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Design and implementation of a photovoltaic I-V curve tracer: Solar modules characterization under real operating conditions[1][edit | edit source]

  • PV performance >> solar irradiance, ambient temperature, and wind speed, in addition to solar module technologies >> usually evaluated by manufacturers under standard test conditions (STC: operating temperature of 25 °C, irradiance of 1000 W/m2 and AM = 1.5), which are almost never encountered[2][3][4][5][6][7]
  • the measure of the entire current-voltage (I-V) curve in short time requires a suitable data acquisition device
  • Research in the field of photovoltaic energy has grown rapidly over the last three decades relative to various aspects such as modeling, control, and physical extraction parameters[8][9][10][11][12]
  • The I-V curve extracted under real operating conditions requires taking the fast variation of climatic conditions into account[13] [12][14]
  • in order to reduce the effect of solar irradiance and temperature fluctuations, several techniques are used to automatically measure the I-V characteristic
    • used the capacitor charging cycle as an automatic variable load to measure the PV cell I-V curve by about a hundredth of a second. However, fluctuations affecting the obtained I-V curve were observed[15]
    • developed a technique based on the bipolar transistor to vary the load resistance and acquire 30 points of the PV module I_V characteristics in a relatively long time, 6–8 s [14]
    • based on an electronic load with the linear MOSFET APL501J to cover the complete range of PV panel I-V characteristic but the sampling time and measurement resolution were not indicated[16]
    • an electronic circuit based on several MOSFET IRFP150N connected in parallel to vary the load resistance and allow the acquisition of PV I-V characteristic, but the sampling time and measurement resolution were not indicated and remarkable fluctuations were observed on the I-V curve[17]
    • implemented a new method to vary the load resistance by using a MOSFET to measure an I-V curve of 36 points in a time average of 70 ms with visible fluctuations[18]
    • Arduino board and relays to switch between several resistances in order to vary the load resistance and extract the entire PV I-V curve. This solution was based on the use of relays characterized by a long response time. The I-V curve also showed visible fluctuations [7]
    • composed of several MOSFET IRF540N controlled by an Arduino board permitting to switch between different load resistance values.[1] The device is also composed of current, voltage, and temperature sensors which are compatible with Arduino board. The obtained IV curves are exploited to investigate the performance of a PV polycrystalline module. Several extraction methods are proposed in the literature to determine the physical parameters associated with single diode models[19] ,[10] conventional and alternative double diode models .[2][20] Thus, to evaluate the effect of temperature and solar irradiance on the module performance, its physical parameters are extracted. Ortiz-Condé and iterative extraction methods[21][22]are applied here to extract the physical parameters using the three cited models.
      • . The data acquisition process is started by measuring solar irradiance in the PV module plane using the solarimètre – SL200.
  • several commercial systems to characterize the PV modules, but they were relatively expensive and had a relatively long measuring time[23]

Design and Development of Low Cost, Portable, On-Field I-V Curve Tracer Based on Capacitor Loading for High Power Rated Solar Photovoltaic Modules[24][edit | edit source]

  • a novel design of low-cost, portable, fast, and precise Current-Voltage Curve Tracer (IVCT) with automated parameter extraction for high power rated Solar Photovoltaic (SPV) modules to effectively and efficiently determine the outdoor operating status of SPV power generators
  • IVCT is based on a Raspberry Pi microprocessor, a super-capacitive load, heat sinkable discharge resistances, and sensors with high sensitivity and resolution for measuring light irradiance, module temperature, current, and voltage.
  • Proposed IVCT can measure individual SPV modules without altering the electrical interconnection circuit, and the operating point can be shifted to 20 A and 45 V in few seconds
  • with accuracies of 1 to 3% for the region near maximum power
  • the SPV module’s long-term viability will inevitably undergo normal aging, resulting in a gradual decrease in power efficiency[25][26][27][28]
  • The output I − V curves of SPV modules are usually obtained using the Current-Voltage Curve Tracer (IVCT) device to verify SPV arrays’ electrical performance under actual operating conditions to detect anomalies and/or fault[29][30][31][32]
  • managing a large SPV power plant requires maintenance rescheduling and fault detection before failure, which is often needed to increase performance and reliability[33]
  • Many simple characteristic parameters can be derived directly from I −V curves, such as open-circuit voltage (Voc), short circuit current (Isc), maximum current (Im), and maximum voltage (Vm), as well as Fill Factor (FF)[34]
  • This study proposes a Super Capacitor load-based technique to achieve auto-sweep over other commonly used methods in the literature, allowing higher resolution data collection with adequate scan time to sweep the characteristic curve
  • Internet of Things (IoT) in conjunction with a super capacitive load-based IVCT device’s novel design to characterize high power rated SPV modules up to 900 Wp
  • In the resistive load approach, the SPV cell or SPV module is directly linked to a variable resistor or resistive load bank for characterization. A manually actuated rheostats or switch-controlled power resistors are used to change resistance step-wise[35].[36][37][38][39][40] The SPV characterization curve’s data points are logged by changing the electrical load’s resistance from minimum to maximum, which helps to move the trace from a short circuit to an open circuit. Electromechanical relays are used to choose the desired resistor combination, which reduces scan time.

