Université de Tunis El Manar

Electrical Engineering Department

Maximum Power Point Tracking:

Algorithm and Software

Development

Author :

Hamza Arif

Classe :3AGE1

Company

Année universitaire 2013/2014

Acknowledgements

This thesis has been conducted at the Research & Development Department of the company

S.&A.S. Ltd located in Jieh in Lebanon.

I would like to acknowledge all the people and institutions that have contributed directly and

indirectly in this work.

First of all, I would like to express my gratitude to Mr Ziad Boustany who gave me the chance

to be part of a wonderful team of employees for almost two months and my supervisor Nazira

Nehem Rassi who supported me along the internship duration it would have not been possible

to complete this work without their invaluable guidance, advice and support. I have learnt a

lot from them during the realization of this thesis.

I am also grateful to my colleagues.They have provided me some valuable information for my

work and have contributed to the good atmosphere in the office we have been working

together.

I would like finally to express thanks to both my home university the National Engineering

School of Tunis and the American University of Beirut for giving me the opportunity of being

an IAESTE exchange .

Abstract

This work done in the research & development department of S.&A.S. Ltd presents a

theoretical study of maximum power point tracking (MPPT) for photovoltaic (PV) system and

a practical implementation of two chosen algorithms on a digital signal processor after a

simulation on MATLAB . A first study includes discussion of various MPPT algorithms and

perform comparative tests of the two popular MPPT algorithms (the Perturbation and

Observation algorithm and the Incremental and Conductance algorithm) after a presentation

of the hardware that will be use and the application that this work is destined for.

RésuméCe travail fait dans le département Recherche & Développement de S. &A.S. Ltd présente une

étude théorique de suivi du point de puissance maximale (MPPT) pour les systèmes

photovoltaïques (PV) et une mise en œuvre pratique de deux algorithmes choisis sur un

processeur de signal numérique après une simulation sur MATLAB. Une première étude

comprend des discussions sur les divers algorithmes MPPT et une réalisation des essais

comparatifs des deux algorithmes MPPT populaires (l'algorithme de perturbation et

d'observation et l'algorithme incrémental et de la conductance) suivi une présentation du

matériel qui sera utilisé et l'application que ce travail est destiné pour.

iv

Contents

List of figures v

General Introduction vii

1 Company Profile and design of the MPPT 8

1.1 Company Profile.............................................................................................................. 8

1.1.1 Presentation ........................................................................................................... 8

1.1.2 Products ................................................................................................................. 9

1.1.2.1 Rescue HP............................................................................................. 10

1.1.2.2 Solar Wind Energy Monitor – SWEM v1.0 + SWEM-D1 v1.0 ......... 11

1.1.2.3 AUTO START MODULE SMART-AST........................................... 12

1.2 Design of the MPPT ...................................................................................................... 13

1.2.1 State of Art of the MPPT..................................................................................... 13

1.2.1.1 Solar Panel ............................................................................................ 14

1.2.1.2 DC-DC converter.................................................................................. 16

1.2.1.3 MPPT Controller .. ............................................................................... 17

1.3 Process of the design ..................................................................................................... 17

2 Simulation and Software Design 18

2.1 MPPT Algorithms ......................................................................................................... 18

2.1.1 Hill-Climbing Alogorithms ................................................................................ 18

2.1.1.1 Perturb & Observe ................................................................................ 19

2.1.1.2 IncCond Algorithm............................................................................... 20

2.2 Simulation of the P&O Algorithms ............................................................................... 21

2.3 Design of the C Software............................................................................................... 23

