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Maximum power point tracker (MPPT) based photovoltaic (PV) water pumping system using AC and DC motors

Master's Thesis 2014 114 Pages

Engineering - Power Engineering

Excerpt

Table of Contents

Abstract

Chapter 1: Introduction

1.1 Objective
1.2 Scope
1.3 Methodology
1.4 Problem Statement
1.5 Back ground
1.6 Proposed System
1.6.1 AC Motor-Pump load
1.6.2 DC Motor-Pump load
1.7 Outline of the Thesis

Chapter 2: Photovoltaic System Modeling
2.1 Introduction
2.2 PV Module Modeling
2.2.1 Simulation by MATLAB
2.2.2 Effect of irradiance
2.2.3 Effect of Temperature
2.2.4 The I-V Characteristics Curve and Maximum PowerPoint (MPP)

Chapter 3: Maximum Power Point Tracking Algorithms
3.1 Introduction
3.2 Perturbation and Observation (P&0) Algorithm
3.3 Incremental and Conductance (IncCond) Algorithm
3.4 Parasitic Capacitance
3.5 Current Control MPPT
3.6 Voltage Control MPPT
3.7 Control of MPPT System
3.8 Comparative Test of (P&O) and IncCond Algorithm
3.9 Simulation Results and Discussion
3.10 Performance and Simulation of MPPT with Resistive load
3.11 Output Sensing Control Technique
3.12 Limitation of Maximum Power Point Tracker (MPPT)
3.13 Simulated System
3.14 System with MPPT vs. Direct Coupled System

Chapter 4: MPPT for PV Water Pumping System
4.1 PV Pumping System
4.2 System Configurations of Pumping System
4.3 Power Conditioner Stage
4.4 AC Motor Using for pumping System
4.4.1 General Descriptions
4.4.1.1 Induction Motor
4.4.1.2 Inverter
4.4.1.3 DC-DC Converter
4.4.1.4 Pump
4.4.2 Control Method
4.4.2.1 Plus-Width Modulation
4.4.2.2 Maximum Power Point Tracker (MPPT)
4.4.3 Steady-State Performance of a PV Pumping System using AC Motor-Pump
4.4.3.1 Induction Motor-Pump
4.4.3.2 DC-AC Inverter
4.4.3.3 PV Generator (PVG)
4.4.3.4 Simulation Results and Discussion
4.5 DC Motor Using for PV Pumping System
4.5.1 I-V Characteristics of DC Motor
4.5.2 Steady-State Performance of PV Pumping System using DC Motor
4.5.2.1 MATLAB Simulink
4.5.2.2 Simulation Results and Discussion
4.6 DC Motor-Pump with MPPT vs. Direct Coupled System

Chapter 5: Conclusion

Acknowledgement

Reference

Appendix-A

Appendix-B

List of Figures

Figure 1-1: Research Methodology of Project

Figure 1-2: Schematic diagram of the proposed AC PV pumping system

Figure 1-3: Schematic diagram of the proposed DC PV pumping system

Figure 2-1: Equivalent circuit diagram of the PV model

Figure 2-2: Effect of diode ideality factors

Figure 2-3: Effect of series resistances

Figure 2-4: BP SX 150S PV module picture

Figure 2-5: Characteristics curve of PV module for different values of temperatures simulated with the MATLAB model (T=25 0C, Irradiance 1KW/m2)

Figure 2-6: Curves of PV module at various sun radiations

Figure 2-7: Curves of PV module at various sun radiations

Figure 2-8: Curves of PV module at various temperatures

Figure 2-9: Curve of PV module and maximum power point

Figure 3-1: Plot of power vs. voltage for PV module (at 25 0C, 1000kW/m2)

Figure 3-2: Flowchart of the Perturb & Observe (P&O) algorithm

Figure 3-3: Plot of power vs. voltage for PV module (at 25 0C, 1000kW/m2)

Figure 3-4: Flowchart of the incCond algorithm

Figure 3-5: Optimum current versus short circuit

Figure 3-6: Optimum voltage versus open voltage

Figure 3-7: Block diagram of MPPT with PI compensator

Figure 3-8: Irradiance data for a sunny day

Figure 3-9: Irradiance data for a cloudy day

Figure 3-10: MPPT tracking on a sunny day for P&O Algorithm

Figure 3-11: MPPT tracking on a sunny day for IncCond Algorithm

Figure 3-12: MPPT tracking on a cloudy day for P&O Algorithm

Figure 3-13: MPPT tracking on a cloudy day for IncCond Algorithm

Figure 3-14: Flowchart of the (P&O) algorithm for the output sensing direct control technique

Figure 3-15: MPPT simulation flowchart for resistive load

Figure 3-16: MPPT simulation with the resistive load of 50 (at 25 0C 200 to 1kW/m2)

Figure 3-17: Output regulation and protection for (60 illustration not visible in this excerpt) loads

Figure 4-1: PV pumping scheme structure

Figure 4-2: Show the per-phase exact equivalent circuit of a 3-phase induction motor

Figure 4-3: The I-V curve of 42 BP solar polycrystalline panel at different atmospheric condition

Figure 4-4: The induction motor-pump load simulation with MPPT (at 25 0C, 20 to 1KW/m2)

Figure 4-5: Shows the developed power of the induction motor, the maximum power generated is around 1600W

Figure 4-6: The developed power of the induction motor

Figure 4-7: Flow rates of PV water pumps for a 12 hour period simulated with the irradiance data of a sunny day (total dynamic head about 50m)

Figure 4-8: Electrical model of PMDC motor

Figure 4-9: DC motor-pump illustration not visible in this excerpt curve and PV illustration not visible in this excerpt cures with varying irradiance

Figure 4-10: Block diagram of the proposed PV pumping system

Figure 4-11: SIMULINK model of PMDC motor-pump

Figure 4-12: Shows block parameter of DC machine

Figure 4-13: SIMULINK plot of illustration not visible in this excerpt

Figure 4-14: The DC motor-pump load with MPPT simulation (at 25 0C, 20 to 1kW/m2)

Figure 4-15: DC pump motor load with a buck converter with MPPT simulation (at 25 0C, 20 to 1kW/m2)

Figure 4-16: Flow rates of PV water pumps for a 12-hour period simulated with irradiance data of a sunny day (total dynamic head=30m)..

List of Tables

Table 2-1: Electrical characteristics data of PV module at 25 0C, 1.5 AM, 1000W/m2 taken from the data-sheet

Table 3-1: Comparison of the P&O and incCond algorithm for cloudy day (25 0C)

Table 3-2: Load matching with the resistive load (50 illustration not visible in this excerpt) under varying irradiance

Table 3-3: Load matching with the resistive load (60 illustration not visible in this excerpt) under varying irradiance

Table 3-4: Shows energy production and efficiency of PV module with MPPT and without MPPT

Table 4-1: Shows energy production and efficiency of PV pumping system with MPPT

Table 4-2: Shows energy production and efficiency of PV pumping system without MPPT.

Table 4-3: Shows energy production of PV pumping system for direct coupled system and different converters efficiencies

Table 4-4: Total volume of water pumps for a 12-hour period simulated with the irradiance data of a sunny day (total dynamic head about 50m)

Table 4-5: Energy produced and efficiency of PV module with MPPT and without MPPT

Table 4-6: Total volume of water pumped for 12-hours simulated with the irradiance data of a sunny day (total dynamic head = 30m)

ACRONYM LIST

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Abstract

With the increased use of photovoltaic (PV) water pumping system, the photovoltaic (PV) has become one of the most promising technology in solar energy applications. Moreover, PV water pumping system is getting more popular in recent days especially in remote areas to supply water where electricity is economically not available.

The present study deals with the simulation of Photovoltaic (PV) based AC motor pumping system and DC motor pumping system equipped with Maximum Power Point Tracker (MPPT) and without MPPT. We performed comparative tests of the two well-known MPPT ‘the Perturbation and observation’ (P&O) and the ‘Incremental Conductance’ (IncCond) algorithms using actual irradiance data for different climate conditions, and also explained of various MPPT algorithms and the modeling of PV module is discussed in this thesis.

The PV pumping system with DC motor-pump load is simulated and described, whose study is carried out by using SimPowerSystem in MATLAB/SIMULINK and the model is then transfer into MATLAB. The whole system is implemented in MATLAB simulation, and verifies the functionality and benefits of MPPT. Simulations also established comparisons between both systems in terms of performance parameters such as total energy produced and total volume of water pumped a day. The results indicate that the system with MPPT can significantly improve the performance and the efficiency of PV water pumping system as compared to the one without MPPT.

The PV pumping system with an inverter fed AC induction motor is studied and simulations are carried out by using MATLAB to verify the functional performance and advantages of MPPT, and the detailed comparison between direct coupled systems and systems with MPPT is also included. The result validates that the pumping system with MPPT has much better performance compared to the system without MPPT.

The comparative tests of the two MPPT methods, Perturbation and observation (P&O) and Incremental Conductance (IncCond), are done by MATLAB to the achieve maximum power transfer. The results validate that under cloudy weather conditions, the performance of the IncCond algorithm exhibits slightly higher efficiency than performance of the P&O algorithm.

The simulations of the PV system with resistive load with MPPT vs. direct are coupled also carried out. The results show that the system with MPPT can utilize more than (96%) of electric energy produced from PVG (PV generator) and, on the other hand the system without MPPT has lower efficiency 34.97% as compared to the system with MPPT.

Keywords: Photovoltaic Pumping system, PV module modeling, MPPT, DC Motor, AC Motor

Chapter 1: INTRODUCTION

This chapter briefs the overview of MPPT based PV water pumping system including project background, objectives, scopes, methodology and outline of the thesis. It explains the description of the MPPT, and PV pumping system with DC motor-pump load and with induction motor-pump load, and whole block diagram of proposed systems. At the end, outline of this thesis is given in this chapter.

1.1 Objective

The main objective of this thesis is to develop an efficient PV water pumping system using MPPT technique and the comparison between the performance of the systems with, and without MPPT. MATLAB simulation is performed and functional performance and advantages of MPPT are tested. The comparative test of the PV module has been undertaken with MPPT vs. direct-couple system and with resistive load. The PV pumping system with DC motor-pump has been studied and simulation carried out using SimPowerSystems in MATLAB/SIMULINK. The PV system with an inverter fed AC induction motor has also study carried out. Moreover, this project is about to explore the action of effective performance in PV water pumping system compared to the system with, and without MPPT. Also study has done the two MPPT algorithms to achieve the maximum power.

1.2 Scope

The scopes of this project are:

- Study the PV module modeling
- Study of comparison between performance of two algorithms using actual irradiance data
- Simulation of MPPT with resistive load and system with MPPT vs. direct-coupled system
- Simulation study of AC induction motor-pump with MPPT and without MPPT
- Simulation study of DC motor-pump with MPPT and without MPPT
- Published a research article in international journal according to the project work

1.3 Methodology

This chapter discusses the research methodology and procedures as well as equipment and software in the whole work process. The methodology describes how the flows of the project work and the project topic is divided into different phases-sections. The work schedule topic describes the use of Gantt charts for the project schedules and the equipment, and software topic describes the equipment and software used in the project.