Implementation of a plug and play I-V curve tracer dedicated to characterization and diagnosis of PV modules under real operating conditions[41][edit | edit source]

  • This paper outlines a low-cost equipment for tracing current-voltage characteristics of photovoltaic systems using a relay to connect the operating module under test to the varying load, which is a power MOSFET transistor.
  • this work include the design of an RC circuit to generate a steady gate-source voltage amplitude controlled via a PWM varying duty cycle
  • investigated the impact of PV module degradations such as discoloration, cell cracks, and PID on the I-V curve in the case of crystalline technology and compared to similar modules taken as reference.
  • Towards developing innovative solutions for sustainability, the integration of renewable energies as new sources of electrical energy is a necessity to meet the energy demands and reduce environmental climate changes.*
  • The lifespan of a photovoltaic module is considered one of its main desirable benefits. It is a parameter that defines the guarantees offered by the manufacturers of photovoltaic modules who are seeking enhancement in solar cells with reduced costs. During the periods of exposure, the PV module can undergo degradation manifested by a change in the values of their parameters and performances, which influences their long-term reliability[42][43]
  • Although failure has different impacts on the curve, correlating another diagnosis method is essential for classification. This curve based diagnosis method can be used with thermal imaging correlation to picture the hot areas in silicone crystalline modules in shading cells cases, or with Electroluminescence imaging for PID or cell cracked visualization.[44][45][46][47][48][49]
  • tech specification:
    • the curve tracer relies on a Power MOSFET
    • low-cost material and includes statistical processing for data quality with a partial system break
    • A low pass filter (RC circuit) for digital to analog conversion >> used as electronic load
    • The RC circuit is controlled via a PWM signal with varying duty-cycle
    • Its output is an analog signal in the range of 2 V to 5 V. It is directly acquired from the DAQ board.
    • prototype is installed at the system level (subsystem or module up to 20 A) with a flexible modular voltage measurement that consists of a voltage booster to increase the input voltage capacity of the developed curve tracer.
    • ,it can be remotely controlled and doesn’t need a battery
    • that the module under test is isolated from its string for a period less than one second to guarantee accurate measurements without affecting the total system performance.
    • The measurement system is composed of current, voltage, irradiation and temperature sensors, their conditioning circuits, and the command circuit.
    • I2C bus protocols
    • data is stored in the SD card
    • A 12 V AC/DC adapter is used as a power supply.
    • a 12 V to 5 V voltage regulator is used as a power supply for some circuits.
    • enclosed in a metallic box

A Review of I–V Tracers for Photovoltaic Modules: Topologies and Challenges[50][edit | edit source]

  • Steps or “ladder”. A deviation observed as steps or a “ladder” can be caused by partial shading, dust deposit, cracked cells, or a short circuit in the bypass diode.
  • Low current. An ISC below the nominal can be caused by the uniform deposit of dust or the normal degradation of the module.
  • Low voltage. A VOC lower than nominal can be caused by thermal module stress (hot spot or module temperature above STC), completely shaded cells, or bypass diode failure.
  • Rounder “knee”. If the inflection point of the curve or “knee” is rounder than that observed in a nominal curve, it may be the cause of aging of the module that can be evidenced by the change in the values of the series and parallel resistances of the model of a diode.
  • Slope reduction. The reduction of the slope on the upper part or “horizontal leg” of the I–V curve can be caused by a dust deposit located on the edge of a cell, due to a mismatch between the ISC of the cells of a module (a reference to the quality of the cells), due to the presence of currents through the parallel branch of the diode model (which appear as short circuits of cracked cells), or due to hot spots.
  • Increased slope. The increase in the slope in the right side or “vertical leg” of the I–V curve can be caused by the increase in the serial resistance of the module, or by excessive resistance of the connecting cables between modules.
  • tables and comparison

