Report_Monitoring System for a Photovoltaic Installation

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Tunisia Polytechnic School

Engineer internship report

Option Signal and Systems

Monitoring System For A PhotovoltaicInstallation

From 01 July to 15 August 2010

Hosting company : CMERP laboratory (ENIS)

Supervised by : Meher CHAABENLecturer

Elaborated by : Ahmed SAKKA

3rd

year student

Academic year: 2010/2011


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Abstract

Data acquisition systems (DAS) are extensively used in solar energy installations (SEI). Dataare collected in order to forecast the system behavior for the following days, to evaluate its

future capacity, to manage the energy, etc. This work describes the development of a sensor

conditioning electronics for a computer-based data acquisition system in order to control

the SEI and to save its parameters. The proposed system monitors a set of sensors which

measure three parameters: solar irradiation, ambient temperature, photovoltaic cell

temperature. The sensors output signals are conditioned using electronic circuits then

connected to a PC by means of a data acquisition (DAQ) card. As LabVIEW development

environment offers performance and flexibility by its programming language, as well as high-

level functionality and configuration util ities designed specifically for measurement and

automation applications, it is used to design the monitoring interface.

Keywords: Data acquisition system; Solar energy system; Virtual instrument; Sensors;

LabVIEW


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Contents

Introduction ................................................................................................................................ 4

1 Presentation of the laboratory:............................................................................................ 5

1.1 Machines and Network team ....................................................................................... 5

1.2 Diagnosis and Monitoring ........................................................................................... 5

1.3 Renewable energies ..................................................................................................... 5

2 Project context .................................................................................................................... 7

2.1 Presentation of the solar installation ............................................................................ 7

2.2 Presentation of sensors: ............................................................................................... 9

2.2.1 Heat sensor ........................................................................................................... 92.2.2 Irradiation sensor ................................................................................................ 11

2.3 Shortcoming of the existing DAS .............................................................................. 12

2.4 Project specification................................................................................................... 12

3 Project equipments ........................................................................................................... 13

3.1 Data acquisition (DAQ) card ..................................................................................... 13

3.1.1 Features of KUSB-3108 card ............................................................................. 13

3.1.2 Wiring method: ................................................................................................... 17

3.2 LabVIEW 8.6............................................................................................................. 183.2.1 General presentation ........................................................................................... 18

3.2.2 LabVIEW terms.................................................................................................. 19

3.3 DT-LV Link ............................................................................................................... 21

4 Conception of the monitoring system............................................................................... 23

4.1 Data acquisition system ............................................................................................. 23

4.1.1 Testing data acquisition with LabVIEW ............................................................ 23

4.1.2 Virtual instrument for solar irradiation acquisition ............................................ 24

4.1.3 Virtual instrument for temperature acquisition .................................................. 254.2 Data logging............................................................................................................... 28

4.2.1 Creating log files ................................................................................................ 28

4.2.2 Opening log files ................................................................................................ 29

4.3 The graphic interface and tests .................................................................................. 30


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List of Figures

figure 1 : The real solar installation............................................................................................. 8

figure 2: Synoptic schema of the solar installation .................................................................... 8figure 3: The ambient temperature sensor .................................................................................. 9figure 4: The photovoltaic cell temperature sensor .................................................................. 10

figure 5: Spektron 210 sensor ................................................................................................... 11Figure 6: Screw terminal assignments o f the KUSB-3108 board ............................................ 15

figure 7: Block Diagram of the KUSB-3108 Modules............................................................. 16figure 8: connecting single-ended voltage inputs (Shown for channel 1, 2 and 3) .................. 17figure 9: Connecting Differential Voltage Inputs (Shown for Channel 0) ............................... 18

figure 10:LabVIEW logo.......................................................................................................... 18figure 11 : Example of VI Front Panel ...................................................................................... 20

figure 12 : Example of VI Block Diagram ................................................................................ 21figure 13: The role of DT-LV Link ......................................................................................... 22figure 14: The prepared Block diagram to test the KUSB board ............................................. 23

figure 15: The line chart of the collected measures .................................................................. 23figure 16: The acquired input of the solar irradiation sensor ................................................... 24

figure 17: Temperature sensor stage c ircuit ............................................................................. 26figure 18: The input of the operational amplifier ..................................................................... 27figure 19: The voltage conditioning c ircuit .............................................................................. 27

figure 20: The carried out circuit .............................................................................................. 28

figure 21: The input of the circuit with the filtering stage ....................................................... 28figure 22: The developed graphic interface .............................................................................. 31
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Introduction