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Figure 1-1: Research Methodology of Project

Figure.1-1 above shows that the first step in this project was focused on research study of PV water pumping system using AC motor-pump and DC motor pump. For the PV pumping system using an AC motor-pump, the simulated system comprises of 42 BP solar polycrystalline, the MPPT control, the ideal boost converter, an inverter and the induction motor-pump. For the PV pumping system using a DC motor-pump, the proposed system involves of Kyocera SD 12-30 solar pump, single PV module, MPPT and brushed permanent magnet DC motor-pump. During this step, the components value was calculated using developed formulas and equations. Then models of AC motor-pump and DC motor-pump were built and simulated using MATLAB software. The both systems compared between the performance and efficiency with MPPT and without.

1.4 Problem Statement

Water resources are extremely important for fulfilling human needs, health safety, and ensuring food production, energy and the restoration of ecosystems, social and economic growth and for sustainable development [1]. However, according to the survey reported by the UN Department, it has been estimated that approximately two billion people are affected by water shortages in over forty countries due to the water scarcity and water stress, and 1.1 billion people do not have available enough drinking water [13]. There is a great and urgent need to supply drinking water in remote area. Remote PV water pumping systems are the most important element in meeting this requirement where grid system is unavailable.

PV systems are highly durable and maintenance free. The PV systems have advantages such as unattended operation, no fuel and no fumes, easy to install, low recurrent costs and are usually preferred because they provide the lowest life-cycle cost, However PV systems have disadvantages under cloudy weather condition when produces low output power [15]. Generally for application demanding less than 9KW, where power gird is unavailable and where internal-combustion engines are high-priced to utilize. If the water source is 1/3 mile (around 0.52Km) or more from the transmission line, PV is a favorable economic choice [2],[4],[9].

Water pumps are driven by various types of motors. AC induction motors are cheaper and widely available worldwide. The system, however, needs an inverter to convert DC output power from PV to AC power, which is usually expensive. In general, DC motors are used because they are highly efficient and can be directly coupled with a PV module or array.

1.5 Background

The development of renewable energy has been one of the most serious topics in the 21st century with the increasing issue of global warming and other ecological problems. With extensive research, alternative renewable energy sources such as biofuel, wind power, hydropower, geothermal energy and solar energy have become more and more significant for electric energy production. While solar photovoltaic cells are definitely nothing new, but their use has become more ordinary, practical and valuable for people global-wide.

The most important aspect of solar cell is that it produces power energy directly from solar energy through the solar PV panel which fabricated of silicon cells. Although every cell outputs a comparatively low voltage, if several are linked in series, a solar photovoltaic module is formed. In a typical module, there can be up to 36 solar cells, generating an open circuit voltage of around 25V. Even the price for such solar cells is reducing; but production of a solar cell module still needs large financial investment. Therefore, to make a PV module beneficial, it is essential to extract as much energy as possible from such a system [2],[5].

At a given temperature and insulation level, PV cells produce maximum power at one particular operation point called the maximum power point (MPP). Different conventional energy sources, it is necessary to operate PV systems at its MPP. However, the MPP locus changes over an extensive approach, depending on PV module insulation intensity and cell temperature. Instantaneous shading conditions and aging of PV cells also affect the MPP locus. Moreover, the electrical load characteristics may also change. Therefore, to attain the operation at the MPP, a time varying matching network is needed that interfaces the varying source and perhaps the varying load. The character of this matching network is called the maximum power point tracking network (MPPT) which to certify operation of the PV array at its MPP, irrespective of load variations and climate conditions. MPPT circuits are known by means of switched mode DC–DC converters [5],[8].

Various algorithms have been proposed for MPP tracking but the most widely used ones are the ‘Perturbation and observation’ (P&O) and the ‘Incremental Conductance’ (IncCond) algorithms. The duty cycle of the converter will be regulated; as a result the source will supply maximum power to the load. Solar energy is utilized for many applications; it is used to feed the grid network, to charge a battery, and also it is used for an off-gird PV water pumping system.

Water pumps are operated by different types of motors. AC induction motors are low-cost and commercially available worldwide. However, the system requires an inverter to convert DC output power from PV module into AC power output, which is typically costly. Mainly DC motors are used as they are very highly efficient, fast response and high dynamics to achieve top performance, and also can be directly coupled with a PV array or module [8],[15].

Finally, the motivation for this study is to explore the use of power electronics in renewable energy especially, photovoltaic (PV). Innumerable researches have been done in PV systems, a great number of them in developed countries. The main focus in this thesis is to enhance motors performance and optimization of PV water pumping system using maximum power point tracker (MPPT) Method.

1.6 Proposed Project

In this thesis, the proposed systems are uncomplicated and efficient for water pumping system. There are two systems which study carried out for this purpose. First, AC motor-pump load and second, DC motor-pump load for PV water pumping system. The pump converts input kinetic power into fluid output power. The output power is expressed by the supply of the pump in terms of flow-rate and head. The most used pumps are:

- Positive displacement pumps which are more suitable for deep wells have a flow-rate which is usually independent of head. On the other hand, have a water output proportional to speed. Generally, Positive displacement types are used in low-volume pumps and cost-effective [4],[8].
- Centrifugal pumps which are appropriate for small to medium head and have their power output increased with speed consequently. Generally, Centrifugal pumps have comparatively high efficiency and are accomplished of pumping a high volume of water [4],[8].

1.6.1 AC Motor-Pump Load

The use of easy and cheapest type of AC motors can be more attractive in water pumping system because require much less maintenance and low cost as compared to DC driven system. The proposed system consists of 42 BP solar polycrystalline, the Maximum Power Point Tracker (MPPT) control, DC-AC inverter, DC-DC converter, a squirrel cage induction motor operating a centrifugal pump and sinusoidal PWM. Figure 1-2 shows the schematic diagram of the proposed AC PV pumping system.

illustration not visible in this excerpt D

Figure 1-2: Schematic diagram of the proposed AC PV pumping system

As comparison with DC motor, the efficiency of the pumping system with an induction motor demonstrates the functional performance and advantages of MPPT in the system. We can accomplish that the system with MPPT has good performance compared to the system without MPPT, because of the robust, low maintenance, higher efficiency and low-cost characteristics of three-phase induction motors; it is obvious that the use of induction motor based PV water pumping systems will become most famous technology in the future.

1.6.2 DC Motor-Pump Load

The pumping system with DC motor-pump composed of Kyocera SD12-13 solar pump because it is positive displacement type pump which is selected here for its cost and size. The composed system includes of PV panel, brushed permanent magnet DC (PMDC) which is used in off-grid water supply systems, DC/DC converter, MPPT and a PWM. Figure 1-3 shows schematic diagram for the proposed DC PV pumping system.

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Figure 1-3: Schematic diagram of the proposed DC PV pumping system

For the pumping system with DC motor-pump load, the MATLAB simulation validates the functional performance and advantages of MPPT. Comparisons between the system without MPPT and with MPPT in terms of performance parameters such as the total energy generated and total volume of water pumped per a day has been carried out. The results show that MPPT can greatly improve the efficiency of energy generation from PV panel and the PV water pumping system has better performance as compared to the system without MPPT even if the converter is not 100% efficient.

1.7 Outline of the thesis

This thesis consists of four chapters.

In the first chapter, it discusses and describes the methodology, equipment of project and block diagram. It gives introduction, background, project objects, scopes and outline thesis. In chapter second, described the PV module modeling and simulated using MATLAB software. Also discussed curve characteristic of the PV module. In chapter third, the two most famous Maximum Power Point Tracker (MPPT) algorithms which are the Perturbation and Observation (P&O) and the Incremental Conductance algorithms are simulated by MATLAB, and compared between the efficiency of the two MPPT algorithms using actual irradiance data for two different climate conditions. A comparative test is done of the PV system with resistive load and MPPT vs. direct-coupled system. The chapter fourth deal with the PV water pumping system using MPPT technique, AC pumping water system with induction motor-pump load and DC pumping water system with DC motor-pump load are described and simulated. To understand the performance of the MPPT, and comparison between direct-coupled systems and systems with MPPT is undertaken. Finally, the last part in the thesis provides the conclusions, references, acknowledgment and appendices append in the project as well. The appendices of thesis are mentioned the master degree publication upon the thesis is written on the behalf.

Chapter 2: PHOTOVOLTAIC SYSTEM MODELING

2.1 Introduction

This chapter describes of PV modeling technique using equivalent electric circuit and models are performed by MATLAB to simulate a real PV module and also discussed of PV module illustration not visible in this excerptand illustration not visible in this excerptcharacteristics curve.

Renewable energy technologies are playing significant role to providing the world’s electricity demands and supplies. In particular, the photovoltaic (PV) generation system, the most promising energy source for the future, is growing fast and exhibiting an industrial development of around 50% per year worldwide [14]. Solar energy which is ultimate and available in most areas of the world has proven to be cheap source of energy in various applications. The earth receives energy from the sun is so massive and so lasting that the entire energy consumed yearly by the whole world is supplied in as short a time as a half hour. On a shining day, the sun's radiation on the earth can be 3000 watts per square meter depending on the location; the sun is a clean and renewable energy source, which produces neither green-house effect gas nor noxious waste through its utilization [6],[16].

The photovoltaic process is totally solid-state and self-reliant which converts sunlight into electricity using photovoltaic cells. There are no moving parts and no materials are consumed or emitted. Consider the benefits that PV systems have over challenging power options:

- They are clean and not releasing pollutants, especially carbon dioxide, into the atmosphere.
- They can be off-gird systems that consistently operate unattended for long life.
- They require no connection to an existing power source or fuel supply.
- They may be combined with other power to increasing reliability of the system.
- They can endure critical weather conditions including ice and snow.
- They consume no fossil fuels such as coal or gas - their fuel is free and abundant.
- They can be installed and upgraded as modular building blocks -as power demand increases; more photovoltaic modules may be added [6]-[7],[11].

2.2 PV Module Modeling

The study of PV electric model with moderate complexity to gives very realistic results, shown in figure 2-1 [6]. The electric model contains of a current source (illustration not visible in this excerpt), a series resistance (illustration not visible in this excerpt) and a diode. The model does not include parallel resistance (illustration not visible in this excerpt) because the effect of parallel resistance is very small in a single module. But it also involves reverse saturation current of diode (illustration not visible in this excerpt) and the temperature effects on the short-circuit current (illustration not visible in this excerpt) for the make better model. To attain the bestillustration not visible in this excerptcurve match result, it uses a single diode with the diode ideality (illustration not visible in this excerpt).

illustration not visible in this excerpt

Figure 2-1: Equivalent circuit diagram of the PV model

This model is a basic formed of the two diode model. The equation which explains the I-V relationship of the PV cell, and it is shown below.

illustration not visible in this excerpt (2-1)

Where: illustration not visible in this excerpt is the cell current (the same as the module current)

illustration not visible in this excerptis the short-circuit current that is equal to the photon generated current

illustration not visible in this excerpt is the reverse saturation current of diode

illustration not visible in this excerpt is the cell voltage = {module voltage} ÷ {# of cells in series}

illustration not visible in this excerpt is the cell temperature, illustration not visible in this excerptis the electric charge (1.6022 10-9 C), illustration not visible in this excerptis the Boltzman’s constant (13,807 10-23 Jk-1).