Measuring outdoor I–V characteristics of PV modules and systems[51][edit | edit source]

  • The cumulative installed capacity of photovoltaics has passed 1 TW, of which about two-thirds were only installed in the past five years.
  • figure 5
  • section 3.1

Design and implementation of an autonomous device with an app to monitor the performance of photovoltaic panels[52][edit | edit source]

  • This paper presents the design and implementation of a portable electronic device to measure the I-V and P-V curves of photovoltaic panels.
  • This instrument acquires solar radiation, ambient temperature, electric current, and voltage signals from a PV panel via a cellphone through a mobile application.
  • the device, capable of real-time characterization of PV panels up to 20 A and 500 V, features a 240 MHz Tensilica LX6 dual-core processor and 4 MB of storage memory
  • section 3.5 (cost)
  • proposed- 1000-1200 USD

References[edit | edit source]

  1. ↑ 1.0 1.1 H. Amiry, M. Benhmida, R. Bendaoud, C. Hajjaj, S. Bounouar, S. Yadir, K. Raïs, M. Sidki, Design and implementation of a photovoltaic I-V curve tracer: Solar modules characterization under real operating conditions, Energy Conversion and Management 169 (2018) 206–216. https://doi.org/10.1016/j.enconman.2018.05.046.
  2. ↑ 2.0 2.1 M.S. Ismail, M. Moghavvemi, T.M.I. Mahlia, Characterization of PV panel and global optimization of its model parameters using genetic algorithm, Energy Conversion and Management 73 (2013) 10–25. https://doi.org/10.1016/j.enconman.2013.03.033.
  3. ↑ E. Karatepe, M. Boztepe, M. Colak, Neural network based solar cell model, Energy Conversion and Management 47 (2006) 1159–1178.
  4. ↑ F. Ghani, G. Rosengarten, M. Duke, J.K. Carson, On the influence of temperature on crystalline silicon solar cell characterisation parameters, Solar Energy 112 (2015) 437–445. https://doi.org/10.1016/j.solener.2014.12.018.
  5. ↑ F. Khan, S.-H. Baek, Y. Park, J.H. Kim, Extraction of diode parameters of silicon solar cells under high illumination conditions, Energy Conversion and Management 76 (2013) 421–429. https://doi.org/10.1016/j.enconman.2013.07.054.
  6. ↑ A. Bouraiou, M. Hamouda, A. Chaker, M. Mostefaoui, S. Lachtar, M. Sadok, N. Boutasseta, M. Othmani, A. Issam, Analysis and evaluation of the impact of climatic conditions on the photovoltaic modules performance in the desert environment, Energy Conversion and Management 106 (2015) 1345–1355. https://doi.org/10.1016/j.enconman.2015.10.073.
  7. ↑ 7.0 7.1 A. Tihane, M. Boulaid, A. Ihlal, M. Nya, Design and Implementation of a Low Cost Automatic Variable Load and Data Acquisition for Characterization of Photovoltaic Modules Simultaneously, IREACO 9 (2016) 48. https://doi.org/10.15866/ireaco.v9i1.7831.
  8. ↑ D. Vatau, S. Musuroi, C. Barbulescu, M. Babescu, PV systems modelling and optimal control, Energy Conversion and Management 84 (2014) 448–456. http://dx.doi.org/10.1016/j. enconman.2014.04.032.
  9. ↑ S. Yadir, M. Benhmida, M. Sidki, E. Assaid, M. Khaidar, New method for extracting the model physical parameters of solar cells using explicit analytic solutions of current-voltage equation, in: 2009 International Conference on Microelectronics-ICM, IEEE, 2009: pp. 390–393. https://ieeexplore.ieee.org/abstract/document/5418599/?casa_token=ERZRqsDJVUQAAAAA:gnXDvG7M2XE2DYXtM8jAireTABhfUtoWXuTHR4rlKSwgEbkBgokBhg66PNq85P2VXr4RmvPl3L8 (accessed October 11, 2024).
