grid integration of distributed generation and statcom systems
TRANSCRIPT
REAL TIME HARDWARE IMPLEMENTATION OF POWER CONVERTERS FOR GRID INTEGRATION OF DISTRIBUTED GENERATION AND STATCOM
SYSTEMS
Ishan JaithwaDr Shuhui Li || Dr Tim Haskew || Dr Rachel Fraizer
RANGE Electric
MY DEFENCE
• Simulation of STATCOM model for 50V using
Conventional Control Direct Current Vector Control Neural Network Control
• Hardware verification of STATCOM / AC/DC/AC CONVERTER AND FILTER model for 50V using d SPACE and OPALRT systems
Conventional Control Direct Current Vector Control Neural Network Control
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SIMULATION
HARDWARE
SIMULATION
CONVENTIONAL CONTROL (50V) DCC (50V)
NEURAL NETWORK
CONTROL (50V)DCC (200 kV)
NEURAL NETWORK
(200kV)
HOW I PROCEED
HARDWARE EXPERIMENT
D SPACE
Conventional Direct vector Control
Neural Network Control
OPAL RT
Conventional
Open Loop Test
Direct vector Control
Neural Network Control
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STATCOM
A STATic COMpensator compensates reactive power and provide voltage support to an ac system. A traditional STATCOM consists of
• Energy storage device • AC power system • Voltage source converter (VSC), and a • Control system
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AC/DC/AC
Maximum Energyextraction
Grid integration
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HARMONICS !!!FILTERS
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+
-
Vdc
va_gcc
vb_gcc
vc_gcc
iaRfLf
ib
ic
va
vc
vb
• First-order filter
• Attenuation of 20 dB/decade over the whole frequency range.
• GCC switching frequency must be high in order to sufficiently attenuate the GCC harmonics.
L FILTER
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C
+
-
Vdc
iaRf Lf
ib
ic
va
vc
vb
ia1
ib1
ic1
vca
vcb
vcc
va_gcc
vb_gcc
vc_gcc
• Second-order filter
• 40 dB/decade attenuation
• Better damping behaviors than the L filter
• Suited to configurations in which the load impedance across C is relatively high at and above the switching frequency.
LC FILTER
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C
+
-
Vdc
iaRgLgRinv Linv
ib
ic
va
vc
vb
ia1
ib1
ic1
vca
vcb
vcc
va_gcc
vb_gcc
vc_gcc
LCL FILTER
• 60dB/decade for frequencies above the resonant frequency
• Good current ripple attenuation even with small inductance values
• Lower GCC switching frequency can be used
• Provides better decoupling between the filter and the grid impedance
• Provides lower current ripple across the grid inductor
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25kV 690V
AC/DC DC/DCDC/DC
AC/DC
Controller Controller
AC/DC DC/DC
Controller
AC/DC DC/DC
Controller
AC/DC DC/AC
ControllerAC/DC
DC/ACController
DMS
Energy StorageThe Grid
Solar
WindFuel cell
Microturbine
MGGC
Charging Station for EV
APPLICATION- SMART GRID
The CONTROL
CONVENTIONALCONTROL
DIRECT CURRENT VECTOR CONTROL
NEURAL NETWORKCONTROL
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3/2
3/2
PWM
Voltage angle
calculation
2/3PI
, ,a b cv
, ,a b ci
,v
,i
e
dv
*1dv
*1qv
*1v
*1v
*1, 1, 1a b cv
dv
qv
*di
*qi
*dcV dcV
diqi
R
L
pRC
dcV
L
PI
PI
L
eje
eje
eje
PI*
busV
Bus Voltage Magnitude Calculation
busV*qi
CONVENTIONAL CONTROL
Fast inner Current Loop: Id, IqSlow Outer Voltage Loop: Vdc, bus Voltage, Reactive power
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DIRECT VECTOR CONTROL
3/2
3/2
2/3di
diqi
, ,a b cv
, ,a b ci
R
L
pRC
dcV
PWM
Voltage angle
calculation
,v
e
dv
,i
*1, 1, 1a b cv*
1v*
1v
*1dv
*1qv
R
R
PI
PI
PI
dcV
qi
L
L
*dcV
*qi
*di
eje
eje
eje
PI
*busV
busV*qi
Bus Voltage Magnitude Calculation
• d-axis current for active or dc capacitor voltage control
• q-axis current for reactive power or grid voltage support control
real power or dc link voltage control
reactive power control
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NEURAL NETWORK CONTROL
• Randomly generating a sample initial state idq(j)
• Randomly generating a sample reference dq current
• Training the action network based on the optimization principle
• Repeating the process until a stop criterion is reached.
