onto the PV panel, the LDR sensorsgenerate different voltages (that is V LDR B andV LDR T according to the changes in the sunirradiance) to move the PV panel.Fig.1 PV Panel and LDR Sensor Angle PositionMICROCONTROLLER MODELAs shown in Fig.2, the microcontroller model ismodeled using the embedded MATLABTM function.The inputs to this function are LDR B and LDR T, areal time clock and initial buffer value of 1.5. One ofthe inputs (named Extime) is used to compare thecurrent time with the previous time when the PWM
Sathishkumar et al., International Journal of Advanced Engineering Technologyvalue changes. The microcontroller generates outputduration of 1.5ms to rotate the PV panel if thevoltage difference of the LDR sensors is less than0.07V and are both less than 0.75V (very lowirradiance).If LDR sensors voltages are both greater than 0.75Vbut the voltage difference is less than 0.07V, the PVpanel remains in the current position. In the casewhen the LDR sensor values is greater than 0.07V,the motor turns the PV panel by adjusting its PWMvalue until the sensors’ voltages are equal. The nextcycle starts after the delay time of 0.7 seconds duringthe simulation.E-ISSN 0976-3945Fig.2 Microcontroller ModelThe process flow chart for the microcontrolleroperation is illustrated in Fig.3 below.Fig.3 Process Flow Chart for Microcontroller OperationMOTOR MODELThe solar panel is designed to drive the PV panel in asmall angle, between 0 to 180 degrees at a low speed.PWM is used to control the motor. The PWM is acontinuous square wave with a period of 20ms. Withthe PWM signal, the output shaft of the PMDC motorchanges the angular position of the PV panel. Thefollowing parameters are used to model the PMDCmotor.1. Moment of inertia (J) 0.01 kg.m22. Damping ratio (B) 0.1 Nm.s3. Electromotive force constant (Kt) 0.01Nm/Amp4. Back electromotive force constant (Ke) 0.01V/rad/s5. Electric resistance (Rm) 1 ohm6. Electric inductance (Lm) 0.5 H7. Input Voltage (Vm)8. Output angle (θ)As the modeling of the PMDC motor iscommon, we write the following transfer functionbetween the output rotational angle and the inputvoltage is written as follows, (s)1Kt []Vm( s ) s ( Js B)( Lms Rm) KtKe(1)Based on this transfer function, the PMDC motormodel can be modeled in Simulink using the look-uptables. The lookup table uses the PWM as an input torotate the motor to a pre-determined angle. WhenInt J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198pulse width changes from 1.25ms to 1.75ms, thepanel angle changes from 0 degree to 180 degree in alinear manner. As the PWM values and itscorresponding angles are incorporated in the look-uptables, the panel angle variation is linear therebyavoiding non-linearty. The actual and the desiredpulse-width are then compared to obtain the errorsignal for the Proportional- Integral-Derivative (PID)controller (using the controller gains: Kp 60, Ki 30,Kd 3) to drive the motor to the desired angle. Theembedded MATLABTM function block is used todeactivate the motor load when it is not turning. Anexternal load of pure resistance value ( 40Ω) wasadded to show whether the motor is able to drive thePV panel. The weight could vary due to the modelingerror and the wind disturbance.Fig.4 PMDC Motor ModelThe panel current Ipv is used to charge the 12Vbattery. Simulation time is set to 36000 secondscorresponding to 10 hours (7am to 5pm).The sunangle and the panel angle is observed through thescope as this shows the actual tracker output
Sathishkumar et al., International Journal of Advanced Engineering TechnologyE-ISSN 0976-3945Fig.5 Smart PV Tracker ModelMODELINGOFCEILINGBRUSHLESS MOTORBRUSHLESS DC MOTORSFANPMceiling fan as shown in Fig.7 has much betterefficiency and excellent constant RPM control as itoperates out of fixed DC voltage. The proposedBLDC motor and the control electronics operates outof 12V DC. A comparison between BLDC andconventional ceiling fans is shown below (42” ceilingfan is considered). The power consumption is lessthan half at full speed and is about 20% at low speedfor the BLDC motor compared to the conventionalmotor based ceiling fan, as can be seen from theFig.8 below.Fig.6 Basic Block Diagram of BLDC MotorThe Fig.6 illustrates the basic block diagram ofBLDC motor. The controller logic circuits contain abinary state generator, which interprets the signalsfrom the sensors and the input direction regarding theposition of the permanent magnet rotor. The logiccircuit outputs a code which tells a drive circuit,which windings should be energized. The rotation ofthe