Low Cost MPPT Algorithms for PV Application: PV
Pumping Case Study
M. A. Elgendy, B. Zahawi and D. J. Atkinson
Presented by:
Bashar Zahawi
E-mail: bashar.zahawi@ncl.ac.uk
NEWCASTLE UNIVERSITY
Power Electronics, Drives and Machines Research Group
31 Jan 2012
Outline
 Maximum power point tracking
 Experimental system description
 Directly Connected PV Pumping Systems
 PV Pumping systems with MPPT
 Constant Voltage MPPT Algorithm
 Perturb and Observe (P&O) MPPT Algorithm
 Incremental Conductance (INC) MPPT Algorithm
 Conclusions
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Introduction
 Water pumping is probably one of the most
important applications of PV systems
 Particularly in rural areas with no grid supply
 Low power pumps ranging from 200W to 2kW
 Most commonly used motor is the PM brushed dc
motor
 Induction motors used for bore-hole and deep-well
pumping
 The dc motor/pump set is connected directly to the
PV array in most commercial systems
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Maximum Power Point Tracking
 A PV array or generator will have one point on its
current/voltage characteristic that corresponds to
maximum power output
 This is referred to as the maximum power point or MPP
 Directly connected systems do not operate at the
MPP
 Significant amounts of available energy are wasted
 A pump controller (dc-dc converter) is required to
better match the PV generator to the motor/pump set
 This is referred to as MPPT
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PV Array Current-Voltage Curves
1000 W/m2
800 W/m2
600 W/m2
400 W/m2
Maximum power line
200 W/m2
PV array current-voltage curves
Mismatch between resistive load and PV Source; current–voltage curves
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PV Array Power-Voltage Curves
PV array current-voltage curves
Load line
Maximum power line
Mismatch between resistive load and PV Source; power–voltage curves
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MPPT Circuit
IPV
PV
generator
S
V PV
VPV IPV
L
CL
IL
C VL
RL
Duty Ratio
DSP, interface, and driver circuits
Circuit diagram for PV system with MPPT control
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MPPT Algorithms
 Mapping or Model Based algorithms
 A model of the system is developed to “map” the operating
characteristics and identify the MPP
 Simple models are not very effective
 More complex models require significant computational
resources and are site specific
 Not suitable for commercial applications
 Constant voltage algorithm
 Hill climbing algorithms
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Hill Climbing MPPT
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Outline of Presentation
 Experimental investigation of the performance of
Maximum power point tracking algorithms for
pumping applications
 Constant Voltage Algorithm
 Perturb and Observe (P&O) Algorithm
 Incremental Conductance (INC) Algorithm
 In each case, system performance is investigated
and the energy utilisation efficiency calculated
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Experimental Set Up
 Experimental investigation of the performance of
Maximum power point tracking algorithms for
pumping applications
 Constant Voltage Algorithm
 Perturb and Observe (P&O) Algorithm
 Incremental Conductance (INC) Algorithm
 In each case, system performance is investigated
and the energy utilisation efficiency calculated
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Experimental Set Up
 1080-Wp PV array facing south at a tilt angle of 54
w.r.t. the horizontal
 Two parallel branches of 3 series connected 180-Wp solar
modules
 Weather station installed at the same roof
 Weather parameters were recorded at a 1 sec sampling rate
 Solar irradiance was measured by a radiation sensor fixed
on a surface inclined at the same tilt angle
 10-stage centrifugal surface pump driven by a
brushed PM dc motor
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Experimental Set Up
 Step-down dc-dc converter
 470F link capacitance and 10kHz PWM frequency
 Texas Instruments DSP based eZdsp kit used for
control and data acquisition
 DSP used to provide flexibility
 In a commercial product, a low cost microcontroller would
be more than adequate
 Array installed on the roof of the New and
Renewable Energy Centre (NaREC) in
Northumberland.