The use of solar energy in electric energy installation has been notably developed during the

last decades. However, the use of solar energy in electrical installation remains limited due

to the low efficiency of converter panels and the high price of storage systems (batteries). Inorder to improve solar plant generation, a total monitoring is necessary. Hence, many works

are interested in a real time power management giving an instantaneous decision on the

way to consume the generated energy. This tendency requires detailed knowledge of some

meteorological data of the photovoltaic panel (PVP) of the installation. The chosen approach

in the CMERP laboratory considers the PVP parameters provided by sensors (ambient

temperature, photovoltaic cell temperature and solar irradiation) during the last ten days in

order to forecast its behavior for the following day.

So this pattern of research needs in addition to the current PVP parameters, a data base of

these parameters during the last ten days. To accomplish this task a computer-based dataacquisition system (DAS) for monitoring and saving these parameters can be the most

flexible and simple solution.

It is within this context that I carried out my engineering internship aimed to develop a data

acquisition system to control in real time the PVP parameters from a graphic interface and to

store them on log files for fixed period.

The report is organized into four chapters. The first chapter gives an overview of the

principal activities of CMERP laboratory. The second chapter presents the project context

and specifications. The third chapter deals with the hardware and software equipments used

in the project. The fourth chapter explains the different steps to carry out the data

acquisition system and presents test results.


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1 Presentation of the laboratory:

The research unit "Commande de Machines Electriques et Rseaux de Puissance " (CMERP)

aims to bring together researchers from the Electrical Engineering discipline to coach,

develop and publish research related to:

modeling, supervision and control of electrical machines;

modeling, optimization and management of solar energy;

supervision, diagnosis and numerical control of industrial processes.

The research themes are developed in the context of:

agreements with universities;

research contracts with industry;

research projects.

The research group at the laboratory is divided in 3 teams:

1.1 Machines and Network team

The main themes of research of this team are:

Modelling, supervision and control of electrical machines;

Modeling and control of grid.

1.2 Diagnosis and Monitoring


Diagnosis and monitoring of complex systems;

Monitoring and fault tolerant control.

1.3 Renewable energies


Optimal energy management;

Modelling and design of installations;

Estimation of climatic parameters.

I carried out my internship with this team, especially with two researchers who conduct a

project based on the solar installation of the laboratory. My project is dedicated principally

to provide this team with a monitoring system for the principal parameters of the solar


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installation and a data base of the collected measures to be used in the estimation of PVP

behavior.


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2 Project context

The target work consists in the implementation of a DAS for the solar installation. So to

present the project context, a presentation of the solar installation and its sensors and an

explanation of the shortcoming of the present DAS are required. Thats leads us to deal with

the project specifications.

2.1 Presentation of the solar installation

Cmerp is equipped by a solar installation which is exposed on the roof of the laboratory.

It includes a 260 Wp photovoltaic panel generation and made up of four parallel connected

arrays (TE500CR+ of Total Energie) and the electric grid as a complementary energy source.

The PVP is equipped with a Maximum Power-Point Tracker, which is an electronic device

that monitors PVP to operate near its maximum power-point along the IV curve and an

inverter that provides the same output voltage as the electric grid (230 V/ 50 Hz). Theappliances, chosen as four lamps of 30, 40, 60 and 75 W, are supplied, via a switching relays

bloc, either by the PVP output or the electric grid. The whole installation is controlled by a

PC computer in which the planning algorithm is implemented.

The computer is connected as well to commercial data logging unit providing climatic

parameter measures: the solar irradiation G, the photovoltaic cell temperature Tpand the

ambient temperature Ta.

Figure 1 shows the real solar installation where as the figure 2 gives its synoptic schema.