  10. ↑ 10.0 10.1 J. Bai, S. Liu, Y. Hao, Z. Zhang, M. Jiang, Y. Zhang, Development of a new compound method to extract the five parameters of PV modules, Energy Conversion and Management 79 (2014) 294–303. http://dx.doi.org/10.1016/j.enconman.2013.12.041.
  11. ↑ N. Boutana, A. Mellit, S. Haddad, A. Rabhi, A.M. Pavan, An explicit I-V model for photovoltaic module technologies, Energy Conversion and Management 138 (2017) 400–412. https://doi.org/10.1016/j.enconman.2017.02.016.
  12. ↑ 12.0 12.1 A. Askarzadeh, L. Dos Santos Coelho, Determination of photovoltaic modules parameters at different operating conditions using a novel bird mating optimizer approach, Energy Conversion and Management 89 (2015) 608–614. https://doi.org/10.1016/j.enconman.2014.10.025.
  13. ↑ Y. Hishikawa, T. Doi, M. Higa, K. Yamagoe, H. Ohshima, Precise Outdoor PV Module Performance Characterization Under Unstable Irradiance, IEEE J. Photovoltaics 6 (2016) 1221–1227. https://doi.org/10.1109/JPHOTOV.2016.2571620.
  14. ↑ 14.0 14.1 T. Mambrini, Characterization of photovoltaic solar panels in real conditions of implantation and according to different technologies, Université Paris Sud-Paris XI (2014).
  15. ↑ D.T. Cotfas, P.A. Cotfas, D. Ursutiu, C. Samoila, Current-voltage characteristic raising techniques for solar cells. Comparisons and applications, in: 2010 12th International Conference on Optimization of Electrical and Electronic Equipment, IEEE, 2010: pp. 1115–1120. https://ieeexplore.ieee.org/abstract/document/5510373/ (accessed October 11, 2024).
  16. ↑ Y. Kuai, S. Yuvarajan, An electronic load for testing photovoltaic panels, Journal of Power Sources 154 (2006) 308–313. https://doi.org/10.1016/j.jpowsour.2005.04.016.
  17. ↑ H. Belmili, S.M. Ait Cheikh, M. Haddadi, C. Larbes, Design and development of a data acquisition system for photovoltaic modules characterization, Renewable Energy 35 (2010) 1484–1492. https://doi.org/10.1016/j.renene.2010.01.007.
  18. ↑ P. Papageorgas, D. Piromalis, T. Valavanis, S. Kambasis, T. Iliopoulou, G. Vokas, A low-cost and fast PV I-V curve tracer based on an open source platform with M2M communication capabilities for preventive monitoring, Energy Procedia 74 (2015) 423–438. https://doi.org/10.1016/j.egypro.2015.07.641.
  19. ↑ A. Chouder, S. Silvestre, N. Sadaoui, L. Rahmani, Modeling and simulation of a grid connected PV system based on the evaluation of main PV module parameters, Simulation Modelling Practice and Theory 20 (2012) 46–58. https://doi.org/10.1016/j.simpat.2011.08.011.
  20. ↑ X. Gao, Y. Cui, J. Hu, G. Xu, Z. Wang, J. Qu, H. Wang, Parameter extraction of solar cell models using improved shuffled complex evolution algorithm, Energy Conversion and Management 157 (2018) 460–479. https://doi.org/10.1016/j.enconman.2017.12.033.
  21. ↑ A. Ortizconde, F. Garciasanchez, J. Muci, New method to extract the model parameters of solar cells from the explicit analytic solutions of their illuminated characteristics, Solar Energy Materials and Solar Cells 90 (2006) 352–361. https://doi.org/10.1016/j.solmat.2005.04.023.
  22. ↑ S. Yadir, S. Assal, A. El Rhassouli, M. Sidki, M. Benhmida, A new technique forextracting physical parameters of a solar cell model from the double exponential model (DECM), Optical Materials 36 (2013) 18–21. https://doi.org/10.1016/j.optmat.2013.07.010.
  23. ↑ H. Amiry, M. Benhmida, R. Bendaoud, C. Hajjaj, S. Bounouar, S. Yadir, K. Raïs, M. Sidki, Design and implementation of a photovoltaic IV curve tracer: Solar modules characterization under real operating conditions, Energy Conversion and Management 169 (2018) 206–216.