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Experimental System
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Experimental System
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Experimental System
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Experimental System
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Circuit Diagram
ia Ra
iPV
SS
La
PWM
vPV
iPV
DSP Based
vPV
MPPT
CL
470µF
va
II I
1080 Wp Selector Step Down DC-DC
PV Array Switch
Converter
B
eb
J
 Te
TP
Motor-Pump
Set
Equivalent circuit of the PV pumping system setup
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System Description
Mismatch between motor-pump load and PV generator when pump is
connected directly to PV array; current-voltage curves
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System Description
Mismatch between motor-pump load and PV generator when pump is
connected directly to PV array; power-voltage curves
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Directly Connected DC PV pumping system
220
7
200
Array/Motor Current
180
6
5
140
Array/Motor Voltage
120
4
100
3
80
Current (A)
Voltage (V)
160
2
60
2
ψ = 736 W/m , TC = 22.1 ºC
40
1
20
0
0
0
1
2
3
4
5
Time (sec)
Experimental results showing array/motor voltage and current waveforms
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Directly Connected DC PV pumping system
300
60
Flow Rate
250
50
200
40
150
30
ψ = 736 W/m2, TC = 22.1 ºC
100
20
50
10
0
0
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Flow Rate (l/min)
Speed (rad/sec)
Motor Speed
5
Time (sec)
Motor speed and flow rate waveforms
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Directly Connected DC PV pumping system
Influence of solar irradiance and cell temperature on MPP location
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Directly Connected DC PV pumping system
Influence of solar irradiance and cell temperature on the energy utilization
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Directly Connected DC PV pumping system
62.7%
Experimental system performance under slow changing irradiance
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Directly Connected DC PV pumping system
51.3%
Experimental system performance under rapidly changing irradiance
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Outline
• Introduction
• System Description
• Directly Connected PV Pumping Systems
• PV Pumping systems with MPPT
– Constant Voltage MPPT Algorithm
– Perturb and Observe (P&O) MPPT Algorithm
– Incremental Conductance (INC) MPPT Algorithm
• Conclusions
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Constant Voltage MPPT Algorithm
• The system performance is affected by:
– Vref
– KP and KI
Block Diagram of Constant Voltage MPPT Algorithm
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Constant Voltage MPPT Algorithm
Influence of solar irradiance and cell temperature on the energy utilization
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Constant Voltage MPPT Algorithm
ψ=8625W/m2 and TC=28.6˚C
Experimental results showing array voltage, current, and power waveforms
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Constant Voltage MPPT Algorithm
91.3%
Experimental performance at nearly constant irradiance
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Constant Voltage MPPT Algorithm
91.1%
Experimental performance at rapidly changing irradiance
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Conclusions I
 Directly connected PV pumping systems eliminate
the use of power electronics converters but suffer
from low energy utilization efficiency.
 Simple constant voltage MPPT algorithm offers
significantly higher energy utilization efficiencies
(about 91%).
 For more significant improvements in energy
utilization, more efficient MPPT control algorithms
that take into account the effects of insolation and
temperature variations on the MPP voltage would be
required.
NEWCASTLE UNIVERSITY
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Outline
• Introduction
• System Description
• Directly Connected PV Pumping Systems
• PV Pumping systems with MPPT
– Constant Voltage MPPT Algorithm
– Perturb and Observe (P&O) MPPT Algorithm
– Incremental Conductance (INC) MPPT Algorithm
• Conclusions
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Perturb and Observe MPPT Algorithm
Flowchart of P&O MPPT Algorithm
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Perturb and Observe MPPT Algorithm
 Reference voltage control
iPV
vPV
MPPT
Control
vref
iPV
-
+
PI
Controller
PV
System
d
vPV
vPV
Block diagram of MPPT with reference voltage control
 Direct duty ratio control
iPV
iPV
vPV
MPPT
Control
d
PV
System
vPV
Block diagram of MPPT with direct duty ratio control
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Perturb and Observe MPPT Algorithm
 System performance is affected by:
 Step Size (Δd or ΔVref)
 Perturbation Frequency (fMPPT)