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figure 1: The real solar installation

figure 2: Synoptic schema of the solar installation


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2.2 Presentation of sensors:

2.2.1 Heatsensor

To measure the temperatures, two PT1000 temperature sensors are used. PT1000 is a

resistance temperature detector (RTD) which exploits the predictable change in electrical

resistance of platinum with changing temperature. This sensor is called PT1000 because it is

a platinum RTD and has a nominal resistance of 1000 ohms at 0 C.

The platinum resistance thermometers are widely used in meteorological applications thinks

of their:

High accuracy for temperature below 200 C

Low drift

Quasi-linear resistance-temperature relationship

Chemical inertness

Wide operating range (from -270 to 660 C)

Suitability for precision applications

The two PT1000 are used to measure respectively:

The ambient temperature whose sensor is mounted in a weatherproof Macrolone

housing. This sensor can measure a range of measurement from -20 to +200 C.

figure 3: The ambient temperature sensor

The photovoltaic cell temperaturewhose sensor has been designed as adhesive foil

sensor for surface measurement. It is mainly used for temperature measurements of

solar systems. In our system, it is stuck to the rear side of the photovoltaic panel.

This sensor can measure a range of measurement from -20 to +150 C.


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figure 4: The photovoltaic cell temperature sensor

The sensor characteristic equation

The platinum sensors have a near linear resistance versus temperature function. Its transfer

function is given by the Callendar

Van Dusen equation which is described by two distinctpolynomial equations: one for temperatures below 0C and another for temperatures above0C. These equations are:

Where:

RT is the resistance at temperature T

R0 is the resistance at 0 C, in our case R0= 1000 A = 3.9083. 10

-3C-1

B= -5.775. 10-7C-2

C= -4.183. 10-12C-12

The last model give a precise result but it needs the use of numerical methods to calculate

the temperature from a known resistance. Whereas, including a numerical method into the

algorithm of a program can affect the performance of the real time case. Therefore, in this

work a simplified linear model is applied. This model eliminates the two last terms of the last

equation which are negligible compared to the other terms:

BTARPt

1000

Where A and B are constants that depend on the range of measured temperature.

A scientific article entitled RTD Interfacing and Linearization Using an ADuC8xx

MicroConverter deals with the choice of optimum values for A and B to minimize the error

band for different ranges of the temperature.

The next equation is the proposed one for this project and gives according to this article,

accurate results for temperature ranged from -20 to +100 C:


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100085,31000

TRPt

2.2.2 Irradiation sensor

To measure the solar irradiation the PVP is equipped by the Spektron 210 sensor. It is a

silicon sensor providing a proportional voltage-intensity of the solar irradiation relationship.

The output signal ranges from 0 to 150mV which correspond to a solar irradiation that

ranges from 0 to 1500 W/m2. So to measure such voltage with high precision, either a

measure instrument with high resolution should be used or the sensor signal should be

amplified before proceeding to the measures step.

The Spektron can be connected directly to a voltmeter or a data acquisition (DAQ) card. The

voltage measured by the Spektron 210 can be converted into the unit of irradiation (W/m),

using the calibration value imprinted on the sensor.

figure 5: Spektron 210 sensor

As the access to the irradiation sensor is difficult since it is exposed on the roof of the

laboratory, I proceed to calculate the calibration value by measuring the input voltage of the

sensor using a voltmeter for many different irradiations read from the old acquisition

system. So I take the average value of proportionality coefficient as calibration value.

V: Output voltage (mV) G: Solar irradiation(W/m2) V/G: proportionality coefficient

31,35 417,61 13320,89314

30,6 408,9 13362,7451

30,23 403,18 13337,08237

35,05 466,68 13314,6933

34,6 462,22 13358,95954

39,67 528,11 13312,5787739,38 525,4 13341,79787


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38,88 518,54 13336,93416

38,13 508,69 13340,93889

37,38 498,106 13325,46816

37,68 502,12 13325,90234

Table 1: Calculation of the calibration value of the Spektron 210 sensor

The average value of the proportionality coefficient = 13333,0614 133333

Thus Solar irradiation = 133333 Output voltage

2.3 Shortcoming of the existing DAS

The problem of the existed commercial data logging unit is that it cant save the historicalvalues of the solar irradiation: It just displays the current value. However as mentioned in

the introduction, the energy management strategy researches of the laboratory are based

on the historical values of the PVP parameters (during the last ten days).