  24. ↑ J. Sayyad, P. Nasikkar, Design and Development of Low Cost, Portable, On-Field I-V Curve Tracer Based on Capacitor Loading for High Power Rated Solar Photovoltaic Modules, IEEE Access 9 (2021) 70715–70731. https://doi.org/10.1109/ACCESS.2021.3078532.
  25. ↑ C. Huang, L. Wang, Simulation study on the degradation process of photovoltaic modules, Energy Conversion and Management 165 (2018) 236–243.
  26. ↑ H.I. Dag, M.S. Buker, Performance evaluation and degradation assessment of crystalline silicon based photovoltaic rooftop technologies under outdoor conditions, Renewable Energy 156 (2020) 1292–1300.
  27. ↑ J.E.F. da Fonseca, F.S. de Oliveira, C.W.M. Prieb, A. Krenzinger, Degradation analysis of a photovoltaic generator after operating for 15 years in southern Brazil, Solar Energy 196 (2020) 196–206.
  28. ↑ D.C. Jordan, T.J. Silverman, B. Sekulic, S.R. Kurtz, PV degradation curves: non‐linearities and failure modes, Progress in Photovoltaics 25 (2017) 583–591. https://doi.org/10.1002/pip.2835.
  29. ↑ P.K. Dash, N.C. Gupta, Effect of temperature on power output from different commercially available photovoltaic modules, International Journal of Engineering Research and Applications 5 (2015) 148–151.
  30. ↑ C.W. Riley, L.M. Tolbert, An online autonomous I–V tracer for PV monitoring applications, in: 2015 IEEE Power & Energy Society General Meeting, IEEE, 2015: pp. 1–5. https://ieeexplore.ieee.org/abstract/document/7286146/ (accessed October 16, 2024).
  31. ↑ Z. Chen, Y. Chen, L. Wu, S. Cheng, P. Lin, Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions, Energy Conversion and Management 198 (2019) 111793.
  32. ↑ Y. Hishikawa, T. Doi, M. Higa, K. Yamagoe, H. Ohshima, Precise outdoor PV module performance characterization under unstable irradiance, IEEE Journal of Photovoltaics 6 (2016) 1221–1227.
  33. ↑ M. Dhimish, Z. Chen, Novel open-circuit photovoltaic bypass diode fault detection algorithm, IEEE Journal of Photovoltaics 9 (2019) 1819–1827.
  34. ↑ J.E. Quiroz, J.S. Stein, C.K. Carmignani, K. Gillispie, In-situ module-level I–V tracers for novel PV monitoring, in: 2015 IEEE 42nd Photovoltaic Specialist Conference (PVSC), IEEE, 2015: pp. 1–6. https://ieeexplore.ieee.org/abstract/document/7355608/ (accessed October 16, 2024).
  35. ↑ A.A. Willoughby, T.V. Omotosho, A.P. Aizebeokhai, A simple resistive load IV curve tracer for monitoring photovoltaic module characteristics, in: 2014 5th International Renewable Energy Congress (IREC), IEEE, 2014: pp. 1–6. https://ieeexplore.ieee.org/abstract/document/6827028/ (accessed October 16, 2024).
  36. ↑ A. Rivai, N.A. Rahim, A low-cost photovoltaic (PV) array monitoring system, in: 2013 IEEE Conference on Clean Energy and Technology (CEAT), IEEE, 2013: pp. 169–174. https://ieeexplore.ieee.org/abstract/document/6775620/ (accessed October 16, 2024).
  37. ↑ A.A. Willoughby, M.O. Osinowo, Development of an electronic load IV curve tracer to investigate the impact of Harmattan aerosol loading on PV module pern2tkformance in southwest Nigeria, Solar Energy 166 (2018) 171–180.
  38. ↑ E.E. Van Dyk, A.R. Gxasheka, E.L. Meyer, Monitoring current–voltage characteristics and energy output of silicon photovoltaic modules, Renewable Energy 30 (2005) 399–411.