Conclusion 24

Bibliography 25

Apprendix 27

v

List of figure

Figure 1 S.&A.S. Ltd Headquarters ........................................................................................................ 8Figure 2 S.&A.S Ltd Commercial Brand ................................................................................................ 9Figure 3 RescueHP Board ..................................................................................................................... 10Figure 4 Solar Wind Energy Monitor – SWEM v1.0 + SWEM-D1 v1.0 ............................................. 11Figure 5 Smart AST .............................................................................................................................. 12Figure 6 MPPT block scheme ............................................................................................................... 14Figure 8 The i-v and p-v characteristic of a solar panel ........................................................................ 15Figure 7 Equivalent Model of a solar Panel .......................................................................................... 15Figure 9 Boost Converter Topology...................................................................................................... 16Figure 10 Flowchart of the P&O algorithm .......................................................................................... 19Figure 11 Flowchart of the InCond algorithm....................................................................................... 21Figure 12 Simulation of the different parameters in P&O Algorithm................................................... 22

vi

General Introduction

Solar panels have a nonlinear voltage-current characteristic, with a distinct maximum power

point (MPP), which depends on the environmental factors, such as temperature and

irradiation. In order to continuously harvest maximum power from he solar panels, they have

to operate at their MPP despite the inevitable changes in the environment. This is why the

controllers of all solar power electronic converters employ some method for maximum power

point tracking (MPPT). Over the past decades many MPPT techniques have been published.

The first objective of this work is to study and analyze them. The two algorithms that where

found most suitable for large and medium size photovoltaic (PV) applications are perturb and

observe (P&O) and incremental conductance (InCond) .These were compared , The first

algorithm was simulated in MATLAB and the second was chosen to be developed in C

language in order to implement it and to be to run on a TMS320F2406 Texas Instrument

Digital Signal Processor (DSP).

We proposed some modifications to the P&O and the InCond algorithms are proposed, which

overcome their poor performance when the irradiation changes continuously.

The dynamic MPPT efficiency tests require long simulations and if detailed models of the

power converter are used they can take a lot of memory and computation time. To overcome

this challenge a simplified model of the PV system was developed. This model was validated

with simulations on MATLAB .

vii

1.

2.

3.

4.

5.

6.

7.

8

Chapter 1

Company Profile and Design of the

MPPT

1.1 Company Profile

1.1.1 Presentation

Founded in 1990, S. & A.S. Co. Ltd has developed a leading name for itself in the field of

industrial electronic controls through continuous introduction of new products that are of

extremely high quality and completely reliable. Extra attention is paid to the look, ease of

Figure 1 S.&A.S. Ltd Headquarters

9

manipulation and installation of the product. The products of the company agrees with a

raisonable budget and yet are still of the utmost quality and innovation.

The product range includes: control relays, diesel generating sets controllers, elevator

controllers and VVVF drives for elevators.

S. & A.S. Co. Ltd is based in Jieh, a beautiful seaside village located 24km south of Beirut.

The Jieh location is a 100sqm building that serves as our headquarter offices and

production facility. S. & A.S. also has an office in Beirut that supports the local

distribution of our products.

Figure 2 S.&A.S Ltd Commercial Brand

The company is certified " Eco -Friendly " since April 2011. it is also an innovative

enterprise: engineers working on new electronic cards and always trying to optimize in

order to make the best circuits they can design.

Fortunately, the solutions exist when for example as a response to the lack of electricity the

company owns two large groups generators . As the company develops Electronic

controllers a part of the electrical energy production is self assured. . In addition, the

engineers are provide electronic maintenance of those two generators and other different

machines.

1.1.2 Products

10

In this part , we’ll expose some of the products that S.&A.S have worked on and we’ll

focus firstly on the device containing the DSP in concern about the implementation of the

MPPT algorithms then we’ll expose the solar wind energy monitor and finally I’ll expose

one of the most recent products of S.&A.S. that I had the opportunity to attend a seminar

about during my internship.

1.1.2.1 RescueHP :

The Rescue v1.3 device is a versatile and simple yet very effective elevator evacuation

system controller. It comprises a single-phase sine wave inverter, a three-phase space

vector modulated inverter and a state of the art battery charger that automatically switches

between four operating modes depending of the battery charge level. The switching

frequency of the inverters is 10KHz. The switching frequency of the charger is 20KHz.

The four operating modes of the charger are: trickle (for depleted batteries), bulk (for

discharged batteries), float (overcharging) and full (for maintaining battery charge). Ease

of installation, adjustment and operation in addition to excellent performance and

reliability are the strong points of this controller.