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P&O Algorithm Parameters
Voltge (V)
200
160
120
80
=857.1W/m2, Tc=27.9oC
Measured Array Voltage
Calculated MPP Voltage
40
Power (W)
Current (A)
0
8
7
6
5
4
3
2
1
0
1000
Measured Array Current
Calculated MPP Current
800
600
400
Vref =10V, fMPPT=1Hz
Measured Array Power
Calculated Maximum Power
200
0
0
5
10
15
Time (sec)
20
25
30
Three-level operation with reference voltage perturbation
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P&O Algorithm Parameters
1000
D
900
Array Power (W)
800
700
C O A
 =857.1W/m2, Tc=27.9oC
B
600
500
400
300
200
100
0
0
20
40
60
80
100
120
Array Voltage (V)
140
160
180
200
Behavior with reference voltage perturbation in thee-level operation
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200
160
120
80
40
0
8
Current (A)
Voltage (V)
P&O Algorithm Parameters
=946.3W/m2, Tc=43oC
Measured Array Voltage
Calculated MPP Voltage
6
4
Measured Array Current
Calculated MPP Current
2
1000
800
600
400
200
0
100
80
60
40
20
0
0
Measured Array Power
Calculated Maximum Power
Duty Ratio (%)
Power (W)
0
d=5%, fMPPT=1Hz
5
10
15
Time (sec)
Duty Ratio
Optimum Duty Ratio
20
25
30
Three-level operation with direct duty ratio perturbation
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Effect of P&O Algorithm Parameters
200
Voltage (V)
160
120
80
d=2%, fMPPT=1Hz
=973.2W/m2, Tc=42.5oC
Measured Array Voltage
Calculated MPP Voltage
40
0
200
Voltage(V)
160
120
80
d=2%, fMPPT=10Hz
=860.1W/m2, Tc=31.8oC
40
0
0
Measured Array Voltage
Calculated MPP Voltage
5
10
15
Time (sec)
20
25
30
The effect of algorithm parameters on the array voltage; P&O MPPT
algorithm with direct duty ratio perturbation
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P&O Algorithm Parameters
200
Voltage (V)
160
120
80
Vref =2V, fMPPT=1Hz
=760.3W/m2, Tc=26oC
Measured Array Voltage
Calculated MPP Voltage
40
0
200
Voltage (V)
160
120
80
2
o
=938.6W/m , Tc=27.6 C
Vref =2V, fMPPT=10Hz
Measured Array Voltage
Calculated MPP Voltage
40
0
0
5
10
15
Time (sec)
20
25
30
Experimental results showing the effect of algorithm parameters on the
array voltage; P&O MPPT algorithm with reference voltage perturbation
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Array Voltage (V)
P&O Algorithm Parameters
160
140
120
=889.1W/m2, Tc=41.3oC
100
Array Current (A)
8
d=5%, fMPPT=4Hz
6
4
Duty Ratio (%)
2
95
Confusion due to system
dynamics
85
75
Confusion due to branch
disconnection
65
55
0
1
2
3
4
Time (sec)
5
6
7
Experimental results showing the system responses to a PV array
branch disconnection (Δd=5%, fMPPT=4Hz)
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1200
1000
800
600
400
200
0
200
160
120
97.2%
Vref =2V, fMPPT=5Hz
80
40
Array Current (A)
Array Voltage (V)
Solar Irradiance (W/m 2)
Energy Utilization with P&O Algorithm
0
8
7
6
5
4
3
2
1
0
0
200
400
600
Time (sec)
800
1000
1200
Experimental system performance under slow changing irradiance; P&O
algorithm with reference voltage perturbation (ΔV=2V and fMPPT=5Hz)
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1200
1000
800
600
400
200
0
200
Array Voltage (V)
Solar Irradiance (W/m 2)
Energy Utilization with P&O Algorithm
160
120
80
97%
Vref =5V, fMPPT=5Hz
40
Array Current (A)
0
10
5
0
0
200
400
600
Time (sec)
800
1000
1200
Experimental system performance under rapidly changing irradiance;
P&O algorithm with reference voltage perturbation
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1200
1000
800
600
400
200
0
200
Array Voltage (V)
Solar Irradiance (W/m 2)
Energy Utilization with P&O Algorithm
150
100
50
170
99%
160
150
200
400
600
800
1000
Array Current (A)
0
8
6
4
d=2%, fMPPT=10Hz
2
0
0
200
400
600
Time (sec)
800
1000
1200
Experimental system performance under slow changing irradiance;
direct duty ratio perturbation
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1200
1000
800
600
400
200
0
200
Array Voltage (V)
Solar Irradiance (W/m 2)
Energy Utilization with P&O Algorithm
150
100
97.9%
d=2%, fMPPT=10Hz
50
Array Current (A)
0
8
6
4
2
0
0
200
400
600
Time (sec)
800
1000
1200
Experimental system performance under rapidly changing irradiance;
direct duty ratio perturbation
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Conclusions II
 The P&O MPPT algorithm is a simple algorithm that
does not require previous knowledge of the PV
generator characteristics or the measurement of
solar intensity and cell temperature.
 Two approaches for implementing the P&O
algorithm have been investigated; reference voltage
perturbation and direct duty ratio perturbation.
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Conclusions II
 With reference voltage perturbation, the system has a faster
transient response to irradiance and temperature
transients.
 However, stability is lost if the MPPT algorithm is operated at
high perturbation rates or if low pass filters are used to reject
noise from the array current and voltage feedback signals.