motor is changed within the control logic, whichin turn reverses the phase energizing sequence. Aswitch or logic input is usually provided to convertthe logic from clockwise to counterclockwise.BLDC CEILING FAN MOTORFig.7 Typical BLDC Ceiling Fan MotorToday the typical ceiling fan is based on AC motorswhich are power hungry. Along with this the typicalAC motor based fans have the rpm control throughthe capacitor or resistor based regulators and is notefficient as there is loss in the regulator itself to someextent. In addition the RPM control is by controllingthe voltage and the voltage fluctuations of the mainsmake it very challenging to have constant RPM basedon the AC mains supply. Further, existing AC motorsolution, results in power factor degradation with noimprovement for PF and there are other ill effectslike harmonics injection to the AC mains, etc. Thetotal amount of air flow or displacement is based onthe blade size & rpm and does not change due to anyother factor. The proposed solution is to keep thesame air flow or displacement with less of energyusage along with improving the PF using the BLDCmotor based ceiling fans. Typical BLDC motor basedInt J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198Fig.8 BLDC versus Conventional Fan PowerConsumptionThe mechanical energy required to rotate at fullspeed (typically 360rpm) for a 42” conventionalceiling fan is about 0.65Nm. The equivalent electricalenergy would be around 26Watts, considering about95% efficiency for mechanical to electrical energyconversion. The total power consumption of 32 wattsas seen in the above design seems to be with in thedesign boundaries for such a motor.MODELING OF BRUSHLESS MOTORThe model of a BLDC consisting of three phases isexplained by means of equations. Since there is noneutral used, the sum of the three phase currentsmust add up to zero (i.e.),ia ib ic 0(2)ia ib ic(3)Fig.9 R, L and Back-emf BLDC Model
Sathishkumar et al., International Journal of Advanced Engineering TechnologyReferring to the Fig.9, the following equations areused to model the two pole three-phase BLDC motor. va Rs 0 0 Ia Laa Lab Lac Ia eas vb Ib p (4) 0 Rs 0 Lba Lbb Lbc Ib ebs vc 0 0 Rs Ic Lca Lcb Lcc Ic ecs If the permanent magnet inducing the rotor field is inthe shape of an arc, it requires that the inductances beindependent of the rotor position, henceLaa Lbb Lcc Lp(5)Considering the symmetry of the above matrix inaddition to independence w.r.t. the rotor position,Lab Lac Lba Lbc Lca Lcb M(6)Above equation reduces to Lp M M Ia eas va Rs 0 0 Ia vb Ib p M Lp M Ib ebs(7) 0 Rs 0 M M Lp Ic ecs vc 0 0 Rs Ic E-ISSN 0976-3945wave that provides a higher voltage to the motor andlower total harmonic distortion (THD). Theadvantage of space vector PWM is, it considers thethree phase inverter as a single unit.For a three phase inverter shown in the Fig.6, thereare 8 possible switching states. Among the 8switching states, 6 states are active states and 2 statesare zero states or null states. In active states, themotor terminals are connected to the DC bus throughvarious combinations of the switches. During nullstates, the motor terminals are shorted through theupper or lower switches. The active states have themagnitude of 2Vdc/3 which gives the hexagonalshape shown in the Fig.11. From the above equations, we have va Rs 0 0 Ia 0 Ia eas La M 0 vb Ib p 0Lb 0 Ib ebs M 0 Rs 0 vc 0 0 Rs Ic 00 Lc M Ic ecs (8)Rearranging the equations, we have obtainedequations in a form suitable for simulation. Thus, themodel of the BLDC reduces to that in Fig 10. Theback-emf waveforms ea, eb & ec are trapezoidal innature and can be represented by either the FourierSeries or by Laplace Transforms.Fig.10 Simplified R, L and Back-emf BLDC ModelThe back-emf is given by,ea kbfas(θr)ωm(9)where fas is a unit function generator correspond tothe trapezoidal induced emf as a function of rotorelectrical positionθr. kb is the emf constant and ωmrotor electrical speed.fas is given by,fas(θr) (θr) 6/π, 0 θr π/6 1,π/6 θr 5 π/6 (π -θr) 6/π,5π/6 θr 7 π/6 -1,7π/6 θr 11π/6(10) (θr-2π)6/π11π/6 θr 2πThe electromagnetic torque (Te) developed by themotor is given by,Te kt{fas(θr)ia fbs(θr)ib fcs(θr)ic}(11)Te ktФasIa(12)The electromechanical equation with the load isgiven by,Jpωm Bωm (Te-TL)(13)where J is the moment of inertia, B is the friction coefficient and TL is the load torque.