Besides, such commercial data logging unit lacks flexibility compared with other data

acquisition systems. This flexibility in DASs is highly required in a laboratory where many

different approaches of research are carried out.

2.4 Project specification

The required work consists of the implementation of a new acquisition system with the

following features:

The DAS should be able to save the acquired data each one minute on a daily log

files;

These log files should be able to be read by Microsoft Excel.

The user can monitor the current value of the measured parameters.

The graphic interface for monitoring should be harmonious and display clearly the

target parameters. The user should be able to visualize the saved data and the line chart of the progress

of the measured parameters during any day when the data is stored.


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3 Project equipments

This chapter gives an overview of the data acquisition (DAQ) card used in the collection of

data, and gives a short introduction on the software to be used to control the data

acquisition system and to store the collected data, NI LabVIEW.

3.1 Data acquisition (DAQ) card

To acquire data from the sensor to the PC a data acquisition (DAQ) card is required. This card

is a way to measure sensor signals and transfer the data into a computer. In this part, firstly,

various aspects of a DAQ card are explained. After that, an overview of the DAQ card KUSB-

3108 used for this project is given.

3.1.1 Features of KUSB-3108 card

The data acquisition system provided for this project is the Keithley KUSB-3108, which is a

USB-based data acquisition module. This model is a low-cost, multifunctional data

acquisition system which is very suitable for this project for many reasons:

The Keithley KUSB-3108 Series brings true plug-and-play data acquisition to

computers that contain Universal Serial Bus (USB) 2.0 and 1.1 ports.

The input resolution of the KUSB-3108 module is 16-bits. In fact, the resolutionof theconverted signal is a function of the number of bits the analog to digital converter

ADC uses to represents the digital data. The higher the resolution, the higher the

number of divisions the voltage range is broken into, and therefore, the smaller the

detectable voltage changes.An ADC with a resolution of 16 bits can encode an analog

input to one in 216 different levels.

The gains of each channel are configurable in order to fix the effective input ranges of

the acquired data. In fact, with fixing the range of the input data the programmable

gate array PGA of the card configure this range as the full scale of the ADC for thecorresponding channel. Thats means the minimum change in voltage required to

guarantee a change in the output code level which called LSB (least significant bit,

since this is the voltage represented by a change in the LSB) can be configured

according to the target measured range so as to provide the maximum voltage

resolution of the ADC.

The voltage resolution of an ADC is equal to its overall voltage measurement range divided

by the number of discrete voltage intervals:


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where:

- N is the number of voltage intervals,

- EFSR is the full scale voltage range, given by, the upper and lower extremes

respectively of the voltages that can be coded.

Normally, the number of voltage intervals is given by, where M is

the ADC's resolution in bits.

Table 2lists the supported gains and effective input ranges of the KUSB-3108 modules.

Table 2: Effective input ranges of KUSB-3108 board

Note

For each channel the gain that has the smallest effective range that includes the

target signal should be chosen. For example, if the range of the analog input signal

is 0.75 V, the effective input range for this channel is then 1V, which provides

the best sampling accuracy for that channel.

The Model KUSB-3108 module features a variety of analog input channels, as well as

single-ended/differential analog input channels: KUSB-3108 modules support 16

single-ended analog input channels, or eight differential analog input channels. The

configuration of the channel type as single-ended or differential is done through an

adequate software such as LabVIEW.

The Model KUSB-3108 provides 2 analog output channels for high-resolution whichcan be used to feed the conditioning circuit.


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The module powered by the +5 volt USB supply from the computer. So no external

power is required.

The sampling frequency of the DAS is 50 KHz. According to the Nyquist theorem, themaximum frequency of the input signals should 25 KHz. Since the quantities

measured, temperature and irradiation, do not change very frequently in time, the

sample frequency is not a problematic for this project.

