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A low-cost computer-controlled Arduino-based educational laboratory system for teaching the fundamentals of photovoltaic cells
This article has been downloaded from IOPscience. Please scroll down to see the full text article. 2012 Eur. J. Phys. 33 1599 (http://iopscience.iop.org/0143-0807/33/6/1599) View the table of contents for this issue, or go to the journal homepage for more
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IOP PUBLISHING
EUROPEAN JOURNAL OF PHYSICS
Eur. J. Phys. 33 (2012) 1599–1610
doi:10.1088/0143-0807/33/6/1599
A low-cost computer-controlled Arduino-based educational laboratory system for teaching the fundamentals of photovoltaic cells K Zachariadou, K Yiasemides and N Trougkakos Technological Educational Institute of Piraeus, P Ralli and Thivon 250, 12244 Egaleo, Greece E-mail:
[email protected]
Received 1 June 2012, in final form 30 July 2012 Published 11 September 2012 Online at stacks.iop.org/EJP/33/1599 Abstract
We present a low-cost, fully computer-controlled, Arduino-based, educational laboratory (SolarInsight) to be used in undergraduate university courses concerned with electrical engineering and physics. The major goal of the system is to provide students with the necessary instrumentation, software tools and methodology in order to learn fundamental concepts of semiconductor physics by exploring the process of an experimental physics inquiry. The system runs under the Windows operating system and is composed of a data acquisition/control board, a power supply and processing boards, sensing elements, a graphical user interface and data analysis software. The data acquisition/control board is based on the Arduino open source electronics prototyping platform. The graphical user interface and communication with the Arduino are developed in C# and C++ programming languages respectively, by using IDE Microsoft Visual Studio 2010 Professional, which is freely available to students. Finally, the data analysis is performed by using the open source, object-oriented framework ROOT. Currently the system supports five teaching activities, each one corresponding to an independent tab in the user interface. SolarInsight has been partially developed in the context of a diploma thesis conducted within the Technological Educational Institute of Piraeus under the co-supervision of the Physics and Electronic Computer Systems departments’ academic staff. (Some figures may appear in colour only in the online journal)
1. Introduction
During the last few decades, as manufacturing costs have decreased and the world’s energy demands and the cost of conventional energy have risen, photovoltaic technology has grown c 2012 IOP Publishing Ltd Printed in the UK & the USA 0143-0807/12/061599+12$33.00
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in popularity throughout the world. Thus, photovoltaic technology is an ideal educational topic for teaching fundamental concepts of semiconductors while keeping students informed of current engineering trends as well as promoting renewable energy technologies. The system that we have developed (SolarInsight) exploits the attractiveness of photovoltaic technology in order to motivate students to learn fundamental concepts of physics and data analysis. The system and the teaching activities have been designed by placing emphasis on engaging students to explore the scientific methodology of formulating testable hypotheses, designing and running experiments and then recording, analysing and interpreting the experimental data in order to draw scientific conclusions. SolarInsight is a low-cost and fully computer-controlled educational laboratory system. It runs under the Windows operating system and is composed of a data acquisition/control board, a power supply and processing boards, sensing elements, a graphical user interface and data analysis software. The data acquisition/control board is based on the open source electronics prototyping platform Arduino [1]. The graphical user interface and communication with Arduino is developed in C# and C++ programming languages respectively, by using the environment Visual Studio 2010 Professional [2], freely available to students through Microsoft’s DreamSpark initiative. Finally, the data analysis is performed by using the open source, object-oriented framework for large scale data analysis developed at CERN, ROOT [3]. SolarInsight proposes a new approach to educational methodology and instrumentation so that educational institutions develop by themselves, according to their specific educational needs, laboratory experiments that will be flexible, educationally reliable and inexpensive. In this concept, it has been designed and developed in order to incorporate the following main features: (a) to be fully computer controlled in order to accelerate the experimental data acquisition time and to allow enough time for meaningful learning; (b) to support both real experimental activities and simulations in a scientifically consistent unity; (c) to provide experimental data analysis tools such as the graphical display of data and curve fitting techniques; (d) to be user-friendly, modular and easily handled; the apparatus consists of distinct boards, each one having well defined operations easily recognized by the students. Moreover, in