First, calculate the short-circuit current (Isc) at a given cell temperature (illustration not visible in this excerpt):

illustration not visible in this excerpt (2-2)

Where: illustration not visible in this excerptat is given in the data-sheet (measured under irradiance of 1000 W/m2), illustration not visible in this excerptis the reference temperature of PV cell in Kelvin (illustration not visible in this excerpt), usually 298illustration not visible in this excerpt(250 C),

illustration not visible in this excerpt is the temperature coefficient ofillustration not visible in this excerptin percent change per degree temperature also given in the PV module data-sheet. The short-circuit current (illustration not visible in this excerpt) is proportional to the intensity of irradiance, thus illustration not visible in this excerptat a given irradiance (illustration not visible in this excerpt) is:

illustration not visible in this excerpt (2-3)

Where: illustration not visible in this excerptis the nominal value of irradiance, which is normally 1 kW/m2, the reverse saturation current of diode (illustration not visible in this excerpt) at the reference temperature illustration not visible in this excerptis:

illustration not visible in this excerpt (2-4)

The reverse saturation current (illustration not visible in this excerpt) is temperature dependent and the illustration not visible in this excerpt at a given temperature

illustration not visible in this excerpt is calculated by the following equation [3]:

illustration not visible in this excerpt (2-5)

The diode ideality factor (illustration not visible in this excerpt) must be estimated which is unknown. Figure 2-2 shows the effect of the varying ideality factor. It takes a value among one and two. However, (for the ideal diode) the value of illustration not visible in this excerpt=1 is used until the more precise value is appraised later by curve fitting [10].

The series resistance (illustration not visible in this excerpt) has a great effect on the slope of the illustration not visible in this excerptcurve near the open-circuit voltage (illustration not visible in this excerpt), as shown in figure 2-3; therefore the value of illustration not visible in this excerpt is evaluated by measuring the slope illustration not visible in this excerpt of the illustration not visible in this excerpt curve at the illustration not visible in this excerpt[10]. The equation for illustration not visible in this excerpt is obtained by differentiating the illustration not visible in this excerpt equation (2-1) and then rearranging it in terms ofillustration not visible in this excerpt.

illustration not visible in this excerpt

Figure 2-2: Effect of diode ideality factors

illustration not visible in this excerpt

Figure 2-3: Effect of series resistances

illustration not visible in this excerpt (2-6)

illustration not visible in this excerpt (2-7)

illustration not visible in this excerpt (2-8)

illustration not visible in this excerpt (2-9)

Then, evaluate the equation (2-8) at the open-circuit voltage that is illustration not visible in this excerpt (also letillustration not visible in this excerpt).

Where: illustration not visible in this excerpt is the slope of the illustration not visible in this excerptcurve at the illustration not visible in this excerpt(use the illustration not visible in this excerpt curve in the data-sheet divide it by the number of cells in series), illustration not visible in this excerpt is the open-circuit voltage of cell (found by dividing illustration not visible in this excerptin the data-sheet by the number of cells in series).

In conclusion, the equation of illustration not visible in this excerpt characteristics is easily to define by the Newton’s method because the solution of current is recursive by inclusion of a series resistance in the model [10]. The Newton’s method is defined as:

illustration not visible in this excerpt (2-10)

Where: illustration not visible in this excerpt is the derivative of the function,illustration not visible in this excerpt, illustration not visible in this excerpt is a present value, and illustration not visible in this excerpt is a next value.

Rewriting the equation (2-1) describes the following function:

illustration not visible in this excerpt (2-11)

Plugging this into the equation (2-10) gives a following recursive equation, and the output current illustration not visible in this excerpt is computed iteratively.

illustration not visible in this excerpt (2-12)

In this thesis, the MATLAB function written to executes the calculation five times iteratively to verify that convergence of the results.

2.2.1 Simulation by MATLAB

The BP Solar BP SX 150S solar array PV module is selected for a MATLAB simulation. The module is consisting of 72 multi-crystalline silicon solar cells in series able to deliver 150W of nominal maximum power [12]. Table 2-1 shows its electrical specification from data sheet.

illustration not visible in this excerpt

Figure 2-4: BP SX 150S PV module picture

Table 2-1: Electrical characteristics data of PV module at 25 0C, 1.5 AM, 1000W/m2 taken from the data-sheet

illustration not visible in this excerpt

The MATLAB model selects the value of n = 1.61 that achieve the most correspondence result with illustration not visible in this excerptcurve according to the data-sheet, after the several tests with various diode ideality factors. The figures 2-5, 2-6, 2-7, show good matching among the simulated illustration not visible in this excerptcurves and the data points.

illustration not visible in this excerpt

Figures 2-5: illustration not visible in this excerpt characteristics curve of PV module for different values of temperatures simulated with the MATLAB model (T=25 0C, Irradiance 1KW/m2)

The simulation result of the modeling of PV module indicates that the using of equivalent electric circuit in moderate complexity provides good matching result according to the data sheet information. For instance, in the data sheet, the nominal maximum power of the BP SX 150S PV module at 25 0C, 1 KW/m2 of temperature, radiation is 150 W and the evaluated value is approximately 148.892 W, therefore the accuracy of the PV modeling is approximately 98.99%. Though, for the large PV system it is chosen to employ the maximum accurate equivalent circuit to have matching best results.

2.2.2 Effect of Irradiance

Irradiance is significant varying element in the performance of solar array. Solar panels are only as effective as the sum of energy they can generate, because solar panels depend on conditions that are always unvarying but the sun of power extracted from a PV module can be very inconstant. The characteristic of irradiance is describes the density of radiation incident on a given surface [18].

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Figure 2-6: illustration not visible in this excerpt Curves of PV module at various sun radiations

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Figure 2-7: illustration not visible in this excerpt curves of PV module at various sun radiations

In terms of PV modules, irradiance describes the amount of solar energy that is absorbed by the array over its area. In typically, Irradiance is describes in watts per square meter (W/m2). A solar panel irradiance, given ideal conditions should be achieve an irradiance of 1000 W/m2, or 100mW/cm2. Unluckily, this value that is achieved from a solar panel will change substantially depending on angle of the sun and geographical position [18],[19].

It can be seeing in above figure 2-6 and figure 2-7, a PV module’s output power is directly proportional to the irradiance. As a result, a smaller irradiance will decrease output power from the solar panel. Though, it is also seen that only the output current is affected by the irradiance. When light intensity or the irradiance is low, the flux of photon is less than when the light intensity is high and the sun is shining, so more current is produced as the light intensity increments. The variation in voltage is low with changing irradiance and for large practical application; the changing is considered insignificant [19].

2.2.3 Effect of temperature

The temperature of the PV modules has a large impact on its performance. The above figure 2-5 indicates that the temperature most influences on the terminal voltage, which increases with reducing of temperature. This is a little astonishing that one would distinctive believe the solar panels to work more efficiently as temperature increment. Though, one of the causes for the solar panel works in order to more efficiently with the reducing of temperature because of the electron and hole mobility of the semiconductor material. As temperature increases, the electron and hole mobility in the semiconductor material decreases considerably.

The band gap energy of semiconductor materials also changes with temperature. An increment in temperature will result to increase the band gap energy of the material. With higher band gap energy, the electrons in the valence band will need more energy from the photons to move to the conduction band. This means that more photons will not have enough energy to be absorbed by the electrons in the valence band as resulting in fewer electrons creating it to the conduction band and a less efficient solar cell [18].

The temperature of a PV module also affects its efficiency because the power output of PV module is decreased at high temperature. In general, increase in temperature, the PV module of the crystalline silicon efficiency will be decrease around 0.6 percent for each degree 0C. However, the result of changing temperature does not have a significant great influence on the current developed [18].

illustration not visible in this excerpt

Figure 2-8: illustration not visible in this excerpt curves of PV module at various temperatures

2.2.4 The Characteristics curve and Maximum Power Point (MPP)

Figure 2-9 shows that the illustration not visible in this excerpt curve of the BP SX 150S PV module and the maximum power point. It should be observed that there are various power-versus-current curves and different voltage-versus-current curves according to the combination of irradiance and temperature. Also, there occur other reasons that with strongly influence the electrical characteristics, i.e., surface contamination and shades on the PV panel. Therefore, the number of the characteristic curves is essentially countless, depending on the potential combinations of atmospheric condition. A PV module can generate the power at a point in anywhere on the illustration not visible in this excerptcurve, called an operating point. The matches of the operating point are the operating current and voltage. There is a unique point close the knee of the illustration not visible in this excerptcurve, is called the maximum power point (MPP), at which the PV module works with the maximum efficiency and generates the maximum output power. It is conceivable to visualize the position of the maximum power point (MPP) by fitting the largest possible rectangle inside of the illustration not visible in this excerpt curve and its area equal to the output power which is a product of current and voltage [11],[15].

illustration not visible in this excerpt

Figure 2-9: illustration not visible in this excerpt curve of PV module and maximum power point

Chapter 3: MAXIMUM POWER POINT TRACKING ALGORITHMS

This chapter provides comparative tests of the two common MPPT algorithms which are the Perturbation and Observation (P&O) and the Incremental and Conductance (incCond) algorithms. The simulation performed of two MPPT algorithms is carried out by using the actual radiance data in the two different climate conditions and also describe a comparative study of the PV system with resistive load and MPPT vs. direct-coupled system.

3.1 Introduction

The MPPT is the method which satisfies that the PV panel under any varies in irradiance and cell temperature conditions provides the maximum obtainable power. In other meaning, there is a need to track the MPP to maximize the power drawn off from the PV panel under any situation that can possibly cause the system to lose regulation [20].

The Peak power is reached with the help of a dc/dc converter among the PV Generator and the load by modifying its duty cycle such that the resistance matching is achieved. At this instant the problem arises how to differ the duty cycle and in which direction so that maximum power is accomplished. The automatic tracking can be operated by using different algorithms [21].

Those algorithms are the heart of the MPPT controller. The algorithms are applied in a personal computer or a micro-controller to perform maximum power tracking. To increases the power output of the module, the algorithm alterations the duty cycle of the dc/dc converter and able to make it work at the peak power point of the PV module. Algorithm that can be used is of the following types:

- Perturb and observe (P&O)
- Incremental Conductance (inCond)
- Parasitic Capacitance
- Current Based Peak Power Tracking
- Voltage Based Peak Power Tracking

3.2 Perturbation and Observation (P&O) Algorithm

The Perturbation & Observation (P&O) algorithm, is also called the “hill climbing” technique, is very famous and the most widely utilized in practice because of its simple structure and the few measured parameters which are needed. The (P&O) algorithm is established on the constant measuring of the PV voltage and current and calculation of its power output while the operating point is affecting in direction to attain the maximum power [11],[20].

In this algorithm the PV module of the operating voltage is disorder by a slight increment, and it is observed by the resulting change of power, ∆P. As shown in figure 3-1, if the ∆P is negative, the operating point has moved away from the MPP, and the direction of perturbation should be reversed to move back toward the MPP. If the ∆P is optimistic, then it is assumed that it has reached the operating point nearer to the MPP. Therefore, more voltage perturbations in the same direction should reach the operating point toward the MPP. This algorithm has two parameters:

1) The increment of the movement of the operating point itself.
2) The time interval among the times when measurement is done and the time when the operating point moves from its optimum value.

illustration not visible in this excerpt

Figure 3-1 plot of power vs. voltage for PV module (at 25 0C, 1000kW/m2)

When the steady state is reached the algorithm oscillates nearby the peak point. In this direction to retain the power variation slight the perturbation size is kept very small. The algorithm is established in such a way that it fixes a reference voltage of the module equivalent to the optimal voltage of the module. A proportional and integral (PI) controller then performs to reaching the operating point of the module to that specific voltage level. It is realized that there is some power loss because of this perturbation also the disable to track the power under fast changing atmospheric conditions. But still this algorithm is very simple and common.