A 500V isolation barrier protects the computer and ensures a reliable stream of data.

Without isolation the computer is tied directly to the external sensor which can

potentially damage The PC.

Figure 4shows the screw terminal assignments on the KUSB-3108 modules.

Figure 6: Screw terminal assignments of the KUSB-3108 board

Note

While only three parameters measures are acquired, only three input analogchannels (channel 0, 1 and 2) are used. The use of three channels divides the


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sampling frequency of the DAS by three . Thats means the possible sampling

frequency for each channel is equal to 50KHz/3 = 16,66 KHz.

The card acquire only voltage signal measures, so to measure the two temperature

sensors a conditioning circuit to convert the PT1000 resistances into a proportional

voltage is needed. In this project, not all functionalities of the KUSB module will be used.

Figure 5 shows a block diagram of the KUSB-3108 modules. Note that bold entries indicate

signals you can access.

figure 7: Block Diagram of the KUSB-3108 Modules


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3.1.2 Wiring method:

The KUSB-3102 and KUSB-3108 modules support both single-ended and differential

configuration:

Single-ended: We choose this configuration when we want to measure high-level

signals, noise is not significant, the source of the input is close to the module, and all

the input signals are referred to the same common ground. When we choose the

single-ended configuration, all 16 analog input channels are available. Figure 8

illustrates how to connect an analog signal source to a KUSB-3108 module using

single-ended configuration.

figure 8: connecting single-ended voltage inputs (Shown for channel 1, 2 and 3)

Differential : We choose this configuration when we want to measure low-level

signals (less than 1 V), we are using an A/D converter with high resolution (greater

than 12 bits), noise is a significant part of the signal, or common-mode voltage exists.

So the differential configuration is the best way to connect wires when the input

voltage is a floating signal source.

When we choose the differential configuration, only eight analog input channels are

available. Figure 9 illustrates how to connect a floating signal source to a KUSB-3108

module using differential inputs. (A floating signal source is a voltage source that has

no connection with earth ground.)


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figure 9: Connecting Differential Voltage Inputs (Shown for Channel 0)

3.2 LabVIEW 8.6

DAQ hardware without software is of little use-and without proper controls the hardware

can be very difficult to program. The purpose of having appropriate software is the

following:

Acquire data at specified sampling rate;

Acquire data in the background while processing in foreground;

Stream data to and from disk;

Develop the graphic interface for monitoring and automatic saving of the collecteddata;

According to these specifications the chosen software is LabVIEW.

3.2.1 General presentation

LabVIEW is the emerging standard in visual programming based

instrumentation control systems. This application uses a datagraphical programming language (called G)where the processing figure 10:LabVIEW logo


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can be controlled using block diagrams and front panels instead of using lines of text to

create applications. In contrast to text-based programming languages, where instructions

determine program execution, LabVIEW uses dataflow programming, where the flow of data

determines execution.

In LabVIEW, you build a user interface by using a set of tools and objects. The user interface

is known as the front panel. You then add code using graphical representations of functions

to control the front panel objects. The block diagram contains this code. In some ways, the

block diagram resembles a flowchart.

LabVIEW is integrated fully for communication with hardware such as GPIB, VXI, PXI, RS-232,

RS-485, and plug-in DAQ devices.

Using LabVIEW, you can create test and measurement, data acquisition, instrument control,

data logging, measurement analysis, and report generation applications. You also can createstand-alone executables and shared libraries, like DLLs, because LabVIEW is a true 32-bit

compiler.

3.2.2 LabVIEW terms

It is worthy before beginning the presentation of the developed program, defining the

different term used by LabVIEW programmer.

Virtual instrument VI:

The combination of a DAQ board and LabVIEW software makes a virtual instrument or a VI,

because their appearance and operation imitate physical instruments, such as oscilloscopes

and multimeters. A VI can perform like an instrument and is programmable by the software

with the advantage of flexibility of logging the data that is being measured.

In LabVIEW programming all inputs are called controls and all outputs are called indictors.

Besides the subroutines are called subVIs.