contrast to the laboratory devices commercially available, the system’s functionalities can be easily and cheaply modified according to the specific educational requirements of the instructor; (e) the graphical user interface (GUI) to be organized in independent tabs each one corresponding to a different teaching activity of increasing difficulty having well defined objectives. The object oriented nature of C# and C++ programming languages that have been used to develop the GUI and the communication with the microcontroller, allows easy addition of new teaching tabs and/or modification of the existing ones in order to fit to the instructor’s specific teaching requirements; (f) to be light, small in size, compact and robust; (g) to be inexpensive; it costs no more than one hundred Euros, much cheaper than educational laboratory systems commercially available. Currently, SolarInsight supports five teaching activities (four experimental and one simulation activity): In the first three laboratory activities, students (a) explore experimentally the environmental effects on the response of a commercial photovoltaic panel with the aid of the computer controlled servo motor and the dimmable light source of the SolarInsigtht apparatus
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and (b) they gain experience in plotting, interpreting and fitting their experimental data. The fourth teaching activity is a simulation activity; it introduces students to the concept of using a theoretical model as a tool to predict the results of an experiment. For this, students use the experimental data acquired in the early teaching activities in order to determine the unknown parameters of the theoretical model of the photovoltaic panel and then they use the theoretical model in order to simulate the response of the panel under different temperature conditions. In the final teaching activity, students are encouraged to design their own experiments in order to improve the theoretical model, or/and to pose testable hypotheses and conduct the necessary experimental procedure that will test their hypotheses and will lead to quantitative conclusions. Bearing in mind that the system is aimed to be used in university physics laboratories that educate hundreds of students every year, we have placed emphasis on the production cost: In order to develop a low-cost and reliable system we have chosen to use the Arduino open source electronics prototyping platform that provides a single-board microcontroller with an AVR CPU that can be programmed using an open source programming language and the Arduino development environment. For the current project, we have chosen among the several board versions the Arduino UNO [4] that features a high performance and low-power CMOS 8 bit microcontroller (AVR ATMega328. ATMega328). Besides its technical advantages and its low-cost, Arduino platform is an open source and user-friendly programming environment accompanied by numerous libraries, tutorials and examples. Therefore it is also suitable to undergraduate students that wish to conduct a diploma thesis on electronics or computer engineering. Moreover, the Arduino board can easily be programmed merely by uploading the developer’s code without using any additional hardware. Therefore, the functionalities of systems that have been developed on the Arduino platform can easily and inexpensively be modified in order to fit the specific educational needs of the instructors. SolarInsight has been partially developed in the context of the diploma thesis [5] of one of the authors of the current article. The diploma thesis has been conducted within the Technological Educational Institute of Piraeus under the co-supervision of the Physics and Electronic Computer Systems departments’ academic staff. The SolarInsight apparatus architecture as well as the implemented teaching activities are described in the following sections. 2. The system architecture
We have designed the laboratory apparatus (figure 1) to be as small as possible; it weighs less than 2 kg and its dimensions are 22 cm × 20 cm × 10 cm, thus it is portable and fits on the top of a laboratory desk along with a PC station leaving the necessary space for textbooks. It consists of four different boards, each one having well defined operations easily recognised by the students, interconnected by flat cables and fixed on a Plexiglas base: the sensor unit (SU), the power supply unit (PSU), the processing unit (PU) and the control unit (CU). The SU comprises the photovoltaic panel and it is contained within an opaque enclosure in order not to be influenced by environmental light fluctuations. The overall layout of the SolarInsight apparatus and a simplified schematic (top view) of its four boards are shown in figure 1. The CU is an Arduino UNO [4], which features the CMOS 8 bit microcontroller AVR ATMega328 and has 14 digital input/output pins, 6 analogue inputs, a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a reset button. The microcontroller on the board is programmed using the Arduino programming language and the Arduino development environment processing, a language based on Java. The board connected to the PC through USB acquires data from the sensors and the photovoltaic panel, controls the servo-motor and the digital potentiometer and performs operations.