The flowchart of this algorithm is given in Figure 3-2:

illustration not visible in this excerpt

Figure 3-2 Flowchart of the Perturb & Observe (P&O) algorithm

3.3 Incremental and Conductance (incCond) Algorithm

The drawback of the Perturb & Observe algorithm when tracking the peak power under fast changing weather condition is overcome by the Incremental Conductance algorithm. The Incremental Conductance (incCond) method is established on the fact that the slope illustration not visible in this excerpt of the PV module power-voltage plot is positive on the left side of the MPP, zero at the MPP and negative on the right side of the MPP as shown in figure 3-3.

illustration not visible in this excerpt

Figure 3-3: Plot of power vs. voltage for PV module (at 25 0C, 1000kW/m2)

The incremental and conductance algorithm creates use of the following equations:

illustration not visible in this excerpt at MPP (3-1)

illustration not visible in this excerpt at the left of MPP (3-2)

illustration not visible in this excerpt at the right of MPP (3-3)

The above equations can be written in terms of current and voltage as follows:

illustration not visible in this excerpt (3-4)

If the operating point is at the MPP, equation (3-4) becomes:

illustration not visible in this excerpt (3-5)

illustration not visible in this excerpt (3-6)

If the operating point is at the left side of the MPP, equation (3-4) becomes:

illustration not visible in this excerpt (3-7)

illustration not visible in this excerpt (3-8)

If the operating point is at the right side of the MPP, equation (3-4) becomes:

illustration not visible in this excerpt (3-9)

illustration not visible in this excerpt (3-10)

The flowchart shown in figure 3-4 below explains the operation of this algorithm. It starts with calculating the present values of the PVG current and voltage. Then, it determines the incremental variations of illustration not visible in this excerptandillustration not visible in this excerpt, using the previous values and present values of current and voltage. The main test is undertaken by the relationships in the equations (3-5), (3-6), and (3-7). If the condition satisfies the inequality (3-6), it is supposed that the operating point is at the left side of the MPP thus must be reached to the right direction through rising the PV generator voltage. Correspondingly, if the condition satisfies inequality (3-7), it is supposed that the operating point is at the right side of the MPP, thus must be reached to the left by reducing the PV generator voltage. When the operating point moves the MPP, the condition satisfies the equation (3-5), and the algorithm bypasses the voltage alteration. At the end of the cycle, it updates the history by storing the current and voltage data that will be used as previous values in the following cycle. Another main test involved in this algorithm is to identify climate conditions. If the MPPT is still operating at the MPP (condition:illustration not visible in this excerpt) and the irradiation has not changed (condition:illustration not visible in this excerpt), it takes no process. If the irradiation has risen (conditionillustration not visible in this excerpt), it increases the MPP voltage. Then, the algorithm will raise the operating voltage to track the MPP. Likewise, in case of reducing irradiation (condition:illustration not visible in this excerpt), the MPP voltage will be dropped. Then, the algorithm will drop the operating voltage .Thus it can be assumed that the incremental conductance can track quickly decreasing and increasing weather conditions with greater accuracy compared to Perturbation and Observation (P&O) algorithm. One drawback of this algorithm is the increased complexity than the Perturb and Observe algorithm [21].

The flowchart of this algorithm is given in figure 3-4:

illustration not visible in this excerpt Figure 3-4 Flowchart of the incCond algorithm

3.4 Parasitic Capacitance Technique

The parasitic capacitance technique is a refinement of the incremental conductance technique that takes into account the parasitic capacitances of the solar cells in the PV array. Parasitic capacitance uses the switching ripple of the MPPT to perturb the array. To account for the parasitic capacitance, the average ripple in the array voltage and power, produced by the switching frequency, are calculated using a series of multipliers and filters, and then used to determine the array conductance. The incremental conductance algorithm is then used to evaluate the direction to reach the operating point of the MPPT. One negative point of this algorithm is that the parasitic capacitance in every module is very slight, and will only point out in large PV arrays where many module strings are linked in parallel. Moreover, the DC-DC converter has a substantial input capacitor used filter out minor ripple in the panel power. This capacitor may cover the whole effects of the parasitic capacitance of the PV panel [20].

3.5 Current Control MPPT

The optimal operating current illustration not visible in this excerpt for the maximum output power is proportional to the short current illustration not visible in this excerpt under various conditions of irradiance illustration not visible in this excerpt [17]. The proportionality relationship is expressed as follows:

illustration not visible in this excerpt (3-11)

Where, illustration not visible in this excerpt: is the proportional constant

illustration not visible in this excerpt: is the optimum operation current

illustration not visible in this excerpt: is the short current of the PV generator (PVG)

This equation shows that current illustration not visible in this excerptcan be determined instantaneously by identifying illustration not visible in this excerptand that the MPPT can be attained by providing a current command illustration not visible in this excerpt to a current-controlled power converter. But, the effect of the temperature has to be investigated first by using the check PV module over a wide range of the temperature.

Figure 3-5 indicates the measurement results and it can be said that the relationship betweenillustration not visible in this excerptand illustration not visible in this excerptis still proportional, despite the temperature variation from 0 0C to 60 0C [12]. From this figure, the proportional parameter k can be calculated to be about 0.90 [20]-[21].

illustration not visible in this excerpt

Figure 3-5: Optimum current versus short circuit

The major disadvantage with this technique is that a great power resistor is needed which can suffer the short-circuit current. The PV generator has to be short circuited to measure the short circuit-current as it goes on varying with the changes in insulation level [21].

3.6 Voltage Control MPPT

A linear dependency exists between “cell voltages corresponding to maximum power” and “cell open circuit voltages” [16]:

illustration not visible in this excerpt (3-12)

This equation describes the key concept of the Voltage-Based Maximum Power Point Tracking (VMPPT) method. illustration not visible in this excerpt, is known as the “voltage factor” and is equal to 0.74 [23]. Equation (3-8) is plotted in figure 3-6 together with the calculated (almost linear) dependency of illustration not visible in this excerptwith respect to illustration not visible in this excerpt (shown by “+” signs).

As a result by measuring the open circuit voltage a reference voltage can be produced and a give forward voltage control system can be applied to carry the solar PV module voltage to the point of maximum power. However the simplicity of this method, it presents one disadvantage. The open circuit voltage of the PV generator changes with the temperature. So as the temperature increase the PV generator open circuit voltage varies and we have to determine the open circuit voltage of the module very often. Therefore the load must be detached from the module to calculate open circuit voltage. Thus some PV generator power will be straying [20]-[21].

illustration not visible in this excerpt

Figure 3-6: Optimum voltage versus open voltage

3.7 Control of MPPT System

As give details in the previous sections, the MPPT algorithm expresses an MPPT controller how to move the operating voltage. Then, it is an MPPT controller’s duty to carry the voltage to maintain in desired level. The MPPT algorithm (Perturbation and Observation, Incremental and Conductance …etc.) is performed in a software program with a self-tuning function, which automatically controls the array reference voltage and voltage step size to fast obtain the Maximum Power Tracking under fast varying conditions. Then, there is another control loop that is the proportional and integral (PI) controller which adjusts the input voltage of the converter. The purpose of the PI controller is to reduce the error between (illustration not visible in this excerpt) and the computed voltage by regulating the duty cycle [3]. The PI loop works with a fast rate and delivers quick response and is used to increase the system stability. The functions in the two loops can be executed by a Digital Signal Processing (DSP). The DSP-based controller detect the PV generator power as shown in figure 3-7, and measurement the PV generator slope power, output power and (illustration not visible in this excerpt) to track the MPP [5],[3].

illustration not visible in this excerpt

Figure 3-7: Block diagram of MPPT with PI compensator

3.8 Comparative Test of (P&O) and incCond Algorithm

In the previous sections we have been discussed various MPPT algorithms. In this present study the Perturb & Observe (P&O) and Incremental Conductance (IncCond) techniques are selected to be performed in MATLAB simulations and verified for their performance. We have preferred those algorithms because they are steady, simple, and they can obtain higher efficiencies, and the main negative point is that the other algorithms require monitoring system (calculators, sensors,...etc) and hence increase the cost, so the Perturb & Observe (P&O) and Incremental Conductance (incCond) techniques are the common option for MPPT [11],[15],[20].

Since the aim is to establish comparisons performance between of the two algorithms, each simulation comprises only the PV model and the algorithm in order to detach any effect from a load or converter. The algorithms are simulated and tested with inconstant irradiance data, the MATLAB are implemented in two sets of irradiance data: the first set of irradiance statistics which taken a every 15 minutes during a typical day in March for the measurements of a sunny day, where the irradiance changes gradually throughout the day. The second set of Irradiance data is the measurements for a cloudy day in the same month, where the irradiance changes very fast during the day. The irradiance values among two data points are evaluated by the cubic interpolation in MATLAB functions [15].

illustration not visible in this excerpt

Figure 3-8: Irradiance data for a sunny day

illustration not visible in this excerpt

Figure 3-9: Irradiance data for a cloudy day

3.9 Simulation Results and Discussion

For the simulation and perform the comparison between the Perturb & Observe algorithm and the IncCond algorithm using the first set of irradiance data of the sunny day computation, showing that the irradiance changes slowly (no effect of cloud), we observation that the two algorithms trace and retain the PV operating point very near to the MPPs without appreciable difference in their efficiency as shown in figure 3-10 and figure 3-11. However, the dissimilar performances of the algorithms are able to see when the second set of irradiance data is used (cloudy day measurement where the irradiance changes very quickly), so the MPP tracking is assumed to be challenging. For each algorithms, the difference of operating points from the MPPs are evident that when matched to the results of a sunny day.

illustration not visible in this excerpt

Figure 3-10: MPPT tracking on a sunny day for P&O Algorithm

illustration not visible in this excerpt

Figure 3-11: MPPT tracking on a sunny day for IncCond Algorithm

illustration not visible in this excerpt

Figure 3-12: MPPT tracking on a cloudy day for P&O Algorithm

illustration not visible in this excerpt

Figure 3-13: MPPT tracking on a cloudy day for IncCond Algorithm

The Incremental Conductance algorithm is assumed to defeat the drawbacks of the Perturb & Observe algorithm under fast inconsistent weather conditions. The simulation test result in figure 4-11 validate that the IncCond algorithm has not slightly larger differences compare to the Perturb & Observe algorithm and it has some unpredictable manners which are also clear in the plot of the IncCond algorithm. To establish good comparison between the two algorithms, the total power energy generated throughout a 12-hour period is measured and as shown in table 3-1.