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Conclusions II
• Direct duty ratio control offers better stability characteristics
and higher energy utilization efficiency at a slower transient
response and worse performance at rapidly changing
irradiance.
• Noise has significant impact on the algorithm
performance, especially with low step sizes where
the system response to noise is comparable to that
of MPPT perturbations.
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Outline
• Introduction
• System Description
• Directly Connected PV Pumping Systems
• PV Pumping systems with MPPT
– Constant Voltage MPPT Algorithm
– Perturb and Observe (P&O) MPPT Algorithm
– Incremental Conductance (INC) MPPT Algorithm
• Conclusions
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Incremental Conductance MPPT Algorithm
1000
1000 W/m2, 60C
Power (W)
800
600
dP
0
dV
dP
0
dV
400
dP
0
dV
200
0
0
50
100
150
200
250
300
Voltage (V)
Power-Voltage Curve of a PV Generator
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Incremental Conductance MPPT Algorithm
1000
1000 W/m2, 60C
Power (W)
800
600
dIdP
I
0
dVdV V
dI dP I

0
dVdV V
400
dI
I
dP
 
0
dV
dV
V
200
0
0
50
100
150
200
250
300
Voltage (V)
Power-Voltage Curve of a PV Generator
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Incremental Conductance MPPT Algorithm
 Reference voltage for the array output voltage
iPV
vPV
MPPT
Control
vref
iPV
-
+
PI
Controller
PV
System
d
vPV
vPV
Block diagram of MPPT with reference voltage control
 Converter duty ratio
iPV
iPV
vPV
MPPT
Control
d
PV
System
vPV
Block diagram of MPPT with direct duty ratio control
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Incremental Conductance MPPT Algorithm
 The system performance is affected by:
 Step Size (Δd or ΔVref)
 Perturbation Frequency (fMPPT)
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INC Algorithm Parameters
Three-level operation with reference voltage perturbation
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INC Algorithm Parameters
Three-level operation with direct duty ratio perturbation
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INC Algorithm Parameters
The effect of algorithm parameters on the array voltage; INC MPPT
algorithm with direct duty ratio perturbation
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INC Algorithm Parameters
The effect of algorithm parameters on the array voltage; INC MPPT
algorithm with reference voltage perturbation
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INC Algorithm Parameters
The effect of noise on the decision of the INC algorithm; reference
voltage perturbation
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INC Algorithm Parameters
Experimental results showing the system responses to a PV array
branch disconnection (Δd=2%, fMPPT=10Hz)
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Energy Utilization with INC Algorithm
ΔVref=5V and fMPPT=5Hz
97.6%
Experimental system performance under slow changing irradiance;
reference voltage perturbation (ΔV=2V and fMPPT=5Hz)
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Energy Utilization with INC Algorithm
ΔVref=5V and fMPPT=5Hz
94.9%
Experimental system performance under rapidly changing irradiance;
reference voltage perturbation
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Energy Utilization with INC Algorithm
Δd=2% and fMPPT=10Hz
98.5%
Experimental system performance under slow changing irradiance;
direct duty ratio perturbation
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Energy Utilization with INC Algorithm
Δd=2% and fMPPT=10Hz
96.8%
Experimental system performance under rapidly changing irradiance;
direct duty ratio perturbation
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Conclusions III
 The INC algorithm is less confused by noise and system
dynamics compared to the P&O algorithm. However, contrary
to general perceptions, it was found to exhibit worse confusion
than the P&O algorithm in rapidly changing weather
conditions.
 Both algorithms offer high energy utilization
efficiencies of up to 99% depending on weather
conditions. The efficiency is marginally lower for
rapidly changing irradiance due to the energy loss
during the confusion and recovery periods.
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More Details
 M. A. Elgendy, B. Zahawi and D. J. Atkinson,
“Comparison of Directly Connected and Constant
Voltage Controlled Photovoltaic Pumping Systems,”
IEEE Transactions on Sustainable Energy, Vol. 1, No.
3, pp. 184-192, Oct. 2010
 M. A. Elgendy, B. Zahawi and D. J. Atkinson,
“Assessment of Perturb and Observe MPPT
Algorithm Implementation Techniques for PV
Pumping Applications,” IEEE Transactions on
Sustainable Energy, Vol. 3, No. 1, pp. 21-33, Jan. 2012
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Thank you
Bashar Zahawi
E-mail: bashar.zahawi@ncl.ac.uk
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