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Figure 1. Left: the SolarInsight apparatus. Right: a simplified schematic (top view) of the SolarInsight boards.
The SU comprises a commercially available photovoltaic panel consisting of four photovoltaic cells wired in series, two 3 W high intensity LEDs wired in series and mounted on a large heat sink, a programmable high resolution light-to-frequency converter (TSL230R) to report the light intensity to the CU, a digital thermometer (DS18B20) for measuring the temperature of the photovoltaic panel and report it to the CU, and a micro analogue servo motor that tilts the photovoltaic panel with respect to the light source. The PSU connects to mains electricity through a 12 V 2 A dc wall adapter and powers the circuit. It has two functionalities: regulating the maximum current for the LED lighting at 700 mA and the light intensity of the LEDs using pulse-width modulation by switching a power MOSFET (RFP30N06LE) connected in series to earth. The PU is shown schematically in figure 2. A dual operational amplifier chip (MCP602) is used in two different configurations: as a voltage multiplier that scales and feeds the voltage of the photovoltaic panel to one of the ADCs of the Arduino and as a current to voltage converter connected to the negative terminal of the photovoltaic panel that scales and converts the current provided by the photovoltaic panel to a voltage level that the Arduino’s second ADC can measure. Connected to the cathode of the photovoltaic panel is also a digitally programmable 100-tap 1 k potentiometer (CAT5113) controlled by the Arduino which acts as a variable load for the photovoltaic panel. The user interface (UI) has been developed in C# by using Microsoft Visual Studio 2010 Professional, freely available to students through the DreamSpark program. The UI communicates with the Arduino and runs in batch mode the C++ interpreter (CINT) of the CERN ROOT framework that in turn executes C++ scripts that analyse the acquired data; by using the CINT interpreter the compile and link cycle is dramatically reduced facilitating rapid development. We have placed emphasis on designing a graphical user interface that is easy for the students to use and modular. Currently it consists of five independent tabs, described in the next sections, each one corresponding to a different experiment. CERN ROOT is an open source object oriented framework with all the functionality needed to handle and analyse large
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Figure 2. Simplified schematic of the processing unit (PU).
amounts of data in a very efficient way. Having the data defined as a set of objects, specialized storage methods are used to get direct access to the separate attributes of the selected objects, without having to touch the bulk of the data. Included are histogramming methods, curve fitting, minimization, simulation, graphics and visualization classes to allow the easy setup of an analysis system that can query and process the data interactively or in batch mode. Although ROOT is a framework that is specifically designed for large scale data analysis it is considered to be an appropriate solution even for smaller data sets because of its efficiency in storing and accessing subsets of data. 3. The laboratory activities
Currently the system supports five teaching activities each one corresponding to an independent tab of the user interface, extensively described in the following subsections. 3.1. The IV-PV tab
During the IV-PV laboratory activity students investigate the current versus voltage (I–V) and power versus voltage (P–V) response of a photovoltaic panel by exploring the curve fitting technique. For this, students measure the current and the voltage supplied by the photovoltaic panel under a variable load by adjusting (load (%) or sweep button) the digital potentiometer on the SU (figure 3). The panel’s temperature is measured by the digital thermometer sensor (get temperature button). During the experiment, the photovoltaic panel is placed in a position perpendicular with respect to the light direction emitted by the LEDs and the LEDs’ brightness is held constant.
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Figure 3. The IV–PV tab: investigation of the I–V and P–V characteristic curves by exploring the method of fitting a model to experimental data.