FEATURES

Figure 3 RescueHP Board

11

• Controlled by a Digital Signal Processor.

• Pure sine-wave on single phase inverter.

• Space vector modulation on three phase inverter.

• Charger Modes: trickle, bulk, float or full

• Fault messages describing common faults.

• Displayed parameters: battery voltage, battery charge current, single phase inverter

current, three phase inverter current.

• Separate diagnostic tool with a 24 character, 2 lines liquid crystal display.

• All terminals are individually labeled according to function to facilitate identification.

• RS-485 port ready for communicating with a diagnostic tool or a PC.

1.1.2.2 Solar Wind Energy Monitor – SWEM v1.0 + SWEM-D1v1.0 :

3-Digit numeric display for voltage, current, produced and consumed energy

• Digital presettable thresholds for voltage, current and delays

• Three push buttons for selecting display measurement and accessing the menu

• Colored leds to indicate battery status

• SWEM-D1 display module used for remote monitoring of the power and energy

Figure 4 Solar Wind Energy Monitor – SWEM v1.0 +SWEM-D1 v1.0

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• Wiring through plug in connector

• Case conforms to DIN 43 880 of the British Standard

• Fits onto 35mm symmetric DIN rail to BS5584 (EN 50 022, DIN 46277-3)

• Humidity class, DIN 40040

• Environmental protection, DIN 40 050

1.1.2.3 AUTO START MODULE – SMART-AST

• Microcontroller based design Operation by 3 push buttons

• Easy to fit DIN standard 72x72 panel mount housing

• Connection is via locking plug and socket connectors

• Solid-state short circuit protected outputs

• Front panel leds for status and alarm indication

Figure 5 Smart AST

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• Automatic engine starting and stopping

• Automatic shutdown on fault condition

• Low oil pressure alarm and shut down

• High engine temperature alarm and shut down

• Dynamo fail alarm and shut down

• Low fuel alarm and shut down

• Over / Under speed alarm and shut down

• Coolant level alarm and shut down

• Optional handheld tool to access all timers, set points and parameters

DESCRIPTION

SMART series is an intelligent auto start and protection module. Automatic assembly and

microcontroller based high integration design resulted in this low-cost yet high

performance controller.

1.2 Design of the MPPT

In order to successfully design a controller for an MPPT, we must get a clear picture of the

general lay-out of an MPPT and have some general knowledge of his subsystems.

Subsequently, we cover the controller of the MPPT in more depth and we discuss the

design process, we used for designing our MPPT controller .

1.2.1 State of the Art of the MPPT

14

Figure 6 MPPT block scheme

Figure 6 depicts a block diagram of a system consisting of a load powered by a solar panel

equipped with an MPPT. There are four blocks in this scheme: a solar panel, a DC-DC

power converter, an MPPT controller and a load. In our case, the solar panel will be the

solar panels of S.&A.S. The DC-DC Power Converter transforms the voltage of the solar

panels to the desired voltage of the batteries. It also determines the operating point of the

solar panels. In the following subsections, we will

elucidate these subsystems.

1.2.1.1 Solar Panel

As can be seen from the model of a solar panel depicted in figure 7, the internal

impedance consists mainly of a diode. Because the internal impedance deter- mines

the ideal operating point and the diode is a non-linear circuit element, the i-v

characteristic of a solar panel is non-linear. The i-v characteristic of a typical solar panel

is shown in figure 8 by the dotted line. The resulting p-v characteristic is depicted by

the green line. As can be seen from the figure, the p-v characteristic has a maximum at a

certain voltage. This voltage is known as the Maximum Power Point (MPP).

15

The MPP of a solar panel is dependent on several factors, namely the amount of

irradiance, the temperature and the shading of the panel. All these factors have an

impact on the location of the MPP. Therefore, the MPP of a solar panel is constantly

changing and an MPPT is needed to obtain the maximum power output.

