Eugene Gargas_MPPT Presentation

7/28/2019 Eugene Gargas_MPPT Presentation

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Solar MPPTTechniques

Geno Gargas

ECE 548Prof. Khaligh


2/20

Purpose of Presentation

I. Provide general description of solarMPPT techniques

II. Describe design of solar MPPTMATLAB model constructed

III. Present results of MATLAB simulation

IV. Give analysis of results withrecommendation for future work


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I Basics of MPPT

Solar panel characteristic has non-linear relationship

with Temperature and Irradiance

MPP also moves non-linearly

MPPT can improve efficiency by 15-20%


4/20

Common MPPT methods

Cheap and Easy Implementation

Fractional Open-Circuit Voltage

Fractional Short-Circuit Current

Intermediate Price and Implementation

Perturb and Observe

Incremental Conductance

Expensive and Difficult Implementation

Fuzzy Logic Control

Neural Networks

Increase

dEfficienc

yC

heaperandEasier


5/20

Basic Perturb and Observe

Implemented through a DC/DC converter

Logic

1. Change duty cycle

2. Observeconsequences on

power output

3. Decide direction of

next change in dutycycle


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P & O Design Parameters

Balance d between size of the oscillationacross MPP, and inability to not get confused

Two degrees of freedom: d and Ta

Ta Constraints d

where


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II Creation of MATLAB model

Boost converter with a typical 12V, 64W solarpanel, using the P&O algorithm for MPPT

3 Subsystems

1. Solar Panel

2. Boost

Converter

3. MPPT controller


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1 - PV model design

Vout -

2

Vout +

1

ih

Vpv

v+

-

Rs

Rh

Photocurrent 1

s

-+

Photocurrent

s -

+

Ipv control

Vpv

Ipv

Ih

Temp

Ipv s

Ipv

i+ -

Ih control

Temp

Suns

Ih s

Ih

i+ -

Diode

Suns

2

Temp

1

Important equationsEquivalent

Circuit

MATLAB

Model

I/P -> Sun and

Temperature

O/P -> Panel

voltage

Uses controlled

current sources


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PV model simulation

0 5 10 15 200

0.5

1

1.5

2

2.5

3

3.5

4

4.5

Panel Voltage (V)

PanelCurrent(A)

I-V characteristics for varying irradiance conditions

S = 300 W/m2

S = 500 W/m2

S = 800 W/m2

S = 1000 W/m2

0 5 10 15 200

10

20

30

40

50

60

Panel Voltage (V)

PanelPower(W)

P-V characteristics for varying irradiance conditions

S = 300 W/m2

S = 500 W/m2

S = 800 W/m2

S = 1000 W/m2

I-V and P-V characteristics of simulated PV model

with various levels of irradiance

Very similar to characteristics of real solar panels


10/20

2 Boost converter design

Load

Cin

Vin -2

Vin +

1

triangle

Relational

Operator


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Boost model simulation

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.160

0.5

1

1.5

2

2.5

3

3.5

time (s)

PVcurrent(A)

Panel current at various Duty cycles in Boost converter

D = .1

D = .2

D = .3

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.1612

13

14

15

16

17

18

19

20

time (s)

PVvoltage(V)

Panel voltage at various Duty cycles in Boost converter

D = .1

D = .2

D = .3

Voltage and current of input vs. time for various duty

cycles

Quick transient decay

Low ripple

Input source is model of solar panel


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3 MPPT controller

Timing Sequence

1. Sample new values

after transient

decays

2. Sample for directionof new d

3. Sample values for

use in next period

4. Make change in d

Logic

1. Get Power and Duty values ofK and K+1 periods

2. Figure out direction of

change in duty cycle

3. Change duty cycle

4. Repeat


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Model of controller

Dire

2

Dout

1

direction

In S/H

1

delta D

.1

Memory

OR

AND

NOT

ANDNOT

NOT

NOT AND

OR

AND

D

-1

K

3

P comp

2

D comp

1

Given values from comparing Pk+1 and Pk and Dk+1

and Dk

Performs logic and outputs new duty cycle


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III - Simulation

Test the system during three types of irradiance

1. Fast Changing (50 W/m2s)

2. Slow Changing (15 W/m2s)

3. No Change (0 W/m2s)

Test with different d

1. Large d (d = .02)

2. Small d (d = .005)

0 0.2 0.4 0.6 0.8 1 1.20.89

0.9

0.91

0.92

0.93

0.94

0.95

0.96

time (s)