The current and voltage data are displayed in real time in tabular form on the graphical interface along with the calculated power. The visualization of the I–V and P–V data is possible via the plot buttons. The save (or open) button pops up a file selector box to allow students to choose the format, the file name and the target directory to store (or retrieve) their measurements. Students are guided to notice the difference between the I–V curve and the linear I–V response of a resistor and to recognize important performance parameters such as the greatest value of the current (short circuit current Isc) and the greatest value of the voltage (open circuit voltage Voc) delivered by the panel. In the P–V curve they should recognize the maximum power point (MPP) that represents the load for which the panel generates the maximum electrical power for the given conditions of irradiance and temperature. Moreover, students are guided towards identifying by trial and error (fitting function selection box) that the mathematical function that best describes the current versus voltage relation of their experimental measurements is of the general form: I(V) = A–B(exp(CV)–1). This form agrees with what they have learned from lectures or reading textbooks: according to the literature [6] the transcendental equation which models a photovoltaic panel is given by the following formula: V + Rs I V + Rs I q(V + Rs I) −1 − = IL − I0 · exp , (1) I(V ) = IL − Id − Rp nd kT Ns Rp where: IL is the photo-current generated by the panel, Id is the diode current for the case of a panel consisting of Ns cells wired in series, I0 is the reverse saturation current of the panel, q = 1.6 × 10−19 C is the electron charge, k = 1.38 × 10−23 J K−1 is Boltzmann’s constant, T is the absolute cell temperature, nd is the diode ideality factor that expresses the degree of ideality of the diode (nd = 1 for an ideal diode). The equivalent series resistance of the array (Rs) represents the internal losses due to the current flow whereas the equivalent parallel resistance (Rp) corresponds to the leakage current to earth (figure 4). Generally, the value of Rs is very low whereas the shunt resistance Rp is high. To simplify the model, we have considered that Rs = 0 and Rp = ∞ neglecting so the last term of the characteristic equation, which is relatively common.
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Figure 4. Equivalent circuit diagram of a photovoltaic cell: a current source in parallel with a
diode. In practice no solar cell is ideal so a shunt resistance (Rp) and a series resistance (Rs) are also included.
Given the above assumptions, the short circuit current equals the photocurrent (Isc = IL) and equation (1) leads to the following formula for the reverse saturation current of the panel: I0 =
Isc qVoc nd kT Ns
. (2) −1 exp Substituting equation (2) to equation (1) yields the following formula that models the response of the photovoltaic panel: −Voc ) 1 − exp q(V n kT N I(V ) = Isc · (3) d ocs . 1 − exp − ndqV kT Ns By using the ROOT framework, we have written scripts that implement equation (3) and perform the graphical representation as well as the fitting of the I–V and P–V curves (plot and fit buttons, respectively). For the curve fitting, ROOT’s least square regression has been used. For the number of cells (Ns) the value given by the manufacturer has been used (Ns = 4) in equation (3) whereas the diode’s ideality factor has been considered approximately equal to unity (nd ∼ 1). For temperature, students insert the measured value of the cell temperature (insert temperature field) and then they estimate by trial and error (fit button) the short circuit current (Isc) and open circuit voltage (Voc) so that the model fits best to the acquired experimental data. Moreover, by using the ROOT scripts students get from the best fitted P–V curve the MPP delivered by the photovoltaic panel (MPP (mW) field). The latter is used along with the measured light irradiance (irradiance(mW cm–2) field) and the value of the panel’s surface (given by the manufacturer: area(mm2) field) to calculate the maximum conversion efficiency of the photovoltaic panel, defined as the ratio of the maximum power produced by the panel over the incident light power (efficiency (%) field). For the case of maximum irradiance the efficiency has been measured to be ∼10%.
3.2. The angle dependence tab
During this laboratory activity, students investigate the dependence of the maximum electrical power generated by the photovoltaic panel on the panel’s orientation with respect to the
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Figure 5. The angle dependence tab: study of the photovoltaic panel’s response by varying the tilt
angle.