Figure 8 The i-v and p-v characteristic of a solar panel

Figure 7 Equivalent Model of a solar Panel

16

1.2.1.2 DC-DC ConverterThe DC-DC converter converts the input DC voltage to another DC voltage. The

converter used is a boost converter, as the voltage required to charge the batteries

is higher than the output voltage of the solar panel. Figure 8 shows the schematic

of the boost converter. The three main components are the inductor, the

MOSFET switching device and the diode. When the switch is open, the current

from the source charges the inductor. When the switch is closed, the energy stored

in the inductor adds to the source and thus increases the output voltage. The duty

cycle of a PWM signal determines the ratio between the input and output voltage.

In case of an ideal switching device and when losses are neglected, the ratio between

Vin and Vout can be calculated with formula presented below In this formula, D

represents the duty cycle of the PWM signal and has an value between 0 and 1. As can

be seen in formula presented below, Vout increases as the duty cycle increases. We

shall use this property to adjust the operating point of the MPPT.

Vout =1

Vin 1 ­D

Figure 9 Boost Converter Topology

17

1.2.1.3 MPPT Controller :

The MPPT controller executes the algorithm to find the MPP. The input of

the controller is the measured output voltage and current of the solar panel.

This value is not the actual value of the output voltage and current, but the

actual value has been converted to a value between 0 and 5 V. Based on these

inputs, the algorithm performs its calculations. The output of the controller is

the adjusted duty cycle of the PWM, which drives the DC-DC converter’s

switching device. A different duty cycle causes a different operating point. In

addition to these calculations, the controller also has to send the measured

output voltage and current to the system. These values are used to track how

much energy is generated and to spot any failures or errors in the system.

1.3 Process of the design :We divided the process of the design of our MPPT into three parts. At first,

we subdivided the system into two main parts, the hardware and the software

part. As I was responsible for the software part, subsequently, we did a literature

survey to find out which algorithms were available to track the MPP and what the

advantage and disadvantage of each respective algorithm was. Then, we

simulated the one of the algorithms in order to visualize under MATLAB &

Simulink environnement the efficiency of the Controller .After this I designed the C

software of another one so I finish by understanding both algorithms and have a

pratical view on them.

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Chapter 2

Simulation and Software Design

2.1 MPPT Algorithms :

As was previously explained, MPPT algorithms are necessary in PV applications because

the MPP of a solar panel varies with the irradiation and temperature, so the use of MPPT

algorithms is required in order to obtain the maximum power from a solar array.Over the

past decades many methods to find the MPP have been developed and published. These

techniques differ in many aspects such as required sensors, complexity, cost, range of

effectiveness, convergence speed, correct tracking when irradiation and/or temperature

change, hardware needed for the implementation or popularity, among others. A complete

review of 19 different MPPT algorithms can be found in . Among these techniques, the

P&O and the InCond algorithms are the most common. These techniques have the

advantage of an easy implementation but they also have drawbacks, as will be shown later.

Other techniques based on different principles are fuzzy logic control, neural network,

fractional open circuit voltage or short circuit current, current sweep, etc. Most of these

methods yield a local maximum and some, like the fractional open circuit voltage or short

circuit current, give an approximated MPP, not the exact one. In normal conditions the V-P

curve has only one maximum, so it is not a problem. However, if the PV array is partially

shaded, there are multiple maxima in these curves. In order to relieve this problem, some

19

algorithms have been implemented as in . In the next section the most popular MPPT

techniques are discussed

2.1.1 Hill Climbing Algorithms :The most common types of algorithms are Hill Climbing algorithms. Hill Climbing means

that the algorithm takes steps over the p-v characteristic to find the MPP. Of this type, there

are three algorithms which are very common, Perturb & Observe and Incremental

Conductance.

2.1.1.1 Perturb & Observe :The most widely used algorithm is the Perturb & Observe (P&O) algorithm.The P&O

algorithm perturbs the duty cycle which controls the power converter,in this way it takes

steps over the p-v characteristic to find the MPP .This perturbation causes a new operating

point with a different output power.In case this output power is larger than the previous

output power, this point is set as the new operating point. In case it is lower, the same

power point is adjusted to a lower or higher working voltage, depending on the previous

step direction.