Table 3-1: comparison of the P&O and incCond algorithm for cloudy day (25 0C)

illustration not visible in this excerpt

As the table 3-1 shows, the total electric energy generated by the IncCond algorithm is almost greater than that of the P&O algorithm. The MPPT efficiency is calculated by the following relation:

Efficiency = {Total Energy (simulation)} ÷ {Total Energy (theoretical max)} × 100%

The result concludes that the efficiency is better for Perturb & Observe algorithm and IncCond algorithm even in cloudy weather conditions. Though, the efficiency is a little good with the IncCond algorithm. There are further simulation studies demonstration closely the same results; the simulation presented that the efficiency of 99.82% for the P& O algorithm and 99.83% for the IncCond algorithm. The observational test results indicated 95.5% and 96.0%, respectively, for a partially cloudy day [15],[25].

3.10 Performance and Simulation of MPPT with Resistive Load

The MPPT with a resistive load is performed in MATLAB simulation and tested. The simulation results in Section 3.9 have indicate that there is no significant benefit in using the much complicated IncCond algorithm, and the P&O algorithm delivers acceptable results even in the cloudy weather condition. The choice of the P&O algorithm allows the use of the output sensing direct control technique which removes the current sensors and input voltage. The MPPT scheme, hence, selects the P&O algorithm and the output sensing direct control technique because of the benefit that permits of a simple and cheap system.

3.11 Output Sensing Direct Control Technique

The output sensing technique measures the power change of PV at the output side of converter and uses the duty cycle as a control variable. This control technique is simple and uses only one control loop, and it executes the alteration of duty cycle within the MPP tracking algorithm.

This control technique utilizes the P&O algorithm to trace the MPP. Figure 3-14 shows the flowchart of algorithm. In order to serve duty cycle as a control variable, the P&O algorithm employed here is a little altered version from that earlier introduced, however the process how it operates is precisely the same. The algorithm perturbs the duty cycle and measures the converter output power. If power increases, the duty cycle is further perturbed in the same direction; otherwise the direction will be reversed. When the converter output power reaches the peak, the PV module or array is assumed to be operating at the Maximum Power Point. As the flowchart describe, first the algorithm measure the converter output current and voltage, then the output power illustration not visible in this excerpt and its variation (illustration not visible in this excerpt) is calculated at each step. If the variation in the output power is optimistic then the variation on the duty cycle kept on the same direction, otherwise the direction of the perturbation on the duty cycle will be reversed [15],[26]-[27].

The flowchart of this algorithm is given in Figure 3-14:

illustration not visible in this excerpt

Figure 3-14 Flowchart of the (P&O) algorithm for the output sensing direct control technique

3.12 Limitation of Maximum Power Point Tracker (MPPT)

The main negative point of MPPT is that there is no control on output during it is tracking a maximum power point. It cannot maintain both output and input at the same period.

The maximum power transfer happens when the input impedance (resistance) of converter matches the optimum impedance (resistance) of the PVG [28], as expressed in the equation below:

illustration not visible in this excerpt (3-13)

illustration not visible in this excerpt, is the input impedance of the converter:

illustration not visible in this excerpt (3-14)

The equation (3-14) for the boost converter is explained for duty cycle (D):

illustration not visible in this excerpt (3-15)

The converter output voltage is assumed by:

illustration not visible in this excerpt (3-16)

The converter output current is assumed by:

illustration not visible in this excerpt (3-17)

The relative betweenillustration not visible in this excerptand illustration not visible in this excerptis:

illustration not visible in this excerpt (3-18)

The evaluation results are presented in the tables below. PV module data are achieved by the implemented MATLAB simulation model. Using the equations above, a set of data is accumulated for the resistive load of 50Ω and 60Ω at the constant PV module temperature of 25 0C.

Table 3-2: Load matching with the resistive load (50illustration not visible in this excerpt) under varying irradiance

illustration not visible in this excerpt

The results in tables 3-2 and 3-3 validate that the output current (Io) and output voltage (Vo) are changing and not adjusted. If the application needs a constant voltage, batteries must be employed to control the voltage constant. When the resistive load alteration from 50Ω to 60Ω the duty cycle of the converter changes even if the input is the similar which clear that the design of the converter must ensure the specifications of the source and the load at the same period. In other term, it is positive point to choice the suitable size of the load, so that the capacity of PV Generator can be completely operated.

Table 3-3: Load matching with the resistive load (60illustration not visible in this excerpt) under varying irradiance

illustration not visible in this excerpt

3.13 Simulated System

The simulated system comprises of the ideal boost converter, BP SX 150S PV model, the resistive load (50Ω) and the MPPT control.

The MATLAB function that models the PVG is the following:

illustration not visible in this excerpt (3-19)

The function, bp_sx150s, measures the module current (illustration not visible in this excerpt) for the given module voltage (illustration not visible in this excerpt), irradiance (G in KW/m2), and module temperature (T in 0C). The operating point of the PVG is measured by its relationship with the load resistance (R):

illustration not visible in this excerpt (3-20)

The irradiance (illustration not visible in this excerpt) and the PVG temperature (illustration not visible in this excerpt) for the function (3-19) is known variables, so it is possible to say that (illustration not visible in this excerpt) is a function of (illustration not visible in this excerpt) hence: illustration not visible in this excerpt

Substituting it into the equation (3-20) gives:

illustration not visible in this excerpt (3-21)

illustration not visible in this excerpt (3-22)

The final equation will be:

illustration not visible in this excerpt (3-23)

Knowing the value of illustration not visible in this excerpt allows to explain this equation for the operating voltage (illustration not visible in this excerpt). MATLAB uses f zero function to do so. Putting (illustration not visible in this excerpt) into the equation (3-19) which provides the operating current (illustration not visible in this excerpt). The following equations define the input/output relationship of current and voltage. The equations are expressed by:

illustration not visible in this excerpt (3-24)

illustration not visible in this excerpt (3-25)

Where:illustration not visible in this excerpt is the boost converter voltage output.

illustration not visible in this excerpt, is the boost converter output current.

illustration not visible in this excerpt, is the boost converter duty cycle.

The flowchart describes the operation of the simulated system, as shown in figure 3-15 below:

illustration not visible in this excerpt

Figure 3-15: MPPT simulation flowchart for resistive load

The control algorithm covers two loops, the main first loop for MPPT and a second loop for output protection. During normal operation, the algorithm works in MPPT mode. When the load cannot absorb all the power generated by the PV generator, it’s current or/and voltage will across the permissible boundaries. To protect the load from failure, the control algorithms quit working in MPPT mode and actuate the output protection. After that, it adjusts the output so that it does not go beyond the safe limits. In the simulation, it sets when the output voltage goes beyond 85.8V or 1.74A for the output current for the resistive load R =50 Ω.

The simulation is done under linearly rising irradiance changing from 200w/m2 to 1000W/m2 with an average rate of 0.4W/m2 per sample. Figure 4-15 (a) and (b) indicate that the locus of operating point is resting near to the MPPs.

Figure 4-15 (c) shows the relationship between the duty cycle and its output power of converter. Figure 4-15 (d) shows the voltage and current relationship of converter output. Meanwhile the load is resistive, the voltage and current rise linearly with the slope of illustration not visible in this excerpt on the illustration not visible in this excerpt plot.

illustration not visible in this excerpt

(a) PV Power vs. Voltage

illustration not visible in this excerpt

(b) PV Current vs. Voltage

illustration not visible in this excerpt

(c) Output Power vs. Duty Cycle

illustration not visible in this excerpt

(d) Output Current vs. Voltage

Figure 3 -1 6 : MPPT simulation with the resistive load of 50 illustration not visible in this excerpt (at 25 0C 200 to 1kW/m2)

3.14 System with MPPT vs. Direct Coupled System

To understand the results of using MPPT in system and how it enhance the performance through extracting the maximal power from the PV panel, a comparison is established among the system with direct coupled system and system with MPPT. The irradiance statistics employed here are the computation of a sunny day. The total power energy generated throughout a 12- hour period is estimated and presented in Table 3-4.

Table 3 -4: Shows Energy production and efficiency of PV module with and without MPPT

illustration not visible in this excerpt

Figure 3-17: Output regulation and protection for (60illustration not visible in this excerpt) load

The results validate that the PV generator system with MPPT can employ more than (96%) of PV Generator capacity. One the other hand, it shows that the system without MPPT has less efficiency (34.97 %) due to dissimilarity among the resistive load and the PV module.

If vary the value of the load to 60Ω, the limit of 85.6V will be across on the rising irradiance. The output protection keeps the voltage about 85.6V. Figure 3-17 (a) shows that the PV generator is not working at the MPP and providing the low power than the high after the irradiance attains at a slightly over 800W/m2, and as we supposed before, this result shows the prominence of choosing an applicable size of load, so it can totally exploit the overall capacity of PV array or module.

Chapter 4: MPPT FOR PV WATER PUMPING SYSTEM

This chapter provides the simulation study of PV water pumping system with MPPT and without MPPT. The maximum power point systems are used with nonlinear source for which a MPPT occurs for any certain operation condition. The AC motor-pump and Dc motor-pump are used for steady-state performance of the PV pumping system described in this chapter.

4.1 PV Pumping System

Safe drinking water is one of the most important requirements for the population around the world, in developing countries; it is still an issue to supply water for all population. To overcome this hard situation many photovoltaic water pumping system programs are proposed. Photovoltaic power source is utilized for water pumping system which is the most promising technology in solar PV applications for supply water in remote area. The pumping system is used to provide water delivery in off-grid communities where electricity supply is unavailable [1].

The use of water pumps fed by PV system has several benefits, such as reliability, ease of installation and low maintenance. Though, two major disadvantages for using solar energy are existed the very low photovoltaic cell conversion efficiency and the high initial cost.

Many researchers have been done on way of matching, sizing and adapting photovoltaic pumping systems. To enhance such installation, prefer of the drive system which more appropriate for the photovoltaic source, type of pumps to use and ways to control the whole system must be studied [7],[36].

A typical photovoltaic pumping system consists of a power conditioner, PV cell array, and the load. Also other fittings materials such as cabling transducers, water storage, energy storages (batteries) and protection are required.

4.2 System Configurations of PV Pumping System

Photovoltaic water pumping system has different system configurations.

1) The first configuration is Photovoltaic pumping system with AC motor using MPPT. However, in this condition some additional conditioning circuit is required.
2) The second configuration is the directly coupled systems where a PV panel is directly coupled to a pump and Dc motor. Such system is dependable and simple, but system does not operate continuously at its optimal point because the continuous variation of solar radiation.
3) The third configuration is Photovoltaic pumping system with DC motor using MPPT to enhance the performance of the system.

4.3 Power Conditioner Stage

The power conditioner stage generally comprise of a DC/DC converter which can be step-down or step-up or step-down/step-up converter. If an AC motor is used for PV pumping system, an inverter must be involved in order to implement the DC/AC conversion stage [46].

4.4 AC Motor Using for PV Pumping System

The PV water pumping system using induction motors can be very attractive; such a system is more consistent and needs low-maintenance as comparison with DC driven system. The only main obstacle of the induction motor is to increase the cost of more complex control circuit. The cheapest and simplest type of AC motor is the squirrel-cage induction motor. Its low cost and rugged structure make it the most widely used motor for PV applications [2],[49].

4.4.1 General Descriptions

Figure 4-1 shows the schematic diagram of PV pumping system with induction motor, the whole system is contained of a power dc–dc adapter, a PV generator (PVG), a squirrel-cage induction motor driving a centrifugal pump and a natural sinusoidal PWM voltage source inverter.

illustration not visible in this excerpt

Figure 4-1: PV pumping scheme structure

4.4.1.1 Induction Motor

Induction motors are commonly used for medium to high-power requirement applications. Induction motors with squirrel-cage rotors are available in either three phases or single phase. An induction motor works at nearly constant speed. However, the speed of an induction motor can be changed with electronic converters (inverters). Using inverters to control induction motor speeds is highly efficient over wide speed and load ranges [2],[48].