Each VI contains three main parts: Front Panel: How the user interacts with the VI.

Block Diagram :The code that controls the program.

Icon/Connector: Means of connecting a VI to other VIs.

VI Front Panel

The front panel is the user interface of the VI. The front panel is built with controls and

indicators, which are the interactive input and output terminals of the VI, respectively.

Controls are knobs, pushbuttons, dials, and other input devices.


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Indicators are graphs, LEDs, and other displays. Controls simulate instrument input devices

and supply data to the block diagram of the VI. Indicators simulate instrument output

devices and display data the block diagram acquires or generates.

figure 11: Example of VI Front Panel

VI Block Diagram

The block diagram contains the graphical source code. Front panel objects appear as

terminals on the block diagram. Additionally, the block diagram contains functions and

structures from built-in LabVIEW VI libraries. Wires connect each of the nodes on the block

diagram, including control and indicator terminals, functions, and structures.


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figure 12: Example of VI Block Diagram

3.3 DT-LV Link

LV Link is a collection of Virtual Instruments (VIs) that give programmers working in LabVIEW

the ability to access KUSB data acquisition modules. This collection is consistent with the

design and layout of the LabVIEW DAQmx VIs to speed development time and minimize

learning curve issues.

The standard version of DT-LV Link supports all DT-Open Layers compliant USB and PCI

hardware, providing the ability to measure and control analog I/O, digital I/O, and

counter/timer signals, and stream the data to disk at full-speed. To get up and running

quickly, numerous application examples are provided with both versions of the software.

Since the source code is also provided, people can easily modify the examples to speed their

development time. By using DT-LV Link in the LabVIEW application, people can integrate all

the Data Translation and National Instruments hardware in the same application.

Three Levels of VIs

Similar to LabVIEWs DAQ interface, DT-LV Link provides three levels of Vis:

1) The Easy I/O VIs

These Vis perform high level data acquisition operations, such as setting up and acquiring

waveforms from multiple analog inputs. Easy I/Os can be run standalone or as part of a


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more complex application.

2) The Utility and Intermediate VIs

These VIs provide more hardware functionality and efficiency in developing applications

than the Easy I/O, but require more integration work. In addition, there are utility VIs to

perform tasks such as converting codes to volts and computing the range and gain given the

limits of a signal.

3) The Advanced VIs

These VIs are the lowest level of VIs for data acquisition. There are one Advanced VI for

each DT-Open Layers function. This provides people with access to the full functionality of

all supported Data Translation data acquisition boards as well as completes flexibility in

creating their application. Itsextremely easy to convert LabVIEW example VIs as well as

their own custom applications to use Data Translation hardware. K

As shown in the figure 13, DT-LV Link is both an interface and a library of VIs. The library

interface is consistent with the design and layout of LabVIEW. The library of VIs enables you

to access Data Translations data acquisition boards or any board that uses DT-Open Layers

device drivers.

figure 13: The role of DT-LV Link

When the device gets the data, it will be sent to the DT-Open Layers, then translated

through the DT-Link VI, the analog signals transfer into digital signals. And the LabVIEW can

analysis and process the data.


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4 Conception of the monitoring system

4.1 Data acquisition system

4.1.1 Testing data acquisition with LabVIEW

As a first step, I begin by testing the acquisition by LabVIEW using the KUSB card. I put in the

analog input channel a precise voltage of 5V after preparing a block diagram on LabVIEW for

this purpose based on the DT-LV Link Library. The prepared diagram consist in acquiring

1000 samples of this voltage with the full scale of the ADC (-10 to 10 V) and the full sampling

frequency capacity of the board (50 KHz) using the single-ended wiring method. Besides, it

calculates the average value of the acquired measures.

figure 14: The prepared Block diagram to test the KUSB board

figure 15: The line chart of the collected measures


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This line chart shows that the KUSB borad genarates a little noise. This noise can be

considred as a white noise.

The averge value of the 1000 collected samples = 4.99949 V. So, the mean of the white noise

is equal to: = 5- 4.99949 = 0,00051 V = 0.51 mV.