ωm (Te-TL-Bωm)/J(14)θr ωmdt(15)SPACE VECTOR MODULATIONFor sinusoidal commutation, a sine lookup table hasto be created with respect to the rotor angle. SpaceVector Pulse Width Modulation (SVPWM) is a moresophisticated method to generate a fundamental sineInt J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198Fig.11 Space Vector DiagramThe possible eight switching states of an inverter isgiven in the Table 1.TABLE 1 INVERTER SWITCHING STATESStateONDevicesVanVbnVcn012345S2, S4, S6S1, S4, S6S1, S3, S6S3, S2, S6S2, S3, S5S2, S4, c/3Vdc/32Vdc/36S1, S4, S5Vdc/3Vdc/3V6 (101)7S1, S3, eVectorV0 (000)V1 (100)V2 (110)V3 (010)V4 (011)V5 (001)0V7 (111)The locus of pure sinusoidal voltage waveform iscircular in nature. Hence for the reference sine wavegeneration, each desired position on the circular locusis obtained by an average relationship between twoneighboring active vectors. For the remaining timeperiod, null vectors are used. For example, if thereference vector Vx is in sector 1 as shown in Fig.11,it can be resolved as,(16)(17)Therefore,(18)(19)where Va and Vb are the adjacent vectors V100 andV110 respectively. Hence the reference vector Vx canbe obtained by applying Va for the time ta and Vb forthe time tb over a period T0. The vector Vx is givenmathematically as,
Sathishkumar et al., International Journal of Advanced Engineering TechnologyVbVaWhere, ta T 0 , tb V 110 T 0 ,V 100(20)E-ISSN 0976-3945The above waveform gives the comparison of the sunangle with that of the panel angle. From the figure itis clear that the panel tracks the sun’s movement atvarious irradiance. From Fig.14 it is observed that thepanel angle follows the sun angle throughout 180degree for all insolation.t 0 T 0(1 ta tb ) .The Simulink model for the ceiling fan brushlessmotor is shown below in Fig.12. Field orientedclosed loop control technique with space vectormodulation for the three phase inverter switches isincorporated.Fig.15 LDR Sensor OutputThe above figure represents the output of the both topand bottom LDR sensors. The maximum differencebetween the two outputs is observed again at noon(12 pm)Fig.12 Ceiling Fan ModelThe nominal speed and load torque of ceiling fan are350RPM and 0.6Nm respectively. The ceiling fanmotor parameters are shown in Table 2 below.TABLE 2 CEILING FAN MOTOR PARAMETERSParameterStator resistance per phase (Rs)D-axis inductance per phase (Ld)Q-axis inductance per phase (Lq)Back-emf Constant (Kb)Torque Constant (Kt)Moment of Inertia (J)Co-efficient of Friction (B)Value0.475 Ω8.5e-4 H8.5e-4 H15.966 V/s/rad15.966 Nm/A0.0008 kg.m20.001Nm.sSIMULATION RESULTS AND DISCUSSIONSMART PV TRACKER RESULTSAs per the modeling guidelines, the smart PV trackeris modeled in Simulink as shown in Fig.5. The panelcurrent Ipv is used to charge the 12V battery.Simulation time is set to 36000 secondscorresponding to 10 hours (7am to 5pm).The sunangle and the panel angle is observed through thescope as this shows the actual tracker output.Fig.16 State of Charge of BatteryThe above figure represents the state of charge of thebattery. It takes nearly 5 hours for the battery toattain its 100% SOC by getting charged by the panel.Fig.17 Battery VoltageFrom the above figure Fig.16 it is observed that fullcharge represents 12.32V (100%). Also the completedischarge corresponds to 11.52V (0%).CEILING FAN PM BRUSHLESS MOTORRESULTSFig.13 Panel CurrentThe above figure shows the panel current waveform.From the above figure it is clear that the maximumpanel current is observed when the sun isperpendicular to the whole panel area (i.e., 12 pmnoon). The peak value of the panel current indicatesthe high irradiance of sun during noon.Fig 18 DC Bus VoltageFig.14 Sun Angle and Panel AngleInt J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198The above figure represents the12 V DC Voltageinput for the BLDC Ceiling Fan motor which iscoming out from the panel. It is fed to the three phaseinverter.The above figure represents the torque demand inputvariation to the ceiling fan motor. This is done toensure the system response and stability. 0.5Nmtorque corresponds to the load to the motor withblades connected. By varying the torque the response