4.4.1.2 Inverter

The inverter is used to convert the dc voltage into ac voltage (three-phase) to deliver the induction motor for operating the pump. The output voltage of the inverter is sinusoidal with variable frequency and amplitude according to the solar radiation. The current is modulated sinusoidal to achieve a high efficiency [41].

4.4.1.3 DC-DC Converter

The DC-DC converter is an impedance adapter; it is used to force the PV array to supply the maximum power to the load.

4.4.1.4 Pump

The pump use as the mechanical load of the induction motor and its size determines the power ratings of the other system components, including the essential PV peak power [50].

Submersible centrifugal pumps are used for PV pumping system with induction motor. Submersible centrifugal pumps are best for high flow rates (30-150 1/min) and medium heads (20-40 meters). The flow head characteristic of a centrifugal pump can be given by the following equation [50].

illustration not visible in this excerpt (4-1)

Where illustration not visible in this excerptare geometric parameters characterizing the pump.

illustration not visible in this excerpt: The speed of motor.

illustration not visible in this excerpt: Total height (m).

illustration not visible in this excerpt: Flow rate of the pump (m3/h)

4.4.2 Control Methods

Latest study has focused on attaining the most energy efficient by control algorithms technique for AC machine-pump loads in which MPPT tracking and maximum motor and pump performance are the system efficiency objectives.

Similar DC motors, the induction motor characteristics harshly affected by the nonlinear characteristic of the PV source, therefore two optimization methods are used [41].

- The induction motor is controlled to accomplish maximum performance and efficiency.
- The PV generator (PVG) maximum power is tracked.

4.4.2.1 Plus-Width Modulation (PWM) Controller

To enhance the PV pumping system, the induction motor has to be controlled to attain maximum performance and efficiency. The two control methods are used: the vector control and scalar control [38].

The conventional (V/f) control operation of the system will have to be modulated according to the atmospheric conditions in order to certify a maximal PV pumping operation during the day.

Numerous studies investigate that the “V/f” law is adequate to governor pumping systems, particularly as this type of applications does not need high energetic performance [39],[49].

4.4.2.2 Maximum Power Point Tracker (MPPT)

We can utilize MPPT on an induction motor-PV pumping system in various stages, in the molded of inverter or DC-DC converter. When the inverter with MPPT is used (without a DC-DC converter stage), the available PV power is employed more efficiently. In this situation, the inverter performs as both a variable-frequency source to regulate the output of the PV generator and the water pump [42]-[43], [47].

4.4.3 Steady-State Performance of a PV Pumping System Using AC Motor-Pump

The proposed PV pumping system includes of the 42 BP solar polycrystalline panel, an inverter, the MPPT control, the induction motor-pump load and the ideal boost converter.

4.4.3.1 Induction Motor-Pump

In the proposed system, A squirrel-cage induction motor of 1.6 KW, 4 poles, 222/381 V, 50 Hz, 1425 tr/min. Rr = 3.709illustration not visible in this excerpt; Rs = 4.94illustration not visible in this excerpt; Xr = 2.499illustration not visible in this excerpt; Xs = 2.512illustration not visible in this excerpt; Rm = 500illustration not visible in this excerpt; Xm = 81.07illustration not visible in this excerpt.

A per-phase equivalent circuit model is used for modeling of the induction motor. As shown in figure 4-2, Xs and Rs are the leakage reactance of the stator winding and per-phase resistance; X’r and R’r are reactance referred to the stator and the rotor resistance. Xm expresses the magnetizing reactance and Rm is the resistance for excitation (or core) loss.

illustration not visible in this excerpt

Figure 4-2: show the per-phase exact equivalent circuit of a 3-phase induction motor.

The equivalent impedance of the induction motor is:

illustration not visible in this excerpt (4-2)

illustration not visible in this excerpt: is the stator impedance (Rs+jXs)

illustration not visible in this excerpt: is the equivalent per-phase impedance realized by the stator across the motor gap (illustration not visible in this excerpt)

illustration not visible in this excerpt (4-3)

The Gap power (power passing from the stator to the rotor through the air gap) is:

illustration not visible in this excerpt (4-4)

The developed power is:

illustration not visible in this excerpt (4-5)

4.4.3.2 DC-AC Inverter

The dc-ac inverter is used to supply three-phase ac voltage to the induction motor to operate the pump which is variable in frequency and amplitude according to the solar radiation.

They differ from 0.1 up to 1 time the rated frequency and voltage. It depends of the weather conditions and loads. The switching frequency is equal to 2 kHz [24],[45]. The phase voltage is representing by the following expression:

illustration not visible in this excerpt (4-6)

With illustration not visible in this excerpt is the input voltage,illustration not visible in this excerpt, illustration not visible in this excerptand illustration not visible in this excerptare the Plus-Width Modulation (PWM) control signals.

According to demands of operate, the V/f can be controlled in not consistent or invariable manner. It changes with weather conditions. If suppose that for lower irradiances, before 09 h:00 or after 17 h:00, the inverter frequency is less than 10 Hz. In order to start or to maintain the operational of the system the V/f ratio changes instantaneously [44].

The V/f law is defined as [36]:

illustration not visible in this excerpt (4-7)

Assuming that the system is stable and the operation is at steady-state and the inverter is ideal, the RMS values of voltages and currents are used in simulations.

4.4.3.3 PV Generator (PVG)

illustration not visible in this excerpt

(a)

illustration not visible in this excerpt

(b)

Figure 4-3: the I-V curve of 42 BP solar polycrystalline panel at different atmospheric conditions

The PV generator comprise of 42 modules which are arranged in three parallel strings with fourteen in both and connected to the dc–dc converter. The maximum power supplied by PV generator is 2.1 KW. For various atmospheric conditions (ambient temperature and irradiance), an example of simulated I–V curve for the 2100 W PV plant as shown in above figure 4-3

4.4.3.4 Simulation Results and Discussion

The simulation is done by the same method as previously simulation; the perturbation and observation (P & O) algorithm is employed to achieve the maximum power from the source maximum power point tracker (MPPT) by changing the duty cycle of the boost converter (to have impedance matching). The irradiance statistics are utilized for the computation of a sunny day; introduced in section 3.8, figures 4-4 (a) and (b) show that the locus of operating point resting near to the MPPs during the simulation. Figure 4-4 (c) shows that the relationship between the duty cycle and its output power of converter. Figure 4-4 (d) shows the voltage and current relationship of converter output.

illustration not visible in this excerpt

Figure 4-4: The induction motor-pump load simulation with MPPT (at 250C, 20 to 1KW/m2)

illustration not visible in this excerpt

Figure 4-5: shows the developed power of the induction motor, the maximum power generated is around 1600W.

The established power produced by the induction motor is computed and total electric energy generated by the PV array throughout a 12-hour period is calculated.

Table 4-1: Shows energy production and efficiency of PV pumping system with MPPT

illustration not visible in this excerpt

As shown in table 4-1, (η1) is the efficiency of the MPPT which is very high, around 96.37% and (η2) is the efficiency of the induction motor which is 70.6% so as a result the (η) total efficiency of the PV water pumping system with MPPT is about 67.37%. We observe the influence of the MPPT in the efficiency of the system. We make a comparison among the previous system and the same system without MPPT. The results are shown in table 4-2.

Table 4-2: Shows energy production and efficiency of PV pumping system without MPPT

illustration not visible in this excerpt

The results validate that the PV water pumping system has less efficiency (35.68%) without MPPT because of not well matching among the induction motor pump load and the PV module, the PV module generate only 52.25% of its capacity. On the other side, but the previous results show that the PV water pumping system with MPPT can employ more than 94% of PV capacity. But in reality the electronic circuits alike DC-AC inverters and DC-DC converters are not 100% efficient, because of resistive losses in inductors and capacitors, diode loss, switching loss in a Power-MOSFET and harmonics reduce the efficiency of the system. In a practical method, the efficiency of the inverter is around 96% and the efficiency of the DC-DC converters is among 90 to 96%. We can have more accurate results by supposing of system losses. We can see comparison of the established power of the induction motor for loss-less converters efficiencies as shown in figure 4-6. It can be seen that the PV pumping system with MPPT provides good result as comparable without MPPT even if the electronic converters are not 100% percent efficient. Table 4-3 shows the developed power in 12 hours of each system.

Table 4-3: Shows energy production of PV pumping system for direct coupled system and different converters efficiencies

illustration not visible in this excerpt

As we can see in Figure 4-7, a more comparison can be done in term of flow rates and total volume of water pumped per day of PV water pumping system. The maximum flow rate of the pumped water for loss-less converter is around 43 1/min, for the 90% efficiency converter is approximately 34 1/min, for the 95% efficiency converter is almost 38 1/min and for direct coupled system the flow rate is about 16 1/min. The results show the great disparity in efficiency among the both systems.

The total volume of water pumped for the 12-hour period is estimated for the system with MPPT and the system without MPPT. The results are presented in table 4-4. The results indicate that the system with MPPT water can more pump up to 60% as compare the system without MPPT. Moreover the simulation plots show that a 6% enhancement in the converter efficiency can raise the pumped water in a day by 11.26%.

illustration not visible in this excerpt

Figure 4-6: The developed power of the induction motor

illustration not visible in this excerpt

Figure 4-7: Flow rates of PV water pumps for a 12 hour period simulated with the irradiance data of a sunny day (total dynamic head about 50m)

Table 4-4: Total volume of water pumps for a 12-hour period simulated with the irradiance data of a sunny day (total dynamic head about 50m)

illustration not visible in this excerpt

4.5 DC Motor Using for PV Pumping System

Direct coupling of series, shunt, and separately excited DC motor can be used to drive the PV water pump. Permanent magnet and separately exited DC motors are more appropriate for PV water pumping systems. Permanent magnet DC motors features high level dynamics, fast response and high efficiency [17].

For better alteration of the load to the source, MPPT method is used to increase the output power produced from the PV generator and thus enhances the efficiency of the entire system as well [17],[31],[37].

4.5.1 I-V Characteristics of DC Motor

The permanent magnet DC (PMDC) motors are compatible for PV pumping system. DC motors easier to directly-coupled with PV arrays and make a simple system therefore DC motors are preferred instead of AC motors for the many PV water pumping systems. Among various types of DC motors, a permanent magnet DC (PMDC) motor is chosen in PV systems because it can deliver higher starting torque speed. When the motor is rotating, it generates a back emf, or a counter- electromotive force, defined as an electric potential (illustration not visible in this excerpt) proportional to the angular speed (illustration not visible in this excerpt) of the rotor [15],[37]. From the equivalent circuit, the DC voltage equation for the armature circuit is:

illustration not visible in this excerpt (4-8)

Where: illustration not visible in this excerpt is the armature resistance.