Figure 10 Flowchart of the P&O algorithm

20

2.1.1.2 Incremental Conductance :Incremental Conductance (InCond) is a more elaborate version of the dP/ dV

algorithm. Because the power equals V*I, the derivative of power with respect to

voltage equals

dP dI dV= V + I

dV dV dVdI

= V + IdV

Combining 4.3 with the set of equations given in 4.2, the following set of rules is

found:dI IdV = −V at MPPdI IdV > −V left of MPPdI IdV < −V right of MPP

With the help of these equations, the next operating point is chosen. A flowchart of

the InCond algorithm is found in figure 11.

A PI controller is an effective way of implementing the InCond algorithm . As an

input for this controller, an error signal is constructed.

The PI controller makes this error signal go to zero, which means the operating point

is at the MPP. The efficiency of this algorithm is higher than P&O that’s why we

have chosen it for the implementation on the hardware.

21

Figure 11 Flowchart of the InCond algorithm

2.2 Simulation of the P&O Algorithm on MATLABSimulink :

In this section, first, we discuss the ideal model which our simulation model is based

upon ( figure 12 ).

For the simulation, a model with a solar panel and a boost converter is used.

22

In our model, it is easy to calculate the ideal maximum power output, which is necessary

for the calculation of the efficiency.

The model of the MPPT algorithm is embedded in a triggered subsystem.

The efficiencies of the different algorithms are calculated as follows:

Pactη =Pmax

∗ 100%

Figure 12 Simulation of the different parameters in P&O Algorithm

23

2.3 Design of the C Software :The algorithm that we design its C software is effectively equivalent to that presented above

in figure 11 : the InCond Algorithm, yet differs in some points .

There are two notable differences between the algorithm we actually implemented and the

theoretical incremental conductance algorithm presented above :

1 . We will not test the absence of variation of the voltage across the panel. Indeed, for

dVpannel > 0 , test variations in the intensity or the relative position of conductance is

equivalent , as we can see in the following cases:

2 . Introduction of a margin of error between G and δG. ( G is the conductance )

Indeed, perfect equality ( that search algorithm ) between these two values is almost

impossible to find , so a margin of error is introduced . Instead of testing for equality , the

algorithm checks if the values are not spaced less than 1%.

We’ll present now the different functions we used in our C code :

- Void incduty () : function responsible of the increasing of the duty cycle

- Void decduty() : function responsible of the decreasing of the duty cycle

- The PWM initialization function and the ADC functions are already implemented on

the target for previous applications

- Void testcurrent(); and void testconductance () :two functions principally including

two if loops that allows to take the decision of activating the two functions of

incduty() or decduty() depending on the conditions we explained below in the

flowchart of the IncCond algorithm.

- The main program is an exact translation to C language from the flowchart explained

below taking in consideration the two modifications we proposed .

24

Conclusion

The aim of this internship was to implement an MPPT algorithm in a controller and to

implement the most efficient algorithm that works in fast changing levels of irradiance and

when the solar panels are partially shaded. Also, the efficency of the algorithm had to be as

high as possible, as the MPPT had to have an efficiency of at least 95%, and the

implementation complexity of the algorithm could not be be too high, in order to fit within

the time constraints of the project.

We succeeded in simulating one of the algorithms and designing the other one . Due to time

constraints, we chose to focus on the P&O algorithm for the simulation and the InCond

algorithm for the designing. .We had no time to make a test on a real solar panel, so we

can not make any conclusions about the performance in reality of the different algorithms

implemented in this case.

We have to mention indeed that we had to test to the different work done with the algorithms

on real solar panel and we had to think on a design that allows us to get the power to the

utility and also there are more advanced and efficient tracking algorithms available than

the hill climbing algorithms, especially in the case of fast changing levels of irradiance

and when the solar panels are partially shaded. Simulating and im- plementing these

algorithms is expected to deliver a higher MPPT algorithm efficiency.

25

Bibliography

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[9] T. Kawamura et al. Analysis of mppt characteristics in photovoltaic power system. SolarEnergy Materials and Solar Cells, 47:47–62, 1997.

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Apprendix

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