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0.45 0.5 0.55 0.6 0.65-20
0
20
40
60
q-ax
is c
urre
nt (A
)
Time (sec)
neuralreferenceconventionalDCC
Comparison of Neural Controller with Conventional Standard and DCC Vector Control Methods
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SIMULATION
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GRID
CONVERTER
CONTROLLER
PWM
CONVENTIONAL CONTROL
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V dc ~ 50V
RESULTS
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Id ~ 50V
Iq ~ 50V
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GRID TRANSMISSION LINE CONVERTER
FAULT LOAD CONTROLLER
DIRECT CURRENT VECTOR CONTROL
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V dc ~ 50V
RESULTS
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Id ~ 50V
Iq ~ 50V
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GRIDTRANSMISSION LINE
CONVERTER
FAULT LOAD
CONTROLLER
PWM
NEURAL NETWORK
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V dc ~ 50V
RESULTS
Iq/Id ~ 50V
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DCC Vdc ~ 200kV
NEURAL NETWORK Vdc ~ 200kV
RESULTS at 200kVECE
DCC Iq/Id ~ 200kV
NEURAL NETWORK Iq/Id ~ 200kV
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HARWDARE
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d SPACE UNIT
DISPLAY
SELECTOR
VARIABLE
CONTROL WINDOW
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d SPACE CONTROL DESK
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OPAL RT UNIT
MASTER CONSOLE
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OPAL RT SIMULATOR
RESISTANCE
CONVERTER
ISOLATORS
INDUCTANCE
GRID
D SPACE
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LAB VOLT UNIT
Component Parameter Value
The gridLine voltage and
current 120/208V – 5A
Frequency 60Hz120/208V
transmission Line cable connection
Inductance/phase 0.7Ω, 25mH – 25A dc max
Parallel Resistance/phase 170 Ω
Component Parameter Value
VSC converter
Dc bus 420V – 10Apower 24V, 0.16A 50/60Hz
Switching Control 0/5V, 0-20KHz
Grid-filter Resistance 0.6 ΩInductance 25mH
CapacitorResistance Rp 700 ΩCapacitance 16000 µF
Reference voltage 50V
Approach Controller Gain (kp / ki)
ConventionalCurrent loop 0.895 / 53.073
dc voltage 0.049 / 0.07
DCCCurrent loop 1.363 / 44.49
dc voltage 0.08 / 105
NeuralCurrent loop 0.6815 / 22.245Dc voltage 0.008 / 105
Parameters of D-STATCOM controllerNetwork data
Parameters of individual STATCOM components
Grid Voltage
PARAMETERSECE
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POWER CONVERTER BOARD
INVERTER 2INVERTER 1DC BUS
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PWM FOR CONVERTER BOARD
d SPACESTATCOM
AC/DC/AC&
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MODELGRID VOLTAGE
GRID CURRENT
CONTROLLER
PWM
PROTECTIONDC VOLTAGE
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GUI INTERFACE FOR D SPACEECE
CONVENTIONALV dc ~ 50V
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Id ~ 50V
Iq ~ 50V
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DIRECT CURRENT VECTOR CONTROL
V dc ~ 50V
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Id ~ 50V
Iq ~ 50V
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0 20 40 60 80 100 120 140 160 180 20030
40
50
60
70
Time (sec)
Volta
ge (V
)NEURAL NETWORK CONTROLLER
V dc ~ 50V
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0 20 40 60 80 100 120 140 160 180 200-0.5
0
0.5
1
1.5
Time (sec)
d-ax
is c
urre
nt (A
)
Id Id-ref
0 20 40 60 80 100 120 140 160 180 200-2
-1
0
1
Time (sec)
q-ax
is c
urre
nt (A
)
IqIq-ref
Id ~ 50V
Iq ~ 50V
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d SPACEFILTERS
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MODELGRID VOLTAGE
GRID CURRENT
CONTROLLER
PWM
PROTECTIONDC VOLTAGE
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+
-
Vdc
va_gcc
vb_gcc
vc_gcc
iaRfLf
ib
ic
va
vc
vb
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Vdc ~ 50V
L FILTER
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Iq ~ 50V
Id ~ 50V
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Vgrid ~ 50V
I grid ~ 50V
C
+
-
Vdc