Irradia

nce(W/m2)

Fast changing irradiance

0 0.2 0.4 0.6 0.8 1 1.20.89

0.9

0.91

0.92

0.93

0.94

0.95

time (s)

Irradiance(W/m2)

Slow changing Irradiance


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Fast Changing Irradiance

0 0.2 0.4 0.6 0.8 1 1.240

42

44

46

48

50

52

54

56

time (s)

Power(W)

Power with D=.02 and fast changing irradiance

0 0.2 0.4 0.6 0.8 1 1.20.3

0.31

0.32

0.33

0.34

0.35

0.36

0.37

0.38

0.39

time (s)

d

utycycle

Duty cycle with D=.02 and fast changing irradiance

(d = .02)

0 0.2 0.4 0.6 0.8 1 1.240

42

44

46

48

50

52

54

56

time (s)

Power(W)

Power with D=.005 and fast changing irradiance

0 0.2 0.4 0.6 0.8 1 1.20.31

0.315

0.32

0.325

0.33

0.335

0.34

0.345

0.35

0.355

0.36

time (s)

dutycycle

Duty cycle with D=.005 and fast c hanging irradiance

(d = .005)

PV

power

Duty

Cycle


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Slow Changing Irradiance

(d = .02) (d = .005)

PV

power

Duty

Cycle

0 0.2 0.4 0.6 0.8 1 1.20.31

0.32

0.33

0.34

0.35

0.36

0.37

0.38

0.39

time (s)

dutycycle

Duty cycle with D=.02 and sl ow changing irradiance

0 0.2 0.4 0.6 0.8 1 1.245

46

47

48

49

50

51

time (s)

Power(W)

Power with D=.005 and sl ow changing irradiance

0 0.2 0.4 0.6 0.8 1 1.20.31

0.315

0.32

0.325

0.33

0.335

0.34

0.345

0.35

0.355

0.36

time (s)

dutycycle

Duty cycl e with D=.005 and slow changing irradiance

0 0.2 0.4 0.6 0.8 1 1.245

46

47

48

49

50

51

time (s)

Power(W)

Power with D=.02 and slow changing irradiance


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No Change in Irradiance

(d = .02) (d = .005)

PV

pow

er

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.545

46

47

48

49

50

51

52

53

time (s)

Power(W)

Power at constant irradiance and D=.02

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 0.45 0.5

45

46

47

48

49

50

51

52

53

time (s)

Power(W)

Power at constant irradiance and D=.005


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IV - Results

d Fast change in S Slow change in S No change in S

.02 48.68 W 47.95 W 47.2 W

.005 48.87 W 48.14 W 48.05 W

Average Power in each simulation

These results were found using the mean statistical data providedby MATLAB in each simulation

Average Maximum power available from solar panel

Fast change in S Slow change in S No change in S

Max Power 49.22 W 48.44 W 48.1 W

These results were found by simulating the panel at the average

insolation for each form of change in irradiation, and finding the

maximum point on the power curve.


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Analysis

d Fast change P Slow change P No change P

.02 98.9 % 99 % 98.1%

.005 99.3 % 99.4 % 99.9%

Efficiency of MPPT algorithm for various parameters

Higher efficiency with small d, regardless of how the sun is

changing

I observed that the smaller d takes much longer to get to the

MPP from a step change in irradiance

The step change is a very rare occurrence, so this may not be

an issue

Design the system for the smallest d possible for the best

efficiency


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Future Work

Design a controller that can vary the size of theperturbation with respect to how far from theMPP it is

Leave d at a small value and adjust the

sampling time to see if that has any effect. Simulate the MPPT controller for other

converter types, possibly in line with a batterycharge controller

Eugene Gargas_MPPT Presentation

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