Figure 6. The intensity dependence tab: study of the dependence of the photovoltaic panel’s response on the irradiance by varying the intensity of the LEDs.
direction of the incident light. This is accomplished by keeping the intensity of the LEDs constant and slanting the photovoltaic panel (tilt (degrees) button) away from the direct perpendicular position (figure 5). For each tilt angle students acquire a complete set of data by adjusting the digital potentiometer, plot the PV curve (MultiPlot button) and perform a curve fitting (fit button) in order to evaluate the maximum power (MPP) delivered by the panel. Data sets can be saved in data files along with the angle, irradiance and temperature conditions and can later be retrieved in order to qualitatively compare the response of the panel under different tilt angles by overlaying the P–V curves (MultiPlot button). Furthermore, students can draw the maximum power versus tilt angle graph and comment on it. 3.3. The intensity dependence tab
During this laboratory activity (figure 6), students examine the dependence of the maximum power delivered by the photovoltaic panel on the incident light irradiance, by keeping the
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panel perpendicular to the light and varying the intensity of the dimmable LEDs on the SU (brightness (%) button). Students acquire a complete set of data for each light intensity value and evaluate the MPP delivered by the panel by fitting the theoretical model to their experimental data. Data sets can be saved in data files and the P–V curves under different intensity conditions can be compared graphically (Multiplot button). Furthermore, students can draw the MPP versus irradiance graph and comment on it. 3.4. The simulation tab
This lab activity introduces students to the concept of using a theoretical model to predict the results of an experiment. Specifically, students use the theoretical model of the photovoltaic panel for predicting its response under different temperature conditions. To implement this activity, we have written ROOT scripts that use a random number generator to generate a certain number of events (insert number of events field) based on the theoretical model of the photovoltaic panel. In addition, a random Gaussian noise is added to the generator (with zero mean and ∼5% standard deviation), for smearing the ideal photovoltaic response. The influence of the temperature on the current–voltage characteristic curve is modelled via its effect on the diode’s current (exponential part of equation (1)). The model has been improved in order to include the influence of the temperature on the reverse saturation current of the panel (I0(T)) [7]: 3 Eg (Tn ) 1 T 1 · . (4) · exp − I0 (T ) = I0 (Tn ) · Tn k Tn T In the above equation Tn is the temperature at nominal condition (Tn = 298 K), Eg is the band-gap energy of the semiconductor (Eg = 1.12 eV for polycrystalline Si at 25 ◦ C [6]) and I0(Tn) is the reverse saturation current of the panel at nominal temperature, given by equation (2) for T = Tn. Finally, the linear dependence of the short circuit current Isc(T) on the temperature has also been considered: Isc (T ) = Isc (Tn ) + K(T − Tn ) ,
for G = constant,
(5)
where the coefficient K has been estimated experimentally. During this laboratory activity, students compare the theoretical model described by equations (1) (where Rs = 0 and Rp = ∞), (2), (4) and (5) with the experimental data acquired at the nominal temperature, Tn and at the maximum possible irradiance, in order to determine the short circuit current Isc(Tn) and the open circuit voltage at nominal temperature Voc(Tn) (model adjustment button). (The diode’s ideality factor has been considered approximately equal to unity: nd ∼ 1.) Then, given the returned parameters (fit outputs field), they generate simulated data based on the implemented model, for different temperature conditions (insert temperatures box) at the same irradiance. A qualitative comparison of the photovoltaic panel response is possible by overlaying the corresponding P–V curves. Students should observe that the maximum power delivered by the photovoltaic panel decreases with increasing temperature. Shown in figure 7 are the simulated P–V curves for the cases of 40◦ , 60◦ , 70◦ and 80 ◦ C. 3.5. The test tab
This laboratory activity guides students to use the implemented theoretical model in order to develop their own testable hypotheses for investigation and then design and perform their
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Figure 7. The simulation tab: adjustment of the model parameters and prediction of the panel’s response under different temperature conditions.