As it is mentionned in the datasheet KUSB borad, this noise is mainly generated by theamplifier and the ADC.

4.1.2 Virtual instrument for solar irradiation acquisition

Acquiring the voltage of the irradiation sensor is very simple if I use the previous VI. But the

result as it is shown in the following graph is very noisy and dont give a precise voltage.

figure 16: The acquired input of the solar irradiation sensor

To reduce this noise I have followed the following steps:

1. For the hardware part:

I wire the voltage source of the sensor to analog input channel 0 using the

differential configuration. In fact, according to the datasheet of the KUSB the

differential wiring method is recommended when the measured signal low-level

signals (less than 1 V). In addition, to the use of differential wiring method, I need to

configure the card from the block diagram of the VI for this purpose.

As the voltage of the irradiation sensor ranges from 0 to 150mV it is worthy to

configure the used channel of the card for this range. In fact, as mentioned above in

the presentation of the features of the card, the lower is the range configuration of

the ADC the more precise is the input of the ADC. From the table 2 listed above, the

most suitable gain for our input range is 100 which correspond to an analog input

ranges from -100mV to 100mV.


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2. For the software part:

As the previous task is not sufficient to obtain an acceptable noise I choose to use a

simple algorithm to eliminate the false values. These false values can be due to a false

interpretation of the analog input values by the ADC which is configured to acquire

negative and positive values. Unfortunately, this configuration cant be changed for this

card.

This algorithm should be as simple as possible with the least complexity to conserve the

real time acquisition case.

The algorithm is

s=0;

for i=1:n

s=s+x(i);

end

m=s/n;

x(1)=m;

for i=2:n

if abs(x(i)-m)>(m/20)

x(i)=x(i-1);

end

end

m=x(n)+ 0,00051;

4.1.3 Virtual instrument for temperature acquisition

4.1.3.1 Temperature conditioning circuit

The selected temperature sensor is a resistive RTD sensor which provides a variation in

resistance as the temperature changes. As the Data Acquisition System is unable to measure

the changes in resistance, a conditioning circuit is needed to obtain an output voltage

proportional to the resistive variation of the heat sensor.

4.1.3.1.1 Sensing stage

To convert the variation in resistance to a variation in voltage an electronic circuit with an

operational amplifier is the proposed solution. In fact, to reach this purpose, it is needed to

pass the sensor resistance by a fix current. The most suitable solution to provide a fix current

Calculating the average value

Initialization of the first sample with the average value

Checking if the difference between the

current value and the previous value < 5 %

Adjustment of the offset of the

card


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is the use of an operational amplifier. According to the diagram from figure 17 the output

voltage has to be:

=

= 0,000549

figure 17: Temperature sensor stage circuit

The maximum current processed by the sensor to depreciate self heating should be 1 mA,

according to specifications. A current of 0.6mA has been selected.

=

=5V

= 0,6 mA

= 8,33k [ 4.1]

The chosen resistance value is 9,1 kbecause it is the nearest resistance value of the

existing standard resistor.

The equations of PT1000 has been used to find the resistance of sensor whit maximal and

minimal temperature of measurement range (-10C a 60C).

= 0C

= 1000

= 40C

= 961,5

= 55C

= 1231

Consequently the maximal and the minimal voltage for the previous resistances and

according to the output voltage equation shown previously result in:

= 10C = 961,5 = 0,000549 961,5 = 0,527 V

= 60C

= 1231

= 0,000549 1231 = 0,678 V


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For all of these calculations, the final sensing circuit implementation has to result the ones

showed in

.

4.1.3.1.2 Filtering stage

As it is shown in the figure 18 the problem of the previous circuit that the operational

amplifier generates an important noise that can affect the real value of the heat sensor input.The problem can be solved in the software part by the conception of a numeric filter but to

decrease the complexity of the developed program, it is worthy to integrate the filtering stagein the electronic circuit.

figure 18: The input of the operational amplifier

The output signal will be filtered using a low pass filter (LPF) to eliminate interferences. This

LPF will filter out frequencies below .Hz(rest some calculation)

4.1.3. The final voltage conditioning circuit


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figure 19: The voltage conditioning circuit

figure 20: The carried out circuit

As it is shown in the figure 21 which is presented in the same scale of the figure 18, the filter

have eliminate nearly all the noise and gives a perfect result.