  39. ↑ E.E. Van Dyk, A.R. Gxasheka, E.L. Meyer, Monitoring current-voltage characteristics of photovoltaic modules, in: Conference Record of the Twenty-Ninth IEEE Photovoltaic Specialists Conference, 2002., IEEE, 2002: pp. 1516–1519. https://ieeexplore.ieee.org/abstract/document/1190899/ (accessed October 16, 2024).
  40. ↑ A. Rivai, N.A. Rahim, Binary‐based tracer of photovoltaic array characteristics, IET Renewable Power Generation 8 (2014) 621–628. https://doi.org/10.1049/iet-rpg.2013.0111.
  41. ↑ S. Sarikh, M. Raoufi, A. Bennouna, A. Benlarabi, B. Ikken, Implementation of a plug and play I-V curve tracer dedicated to characterization and diagnosis of PV modules under real operating conditions, Energy Conversion and Management 209 (2020) 112613. https://doi.org/10.1016/j.enconman.2020.112613.
  42. ↑ T. Tanaka, T. Hayashi, T. Nagayama, T. Yanagidaira, Y. Inui, Proposal of novel degradation diagnosis method for photovoltaic module employing xenon flash lighting system and detector capacitor, Energy Conversion and Management 186 (2019) 450–461. https://doi.org/10.1016/j.enconman.2019.02.059.
  43. ↑ A. Ndiaye, A. Charki, A. Kobi, C.M.F. Kébé, P.A. Ndiaye, V. Sambou, Degradations of silicon photovoltaic modules: A literature review, Solar Energy 96 (2013) 140–151. https://doi.org/10.1016/j.solener.2013.07.005.
  44. ↑ J.A. Tsanakas, L. Ha, C. Buerhop, Faults and infrared thermographic diagnosis in operating c-Si photovoltaic modules: A review of research and future challenges, Renewable and Sustainable Energy Reviews 62 (2016) 695–709.
  45. ↑ J. Hylský, D. Strachala, P. Vyroubal, P. Čudek, J. Vaněk, P. Vanýsek, Effect of negative potential on the extent of PID degradation in photovoltaic power plant in a real operation mode, Microelectronics Reliability 85 (2018) 12–18. https://doi.org/10.1016/j.microrel.2018.04.003.
  46. ↑ J. Šlamberger, M. Schwark, B.B. Van Aken, P. Virtič, Comparison of potential-induced degradation (PID) of n-type and p-type silicon solar cells, Energy 161 (2018) 266–276. https://doi.org/10.1016/j.energy.2018.07.118.
  47. ↑ M. Dhimish, V. Holmes, P. Mather, C. Aissa, M. Sibley, Development of 3D graph-based model to examine photovoltaic micro cracks, Journal of Science: Advanced Materials and Devices 3 (2018) 380–388. https://doi.org/10.1016/j.jsamd.2018.07.004.
  48. ↑ I. Berardone, J. Lopez Garcia, M. Paggi, Analysis of electroluminescence and infrared thermal images of monocrystalline silicon photovoltaic modules after 20 years of outdoor use in a solar vehicle, Solar Energy 173 (2018) 478–486. https://doi.org/10.1016/j.solener.2018.07.055.
  49. ↑ M. Dhimish, V. Holmes, B. Mehrdadi, M. Dales, The impact of cracks on photovoltaic power performance, Journal of Science: Advanced Materials and Devices 2 (2017) 199–209. https://doi.org/10.1016/j.jsamd.2017.05.005.
  50. ↑ Morales-Aragonés JI, Dávila-Sacoto M, González LG, Alonso-Gómez V, Gallardo-Saavedra S, Hernández-Callejo L. A Review of I–V Tracers for Photovoltaic Modules: Topologies and Challenges. Electronics 2021;10:1283. https://doi.org/10.3390/electronics10111283.
  51. ↑ Augusto A, Killam A, Bowden SG, Wilterdink H. Measuring outdoor I–V characteristics of PV modules and systems. Prog Energy 2022;4:042006. https://doi.org/10.1088/2516-1083/ac851c.
  52. ↑ Ordoñez A, Urbano J, Mesa F, Castañeda M, Zapata S, Quesada B, et al. Design and implementation of an autonomous device with an app to monitor the performance of photovoltaic panels. Energy Reports 2024;12:2498–510. https://doi.org/10.1016/j.egyr.2024.07.062.
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