Figure 8. The test tab: design and conduct experiments.
own experiments. For instance, by using the implemented theoretical model (simulation tab) they could notice that the open circuit voltage decreases with temperature. To test and explore quantitatively this prediction they could design the experiment of acquiring data under at least three different temperature conditions and of evaluating the open circuit voltage of the panel by fitting the theoretical model to their experimental data. Then, by using the Test tab they could graph the open circuit voltage versus temperature dependence by defining the correct range of values for the X and Y axes data (axes range field) as well as labels and units for the X and Y axes (axes labels fields). Finally, by performing a linear fit to their data (fit button) they could come up with the conclusion that the open circuit voltage decreases approximately linearly with the temperature and evaluate the open circuit voltage reduction rate (figure 8) by the slope. It is also possible to drive students to the challenge of improving the theoretical model. For instance, students could formulate the question and then experimentally investigate whether
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there is a linear dependence of the short circuit current on the irradiance: G for T = constant. (6) Isc (G) = Isc (Gn ) · Gn Students should design the procedure of experimentally testing the above assumption by measuring the short circuit current of the photovoltaic panel at different irradiance conditions under constant temperature. For this, they should use the intensity dependence tab to acquire data for at least three light intensity conditions under constant temperature and evaluate the short circuit current delivered by the panel by fitting the experimental data. Then, by using the test tab they could perform a linear fit to the short circuit current versus irradiance graph. Furthermore, students could estimate the short circuit current at the nominal irradiance (Isc(Gn)) from the slope of the fitted linear function. 4. Summary
We have presented an educational laboratory apparatus and associated teaching laboratory sessions (SolarInsight) for undergraduate curricula concerning electrical engineering and physics. The system and the teaching activities have been designed to assist students developing science process skills by learning fundamental aspects of semiconductors and electricity. The implementation of SolarInsight is based on the electronics prototyping platform (Arduino) for data acquisition and monitoring, whereas for communication with the Arduino, the graphical user interface and data analysis, the Microsoft Visual Studio and the ROOT frameworks have been combined. SolarInsight apparatus is a portable and inexpensive system: it measures 22 cm × 20 cm × 10 cm, weighs less than 2 kg and costs about 100 Euros. It has been developed in the context of a diploma thesis conducted within the Technological Educational Institute of Piraeus under the co-supervision of the Physics and Electronic Computer Systems departments’ academic staff. Currently, the system supports five laboratory sessions of increasing difficulty with the main teaching challenge of keeping the students’ interest undiminished so that they investigate in depth the fundamentals of a photovoltaic panel and gain enough experience in designing and conducting experiments. The modularity of the system allows its easy extension in order to support more laboratory activities. For this, the development of a theoretical model that implements the effect of the shunt and series resistance on the current–voltage characteristics of the panel is underway. Moreover, laboratory exercises that instruct fundamental concepts of data analysis such as fitting techniques, statistical distributions and multidimensional histogramming are under development. SolarInsight laboratory sessions along with a detailed teaching activity guide were first offered in fall 2011 to undergraduate students of the Faculty of Technological Applications enrolled in a general physics laboratory course. Positive results and feedback have been received and SolarInsight will be incorporated in the undergraduate laboratory curriculum taught in the Physics department of the Technological Educational Institute of Piraeus. Acknowledgment
We wish to acknowledge the assistance and encouragement from Professor G Prezerakos, Department of Electronic Computer Systems of the Technological Educational Institute of Piraeus.
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References [1] [2] [3] [4] [5]
Arduino http://www.arduino.cc/ Microsoft Visual Studio www.dreamspark.com A Data Analysis Framework http://root.cern.ch/drupal Arduino Uno board http://arduino.cc/en/Main/ArduinoBoardUno Trougkakos N 2012 Development of a data acquisition and analysis system for laboratory devices. Application: a laboratory device for studying photovoltaic cells Diploma Thesis Technological Educational Institute of Piraeus, in preparation [6] Nelson J 2003 The Physics of Solar Cells (London: Imperial College Press) [7] De Soto W, Klein S A and Beckman W A 2006 Improvement and validation of a model for photovoltaic array performance Sol. Energy 80 78–88