The back emf is illustration not visible in this excerpt where: illustration not visible in this excerpt is the constant, and illustration not visible in this excerpt is the angular speed of rotor in rad/sec.

illustration not visible in this excerpt

Figure 4-8: Electrical model of PMDC motor

Figure 6-8 [32]-[34] shows an example of current-voltage relationship (illustration not visible in this excerpt cure) of a DC motor. Applying the voltage to start the motor, the current increases fast with rising voltage while the current is adequate to make sufficient starting torque to break the motor loose from static friction [15]-[16]. At start-up illustration not visible in this excerpt there is no influence of back emf, thus the starting current produce linearly with a steep slope of 1/Ra on the illustration not visible in this excerpt plot as shown in figure 4-9. Once it starts to operate, the back emf takes effect and drops the current, therefore the current increases gradually with rising voltage.

Under steady state operation stage when we have a direct coupled PV pumping system with a DC motor. It is realized that the relationship between the I-V characteristic of the PV generator (PVG) and the I-V characteristics of the motor is not at the optimal point as shown in figure 5-2. In this case, the water pumping system would not start operating up to irradiance attain at 400W/m2. Once it starts to drive, it needs as slight as 200W/m2 of irradiance to uphold the minimal operation. This means that the system cannot employ a reasonable amount of morning insulation because there is not enough starting torque. Moreover, when the motor is driven under the safe condition for a long period, it might derived in reducing of the lifetime of the motor because of input electrical power changed to heat into mechanical output. For the PV source the power generated at the MPP is comparatively high-voltage and low-current which is completely different of those needed by the pump motor, so the MPPT is used to overcome this mismatching factor and obviously improve the efficiency by converting the power into low-voltage and high-current which adequate the pump motor characteristics. The Maximum power point tracker could start the pump motor at 60W/m2 of irradiance [35].

illustration not visible in this excerpt

Figure 4-9: DC motor-pump illustration not visible in this excerpt curve and PV illustration not visible in this excerpt cures with varying irradiance

4.5.2 Steady-State Performance of PV Pumping System Using DC Motor

The proposed system is very simple and consists of a DC water pump, a single PV module and a maximum power point tracker (MPPT).

illustration not visible in this excerpt

Figure 4-10: Block diagram of the proposed PV pumping system

The Kyocera SD 12-30 solar pump is chosen due to its cost and size. It is a positive displacement pump equipped with a brushed permanent magnet DC motor and designed it for use in standalone water provision systems, especially for water supply in off-grid areas. The flow rates of the pump up to 18.0L/min and heads up to 35.0m (114ft.). The estimated daily water output is between 2,600L and 4,500L. The evaluated maximum power use is 160W. It drives with a low voltage between (12~30V DC) and its current demand is as small as 40W.

The flow rate of water in positive displacement pumps is directly proportional to the speed of the pump motor, which is employed by the available operating voltage. They have constant load torque to the pump motors and it is defined by the total dynamic head in terms of its equivalent vertical column of water. For example, vertical lift and friction converted to vertical lift [4].

4.5.2.1 MATLAB SIMULINK

To model a PMDC motor, the SIMULINK model applies a constant field, as shown in figure 4-11. Meanwhile the DC motor-pump is a positive displacement type so the load torque is as well invariable. The value is chosen to plot the maximal power of 160W at the maximal voltage of 30V. The functional parameters of DC machine match with actual pump-motor which are unidentified, therefore they are selected by alteration of the default values and evaluation from other references. The DC machine parameter can see in figure 4-12.

illustration not visible in this excerpt

Figure: 4-11 SIMULINK model of PMDC motor-pump

illustration not visible in this excerpt

Figure: 4-12 shows block parameter of DC machine

The DC motor-pump load is characterized by a varying resistance. The variable resistance changes with the slight difference of the voltage source as given by equation (4-9). The voltage source applies a 0-30V ramp at the rate of 1V per second. The alteration of load resistance is noticed; see in figure 4-13. The plot statistics are shifted to MATLAB and the cubic curve fitting tool in MATLAB gives the equation of the curve, shown in below.

illustration not visible in this excerpt (4-9)

Where: illustration not visible in this excerpt is the output voltage of converter, this equation represented the DC pump motor and use it in the MATLAB simulation.

illustration not visible in this excerpt

Figure 4-13: SIMULINK plot of illustration not visible in this excerpt

4.5.2.2 Simulation Results and Discussion

The simulation is undertaken by same method as that for the resistive load. The irradiance is rise linearly from 200W/m2 to 1000W/m2 with the equal amount of 0.4W per sample. Though, as a replacement of boost converter for MPPT; a buck-boost converter is utilized for water pumping.

The output voltage requires to be stepped down to deliver a higher starting power for a pump motor of the water pumping systems. The buck-converter is easiest to understand, simplest topology and structure, but it shows the most critical failure approach of each configurations; the buck- converter give a high current for the output, when the Root Mean Square (RMS) value of this current squared and multiplied by the Equivalent Series Resistance (ESR) of the affected capacitor (the capacitor is the weakest portion in the circuit), result in heating. Immoderate heating can degrade component efficiency and lifetime. In this cause, buck-converter cannot work at the MPP under each state. Hence, the more boost capability can improve the overall performance of the system. [24],[47]. Figure 4-14 (a) and (b) show that the locus of operating point staying near to the MPPs during the simulation.

illustration not visible in this excerpt

Figure 4-14 (c) shows the relationship between the duty cycle and the converter output power.

illustration not visible in this excerpt

Figure 4-14 (d) shows the voltage and current relationship of converter output which is same to the DC motor load.

Figure 4-14: The DC motor-pump load with MPPT simulation (at 25 0C, 20 to 1kW/m2)

Figure 4-14 (d) indicate that the output current increases fast with rising voltage while the current is adequate to produce sufficient torque to drive the motor. Once it starts to drive, the back emf takes effect and drops the current, so the current increases gradually with rising voltage. It is notice that those characteristics are matching with the characteristics of the DC motor pump illustration not visible in this excerpt curve as shown in figure 4-9; therefore it can be obvious that the simple MATLAB model of DC motor governed here is valid.

It is supposed in previous section the buck-boost converter is much competent compare the buck converter for the water pumping system because of the boost function, figure 4-15 exhibit the simulation of the same system but with the buck converter. It is clearly observed that the buck converter cannot able to handle the MPP for all conditions.

illustration not visible in this excerpt

Figure 4-15: DC pump motor load with a buck converter with MPPT simulation (at 25 0C, 20 to 1kW/m2)

4.6 DC Motor-Pump with MPPT vs. Direct Coupled System

In the earlier section, the PV water pumping system with MPPT simulated which is comparative with the direct-coupled PV water pumping system without MPPT. The irradiance statistics used here are the computation of a sunny day; presented in section 3.8. The total electric energy generated throughout a 12-hour period is computed, shows in Table 4-5.

Table: 4-5 Energy produced and efficiency of PV module without MPPT and with MPPT

illustration not visible in this excerpt

The results conclude that the PV water pumping system with MPPT can employ more than 96% capacity which produced from PVG. On the other hand, the system without MPPT has low efficiency (60.97 %) due to dissimilarity among DC pump motor load and the PV module. Supposing a DC-DC converter has efficiency more than 90%, the system can enhance the whole efficiency by more than 26% as compared to the system without MPPT.

A further comparison of the two systems can be made in terms of performance parameters such as flow rates and total volume of water pumped per day. As we can see in figure 4-13, the flow rate of Kyocera SD 12-30 water pump is proportional to the produced power. When the total dynamic head is 35m, the flow rate per watt is almost 85.9cm3/W.min. The lowest power requirement of pump motor is 40W; therefore as long as the output power is higher than 45W, it pumps water with the flow rate overhead [4]. Performing the same experiment technique, the flow rates of pump are achieved from the MATLAB simulation test and shown in figure 4-16.

As shown in figure 4-16, it is said that the efficiency of the pumping system is increased if the output power of the PV generator is optimum. The direct-coupled PV water pumping system efficiency is poor than the system with MPPT even if the converter is 90 % or 95 % efficient, for the first 120 minutes the pump stays at rest during period the same system with MPPT is already pumping water. Likewise, it goes indolently almost two hours earlier compared the system with MPPT in the middle of the day.

illustration not visible in this excerpt

Figure 4-16: Flow rates of PV water pumps for a 12-hour period simulated with irradiance data of a sunny day (total dynamic head=30m)

The flow rate of water is also decrease during the operating period. Around the afternoon, we notice that the direct-coupled system has increase performance compared to the system of the 90% efficiency converter and almost the same performance as the 95% efficiency converter because of the high irradiance at this period. The total volume of water pumped for the 12-hour period is also computed for both systems. The results are presented in table 4-6.

Table: 4-6 Total volume of water pumped for 12-hours simulated with the irradiance data of a sunny day (total dynamic head = 30m)

illustration not visible in this excerpt

The table results show that MPPT gives significant enhancement in performance. It capable to pump more water up to 65% compared to the system without MPPT. However if the efficiency of converter is fix to 90%, but it can still pump more water 45% as compared to the system without MPPT. The results also indicate that 6% progress in the converter efficiency can raise the pumped water about 300 L/day which is around 6% of the volume of pumped water.

Chapter 5: CONCULSION

This thesis deals with the simplest but cost-effective photovoltaic water pumping system. It provides theoretical studies of maximum power point tracking (MPPT) for PV systems and its various applications for several loads. The study includes discussion of PV module modelling technique and different MMPT algorithms. The modelling of the PV module established on a basic formed of the two diode model attains good matching according to data sheet information. Theillustration not visible in this excerpt characteristic curve of the PV module is non-linear and the sum of power extracted fluctuates significantly depending on the radiation and temperature. The electric energy generated from the PV module is directly proportional to the irradiance and inversely proportional to the temperature.

The most common two MPPT algorithms, the Perturbation and Observation (P&O) algorithm and the Incremental and Conductance (IncCond) algorithm are simulated to obtain maximum power delivery; The IncCond algorithm shows narrowly but good performance in terms of efficiency as compared to the P&O algorithm under cloudy weather condition. A slightly progress of efficiency could take considerable preserving if the system is size-able. But, it could be difficult to explain the utilize of IncCond algorithm for small cheap systems such as the cost and accessibility are the two main feature of system structure and the IncCond algorithm will need four sensors more than the P&O algorithm and also it require additional control loops. In this cause, the (P&O) algorithm is preferred.

The comparative study of the PV system, MPPT with resistive load and system with MPPT vs. direct-coupled system; it indicates that the system with MPPT can employ more than 96% efficiency of PV theoretical capacity. On the other hand, the PV system without MPPT has less efficiency because of dissimilarity among the load and the PV module. Though, MPPT has several limitations; one of its major disadvantages is that there is no control on the output whereas it is tracking a maximum power point. It cannot maintain both input and output at the similar period. If the application needs a variable voltage, it must use batteries to adjust the voltage constant. Furthermore, if the value of the load resistance alteration the duty cycle of the converter changes even if the input is the same; this signify that the design of the converter must meet the specifications of the source and the load at the same period. Therefore, it is great essential to choice the suitable size of the load, therefore that the overall capacity of the PV panel and array is employed.

The PV pumping system with DC motor-pump has been simulated and study done by SimPowerSystems in SIMULINK. The model is then shifted into MATLAB. Simulation of the overall system is implemented and tested to functional performance and benefits of MPPT in the system. Comparison of the system with MPPT and without MPPT in terms performance parameter of total volume of water pumped per day and total energy generated is under taken. The Results show that the system performance with MPPT can significantly increase more than 96% of PV capacity and it is capable to achieve more water pump up to 65% as compared to the system without MPPT. Even if the efficiency of converter is not 90% efficient, it can still pump 45% more water compared the system without MPPT. The results show also that 6% progress in the converter efficiency can raise the pumped water around by 300 Litter per day which is about 6% of the volume of pumped water.