Sathishkumar et al., International Journal of Advanced Engineering TechnologyE-ISSN 0976-3945of the system is observed by observing the variationsin the other parameters such as speed, current androtor angle.Fig.23 Speed OutputFig.19 Torque InputFig.20 Rotor AngleThe above figure corresponds to the rotor angle ofceiling fan motor. As we are varying the torque anspeed simultaneously, the corresponding response bythe rotor is observed by variations in attaining itsmaximum value.The above waveforms are the simulation resultsobtained from the ceiling fan brushless motor modelin Simulink. Simulation time is set to 0.5 seconds.The torque input 0.6Nm is given in steps as shown inFig.19. Coordinate transforms such as Clarke, Park,inverse Park and inverse Clarke are done to convertthe three phase to two phase quantities and viceversa. Set speed and estimated speed of the fan motoris shown in Fig.23 and the control is much précisedbased on the waveforms observed.CONCLUSIONIn this work modeling of the smart PV tracker fedPM brushless motor for residential application i.e.,ceiling fan has been presented. To extract themaximum power from the PV source single axisactive solar tracker is used. The maximum outputthus obtained from the panel is stored in the batteryand it is fed to the brushless ceiling fan motor model.Field oriented control with sinusoidal space vectormodulation technique is incorporated in the model toobtain highly précised control.REFERENCES1.Fig.21 Phase ‘A’ VoltageThe above figure corresponds to the voltagewaveform of the phase ‘A’. It corresponds to thespace vector pulse width modulated output of the DCinput voltage(12V). From the above waveform itselfit is clear that the maximum value of the phasevoltage is 1.732( 3 ) times that of the DC inputvoltage.Fig.21 Phase ‘A’ CurrentFig.22 Three-phase CurrentFrom Fig.21and Fig.22 it is observed that there is anincrease in current to a high value as the motor startswith initial load and also due to the consecutivechanges in input. It settles as the motor gains thespeed.Int J Adv Engg Tech/Vol. VII/Issue I/Jan.-March.,2016/193-198C. Saravanan, Dr M.A. Panneerselvam, I. WilliamChristopher, 2011, “A Novel Low Cost AutomaticSolar Tracking System”, International Journal ofComputer Applications (0975 – 8887) Volume 31–No.9.2. B. Koyuncu, K. Balasubramanian, 1991, “Amicroprocessor controlled automatic sun tracker”, IEEETransactions on Consumer Electronics.37, 913-917.3. A. Zeroual, M. Raoufi, M. Ankrim, A. J. Wilkinson,1998, “Design and construction of a closed loop suntracker with microprocessor management”, SolarEnergy. 19, 263-274.4. P. Hatfield, 2006, “Low cost solar tracker”, Bachelor ofElectrical Engineering Thesis, Department of Electricaland Computer Engineering, Curtin University ofTechnology.5. O. Bingol, A. O. Altintas, 2006, “Microcontroller basedsolar-tracking system and its implementation”, Journalof Engineering Sciences.12, 243-248.6. S. A. Kalogirou, 1996, “Design and construction of aone-axis sun-tracking”, Solar Energy.57, 465-469.7. H. Mousazadeh, A. Keyhani, A. Javadi, H. Mobli, K.Abrinia, A. Sharifi, 2009 , “A review of principle andsun-tracking methods for maximizing solar systemsoutput”, Renewable and Sustainable Energy Reviews.13, 1800-1818.8. [8] H. L. Tsai, 2010, “Insolation-oriented model ofphotovoltaic module using Matlab/Simulink”, SolarEnergy. 84, 1318-1326.9. Tanvir Arafat Khan Md., S.M. Shahrear Tanzil, RifatRahman, S M Shafiul Alam, 2010, “Design andConstruction of an Automatic Solar Tracking System”,presented at 6th International Conference on Electricaland Computer Engineering, ICECE 2010, 18-20.10. Jiping Chen, Tao Yu, Guanhua Zhou, Xingfeng Chen,Guolin Yu, 2011, “Design of the Attitude AutomaticAdjusting System for the Solar Panel”, presented at 2ndInternational Conference on Computing, Control andIndustrial Engineering (CCIE), IEEE, pp 367 – 370.11. Pillay P and Krishnan R, 1988, “Modeling ofPermanent Magnet Motor Drives”, IEEE Transactionson IA, vol.25, pp.274-279
MODELING OF SMART PV TRACKER A solar tracker is a device that orient photovoltaic array towards the sun. In flat-panel PV applications trackers are used to minimize the angle of incidence between the incoming light and a photovoltaic panel. This increases the amount of energy produced by the photovoltaic array. The main focus in this section is
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Simulation is a process of emulating real design behavior in a software environment. Simulation helps verify the functionality of a design by injecting stimulus and observing the design outputs. This chapter provides an overview of the simulation process, and the simulation options in the Vivado Design Suite. The process of simulation includes:
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Simulation Models and Analyses Reference Version (v1.6) Apr 21, 2008 1 This reference details the simulation models and circuit simulation analyses and describes some simulation troubleshooting techniques. Simulation Models The Altium Designer-based Circuit Simulator is a true mixed-signal simulator, meaning