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figure 21: The input of the circuit with the filtering stage

4.2 Data logging

When the calibration procedure is completed, the calculated values are displayed

on the monitor. Also, the measurements performed every 1 min are stored on the

PC hard disk, in files named with the current date. These files contain the exact time of the

measurement along with each measured parameter identification and value.

Through this part, I will describe the way that I proceeded to create the log files which save

the data of the three sensor parameters and to open these files from the monitoring

interface or from the excel software.

4.2.1 Creating log files

LabVIEW provides an easy-to-use application and several functions to record data acquired

from the DAQ card in real time.

For data-logging applications, LabVIEW offers built-in functions to choose how data files are

created. The developer have the choice to select from basic text files to compact binary files

and user standard spreadsheet programs such as Microsoft Excel to view and interact with

his data.

For this project I have chosen the Technical Data Management Streaming (TDMS) as

extension for log files. This extension is introduced by National Instruments for many usefulpurposes. In fact the TDMS format:

gives more effective and accurate data storage than the traditional format like txt.

creates a file composed by three sheets: the first sheet to display the header

information, the second sheet to display logged data and the third sheet to display

the line chart for the corresponding data.

may be opened in LabVIEW, of course, and in NI DIAdem which is a software tool for

managing, analyzing, and reporting data in log files.

Can be read by Microsoft excel by adding a plug-in provided by National Instrument.

This characteristic provides for the researcher the ability to easily use the logged

data into their researches.


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The procedure of developing this part consists of storing the acquired data in a log file

having the corresponding date as name. The storing action consists of creating a new line in

the TDMS file that the first case is devoted for the instant of the storage, the second one is

devoted for the order of the stored line and the other three cases are devoted to store the

three acquired parameters. When the date change another log file will be created with this

new date as name.

4.2.2 Opening log files

Since I have organized the log files with the date of the target data I take advantage of this

option to open the log files. In fact, I prepared a small box in the front panel in which I placed

a label to enter the date of the target log file and a Boolean control button to order the

opening of the file.

Boolean controls have mechanical actions, which control how activation with the mouse

affects the value of the control. In order to affect the true value for the Boolean control only

when the button is pushed to open a log file I select the Switch until released as button

behaviors. Thats means the value of the control changes only so long as the mouse button is

held down. When the mouse button is released, the control returns to its default value. This

behavior is not affected by how often the VI reads the control.

In the block diagram part I put all the functions used for the conception of the opening box

in a while loop which verify each milliseconds if the Boolean control button is pushed inother word if the value of the Boolean control is true. If this value is true and the user have

entered the date of the target log file a case structure will be activated and give the

permission for the TDMS function to open the file.


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4.3 The graphic interface and tests

The final developed graphic interface is shown in figure 22. The measurements of all sensors

described in last sections, collected in a specific day, are illustrated in figure 23. A part of the

LABVIEW program code is shown in 24.

figure 22: The developed graphic interface


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Conclusion

The current report presents the different phases to perform the monitoring system of thephotovoltaic installation.

Firstly, I dealt with the project context. In this part, I presented the different components ofthe installation and principally the sensors features on which I have worked. Besides, I

explained the project specifications. After that, I presented the different software andhardware equipments used in this work. These precedent parts facilitated the accomplishment

of the target work as they presented with detail the project context and equipment.In the conception of the monitoring system part, I proceed by acquiring each parameters aloneand attributing the necessary corrections to reduce the signal-to-noise ratio.

After acquiring the target parameters I developed a graphic program to save them each oneminute in a daily log file. So the fruit of all this work is a graphic interface which shows

clearly the value of the different parameters and their progressions during the day and allowsthe open of the logged file.

The research in the laboratory can implement the algorithm of forecasting the photovoltaicinstallation parameters directly in the prepared virtual instrument. Besides, they can

implement a program in this virtual instrument to manage the use of solar energy andcommand the optimal distribution of energy using the KUSB board.