The PV pumping system with an inverter fed AC motor-pump is study carried out. The induction motor is system using the per-phase equivalent circuit. A comparison performance between the system without MPPT and the system with MPPT is undertaken. We can understand that the system without MPPT has poor efficiency than the system with MPPT; the efficiency is around 35% for the system without MPPT and 67% for the system with MPPT. Because of the robust, free maintenance and low cost characteristics of three-phase induction motors; it is obvious that induction motor based PV water pumping systems will become one of the most feasible solutions in remote area for water supply.

Future Recommendation

The accurate modelling of the DC water pump and DC-DC converter is an imperative area of research. A more correct model of the DC-DC converter would comprise switching losses in a Power switch, a diode losses and resistive losses in capacitors and inductors.

The model of DC water pump used for simulations which provides results within a practicable approach. But, the model accuracy and precision unknown due to the parameters are only estimates. If experiments could be run on the actual water pump motor or comparable sized motor to decide reasonable accesses to SIMULINK block parameters, this could lead to more correct simulation runs. Moreover, in a simple manner increasing the size of system and using a larger motor.

Similarly a more realistic modelling of the induction motor composed with the inverter is in sequence. Particular attention will be consecrated to reducing losses in all system portions, through the use of various converter topologies.

Practical execution of the system is examined as the following step. It may cover implementation of: a micro-controller or DSP (Digital Signal Processing), a technique of delivering power to the controller, DC- DC converters, and signal conditioning circuits for A/D converters, an operating circuit for Power- MOSFET, and a water level sensor that observes when the water pond reaches full. It will include performance investigation on the actual system and comparisons with simulations.

Acknowledgments

All praise to Almighty Allah, the most merciful and compassionate, who enable us to accomplish the goal of completing this. We express our special gratitude to our parents who provided us moral support and always prayed for our lifetime achievements. Although it has just been 3 years studying in Yunnan Normal University, it is an experience that will stay with me forever. My stay in still water has given me a lot to cherish, good friendships, an excellent studying environment to name a few. First of all I would like to thank Prof. Dr. Li Ming. He has inspired me throughout my life and has taught me never to give up. After I would like to thank my siblings for helping me realize my long standing dream of studying in an esteemed university. I am thankful to all my colleagues in our research group for assisting and helping me on numerous occasions. I consider myself fortunate enough to have made a lot of good friends. I would like to thank all of them for the help and support they extended towards me. I wish to extend my sincere appreciation to my supervisor Prof. Li for his guidance, intelligent supervision, and inspiration that helped me in the publishing of 4 research papers including 2 e-books and master thesis. My sincere appreciation also extends to my master thesis adviser Prof. Xiu Ji, Mr. Irfan Jamil and Mr. Engr. Rizwan Jamil whose assistance and encouragement are also invaluable.

Finally, I would like to thank School of Physics and Electronic Information and all members of faculty those taught master degree curriculum subjects and supporting me in published research papers and master graduation thesis.

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Appendix-A

Publications in Master degree 2011- 2013

1. Rehan Jamil, Ming Li, Xu Ji and Xi Luo “An Overview of Photovoltaic Power Generation and Solar PV Technology in Rural Area of Pakistan” Poster Presentation at the 26th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS-2013) at Guilin, China. GRIN Publishing GmbH, Munich, Germany, February, 2014.
2. Rehan Jamil, Li Ming, Irfan Jamil and Rizwan Jamil, “Application and Development Trend of Flue Gas Desulfurization (FGD) Process: A Review, International Journal of Innovation and Applied Studies, Vol. 4 No. 2 Oct. 2013, pp. 286-297, October 2013. ISSR Innovative Space of Scientific Research Journals.
3. Rehan Jamil, Irfan Jamil, Zhao Jinquan, Li Ming, Wei Ying Dong, and Rizwan Jamil, “Control and Configuration of Generator Excitation System as Current Mainstream Technology of Power System” International Journal of Innovation and Applied Studies. vol. 4, no. 3, pp. 603–611, November 2013. ISSR Innovative Space of Scientific Research Journals.
4. Rehan Jamil, Irfan Jamil, Zhao Jinquan, Li Ming, Wei Ying Dong, and Rizwan Jamil, “Theoretical Studies of Automatic Generation Control Technology,” International Journal of Innovation and Applied Studies, vol. 4, no. 4, pp. 636–642, December 2013. ISSR Innovative Space of Scientific Research Journals.
5. Jamil, R., Jamil, I., Li, M., Jinquan, Z... “Development Tendency of Energy: A Short Review". World Academy of Science, Engineering and Technology, International Science Index 81, International Journal of Environmental, Earth Science and Engineering (2013), 7(9), 74 - 79.
6. Irfan Jamil, Rehan Jamil, Zhao Jinquan, Li Ming, and Rizwan Jamil, “Applied analysis and construction of Prevention, Monitoring and Early Warning System of Mountain Torrent Disaster,” International Journal of Innovation and Applied Studies, vol. 4, no. 2, pp. 298–310, October 2013. © 2013 - ISSR Innovative Space of Scientific Research Journals.
7. Irfan Jamil, Rehan Jamil, Abdul Ghaffar, Li Ming, Zhao Jinquan, and Rizwan Jamil “Technical Analysis of Coal Utilization and Environmental Pollution” International Journal of Innovation and Applied Studies, vol. 4, no. 3, pp. 568–581, October 2013. © 2013 - ISSR Innovative Space of Scientific Research Journals.
8. Irfan Jamil, Rehan Jamil, Zhao Jinquan, Li Ming, Wei Ying Dong, and Rizwan Jamil “Condition-Based Maintenance Decision-making Support System (DSS) of Hydropower Plant” International Journal of Innovation and Applied Studies, vol. 4, no. 3, pp. 593–602, October 2013. ISSR Innovative Space of Scientific Research Journals.
9. Irfan Jamil, Rehan Jamil, Zhao Jinquan, Li Ming, Jiang Qirong, Wei Ying Dong, Rizwan Jamil “Application and Composition Observing System of Automatic Weather Station (AWS) and Power Grid (PGMIS) Electrical and Electronics Engineering: An International Journal (ELELIJ) Vol 2, No 4, Nov. 2013. Wireilla Scientific Publications, New South Wales, Australia.
10. Irfan Jamil , Rehan Jamil, Rizwan Jamil, Zhao Jinquan, and Abdus Samee, “Technical Communication of Automation Control System in Water Treatment Plant” International Journal of Innovation and Applied Studies, vol. 4, no. 1, pp. 28–36, September 2013. ISSR Innovative Space of Scientific Research Journals.
11. Irfan Jamil, Rehan Jamil, Zhao Jinquan, Rizwan Jamil and Abdus Samee, “Mathematical Model Analysis and Control Algorithms Design Based on State Feedback Method of Rotary Inverted Pendulum”, IMPACT: International Journal of Research in Engineering & Technology (IMPACT: IJRET), Vol. 1, Issue 3, Aug 2013, pp. 41-50, © Impact Journals.
12. Irfan Jamil, Zhao Jinquan, Rehan Jamil, Rizwan Jamil and Abdus Samee “A battery Charging system & Appended (ZCS) PWM Resonate Converter Dc-Dc Buck Technique for Battery Charger to Yield Efficient Performance in Charging Shaping” Electrical & Electronics Engineering: An International Journal (ELELIJ) Vol 2, No 2, May 2013. Wireilla Scientific Publications, New South Wales, Australia.
13. Irfan Jamil, Zhao Jinquan, Rehan Jamil, “Analysis, Design and Implementation of Zero-Current-Switching Resonant Converter DC-DC Buck Converter” International Journal of Electrical & Electronic Engineering (IJEEE) IASET, Vol. 2, Issue.2, pp. 1-12 May 2013.
14. Irfan Jamil, Zhao Jiquan, Qirong Jiang, Wei Ying Dong, Rehan Jamil “Technical Communication of Condition Monitoring System of Hydroelectric Generating Unit of HPP” 2013 IEEE 4th International Conference on Electronics Information and Emergency Communication Nov. 15-17, 2013, Beijing
15. Irfan Jamil, Rehan Jamil, Zhao Jinquan, Rizwan Jamil and Abdus Samee, “Mathematical Model Analysis and Control Algorithms Design Based on State Feedback Method of Rotary Inverted Pendulum”, IMPACT: International Journal of Research in Engineering & Technology (IMPACT: IJRET), Vol. 1, Issue 3, Aug 2013, pp. 41-50, © Impact Journals.
16. Muhammad Usman, Dai Zhongjian, Irfan Jamil , Rehan Jamil, Hassan Syed Mubashir “Model Building And Cascade Compensation Of Angle Servo Control System” Int. Journal of Engineering Research and Application ISSN : 2248-9622, Vol. 3, Issue 5, Sep-Oct 2013, pp.1000-1006
17. Rehan Jami l, Irfan Jamil, Zhao Jinquan, Ming, Li, Jiang Qirong, Wie ying dong, Rizwan Jamil “Development Engineering of Hydroelectric Generation Technology of HPP in China” ( Under Peer Review)
18. Rehan Jamil, Ming Li, Irfan Jamil, “A Comparative Test and Simulation Study of PV Water Pumping System” (Under Peer Review)

Appendix-B

MATLAB Functions and Programming

B.1 MATLAB Function for PV Modeling BP SX 150S PV Panel

This MATLAB function (bp_sx150s1.m) used in simulation throughout of this thesis. This function is to simulate the power-voltage (P-V) and current- voltage (I-V) relationship of BP SX 150S PV.

illustration not visible in this excerpt

B.2 MATLAB Function to Draw PV Module illustration not visible in this excerpt Curves

The simple MATLAB function is used for figure 2-1 to plot the illustration not visible in this excerpt characteristics curve for various module temperatures. Other draws showing PV module characteristics are simulated in similar method using MATLAB.

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B.3 MATLAB Script to find the MPP

This simple MATLAB script is to find the voltage, power and current at the MPP of BP SX 150S PV Generator under the given module temperature and Irradiance.

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B.4 MATLAB Function: IncCond Algorithm Under the Sunny Weather Condition

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B.5 MATLAB Function: IncCond Algorithm Under the Cloudy Weather Condition

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B.6 MATLAB Function: P&O Algorithm under Cloudy Weather Condition

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B.7 MATLAB Function: P&O Algorithm under Sunny Weather Condition

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B.8 MATLAB Script: MPPT with Output Sensing Direct Control Technique

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B.9 MATLAB Script: Matlab MPPT Simulation with AC Pump Motor Load

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B.10 MATLAB Script: Matlab MPPT Simulation with DC Pump Motor Load

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Details

Pages
114
Year
2014
ISBN (Book)
9783656684077
File size
1.7 MB
Language
English
Catalog Number
v275849
Grade
Tags
Photovoltaic Pumping system PV module modeling MPPT DC Motor AC Motor

Author

Previous

Title: Maximum power point tracker (MPPT) based photovoltaic (PV) water pumping system using AC and DC motors