iaRf Lf
ib
ic
va
vc
vb
ia1
ib1
ic1
vca
vcb
vcc
va_gcc
vb_gcc
vc_gcc
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Vdc ~ 50V
LC FILTER
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Iq ~ 50V
Id ~ 50V
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Vgrid ~ 50V
Igrid ~ 50V
C
+
-
Vdc
iaRgLgRinv Linv
ib
ic
va
vc
vb
ia1
ib1
ic1
vca
vcb
vcc
va_gcc
vb_gcc
vc_gcc
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Vdc ~ 50V
LCL FILTER
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Iq ~ 50V
Id ~ 50V
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Vgrid ~ 50V
Igrid ~ 50V
RT LAB
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PWM MAIN CONTROLLER
MEASUREMENTCONTROL
COMMUNICATION
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RT LAB MASTER UNIT
EXTERNAL INPUT
COMMUNICATIONPWM START/STOP SIGNAL
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RT LAB CONSOLE
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RCPWM
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PWM out
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RC EVENTS
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RESULTS
Iq ~ 50V
Vdc ~ 50V
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RANGE Electric
Kenneth J Polk
Lynette Horton
Ishan Jaithwa•Electrical Engineering, MS, University of Alabama
Joshua Stoddard•Mechanical Engineering and STEM path to the MBA, Student at the University of Alabama
Xingang FuElectrical Engineering, Phd, University of Alabama
Dr Shuhui Li -INVENTOR•Associate professor, ECE, University of Alabama
Dr Rachel Frazier•Research Engineer, AIME, University of Alabama
DR Tim A HaskewDepartment Head, ECE, University of Alabama
AD
VISO
RS
MENTORS
Innovation Counsel at American Chemical Society
Financial and Technology Industry Executive
TEAMRANGE Electric
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WHAT DO WE WANT ?
A SELF COMPETING CONTROLLER……..!
EFFICIENT, GOOD BUT SLOW AND PARAMETER DEPENDENT CONTROLLER……!
INTELLIGENT, SELF LEARNING & SUPER FAST CONTROLLER ……………
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Ishan Jaithwa, S Li , X Fu, J Stoddard, “Hardware Experiment Evaluation of STATCOMs using Artificial Neural Networks” (Preparing to submit)
Ishan Jaithwa, J Stoddard, S. Li “Hardware Experiment Evaluation of STATCOMs using Conventional and Direct-Current Vector Control Strategies” (under review).
S. Li, Ishan Jaithwa, R Suftah, X Fu “Direct-Current Vector Control of Three-Phase Grid-Connected Converter with L, LC and LCL Filters” (reviewd and under revision).
S. Li1, X Fu, M Fairbank, Ishan Jaithwa, E Alonso, and D C. Wunsch “Simulation and Hardware Validation for Control of Three-Phase Grid-Connected Microgrids Using Artificial Neural Networks” (under review).
X Fu, S. Li, and Ishan Jaithwa,“ Neural Network Vector Control for Single-Phase PV Grid Converters ,” (Preparing to submit)
PUBLICATIONSECE
REFERENCES[1] N.G. Hingorani, “Flexible AC Transmission Systems”, IEEE Spectrum, Vol. 30, No. 4, 1993, pp. 41-48.[2] A. R. Bergen and V. Vittal, Power System Analysis, 2nd Ed. Upper Saddle River, NJ: Prentice Hall, 2000.[3] E. Acha, C.R. Fuerte-Esquivel, H. Ambriz-Perez, and C. Angeles-Camacho, “FACTS
– Modeling and Simulation in Power Networks,” Chichester, England: John Wiley & Sons Inc., 2004.[4] C. Schauder and H. Mehta, “Vector analysis and control of advanced static VAR compensators,” IEE Proceedings-C, vol. 140, no. 4, pp. 299-306, Jul. 1993.[5] Pablo García-González and Aurelio García-Cerrada, “Control system for a PWM-based STATCOM,” IEEE Trans. on Power Delivery, vol. 15, no. 4, pp. 1252- 1257, Oct. 2000.[6] Pranesh Rao, M. L. Crow, and Zhiping Yang, “STATCOM control for power system voltage control applications,” IEEE Trans. on Power Delivery, vol. 15, no. 4, pp. 1311-1317, Oct. 2000.[7] S. Li, L. Xu, T.A Haskew, “Control of VSC based STATCOM using conventional and
direct current vector control strategies”, International Journal of Electric Power & Energy Systems (Elsevier), Vol. 45, Issue 1, Feb. 2013, pp. 175-186.
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