Autonomous Multifunctional Measuring Device for Monitoring the Characteristics of Photovoltaic Modules

Abstract

The study provides a multifunctional measuring device that searches for the maximum energy output using a certain algorithm and calculates the fill factor and efficiency of a solar module. It also monitors the air temperature and relative humidity, the temperature of the solar module, the level of solar radiation, wind speed, and current and voltage of the solar module. An electrical circuit for measuring the current–voltage characteristic of photovoltaic modules is proposed. In addition, rechargeable batteries allowing measurements without connecting the device to a power supply ensure autonomy of the device. An algorithm is proposed for finding the point of maximum power of a photovoltaic module. The device is developed on the basis of an ATmega2560 microcontroller with additional sensors. The measuring device software sends all acquired data from the device to a computer to be saved in a database.

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REFERENCES

  1. 1

    Salas, V., Olias, E., Barrado, A., and Lazaro, A., Review of maximum power point tracking algorithms for stand-alone photovoltaic systems, Sol. Energy Mater. Sol. Cells, 2006, vol. 90, pp. 1555–1578.

    Article  Google Scholar 

  2. 2

    Odeh, S. and Behnia, M., Improving photovoltaic module efficiency using water cooling, Heat Transfer Eng., 2009, vol. 30, no. 6, pp. 499–505.

    Article  Google Scholar 

  3. 3

    Abdallaha, S. and Badranb, O.O., Sun tracking system for productivity enhancement of solar still, Desalination, 2008, vol. 220, nos. 1–3, pp. 669–676.

    Article  Google Scholar 

  4. 4

    Huynh, D.C., Nguyen, Th.A.T., Dunnigan, M.W., and Mueller, M.A., Maximum power point tracking of solar photovoltaic panels using advanced perturbation and observation algorithm, in Proceedings of the IEEE 8th Conference on Industrial Electronics and Applications (ICIEA), June 19–21, 2013, pp. 864–869.

  5. 5

    Sugiartha, N., Sugina, I.M., Agus Tri Putra, I.D.G., Indraswara, M.A., and Suryani, L.I.D., Development of an arduino-based data acquisition device for monitoring solar PV system parameters, Atlantis Highlights in Engineering (AHE), in Proceedings of the International Conference on Science and Technology, 2018, vol. 1, pp. 995–999.

  6. 6

    Vasel, A. and Iakovidis, F., The effect of wind direction on the performance of solar PV plants, Energy Convers. Manage., 2017, vol. 153, pp. 455–461.

    Article  Google Scholar 

  7. 7

    Skoplaki, E. and Palyvos, J.A., On the temperature dependence of photovoltaic module electrical performance: A review of efficiency/power correlations, Sol. Energy, 2009, vol. 83, pp. 614–624.

    Article  Google Scholar 

  8. 8

    Okoye, C.O. and Solyali, O., Optimal sizing of stand-alone photovoltaic systems in residential buildings, Energy, 2017, vol. 126, pp. 573–584.

    Article  Google Scholar 

  9. 9

    Tyagi, V.V., Rahim, N.S.A., Rahim, N.A., and Selvaraj, J.A.L., Progress in solar PV technology: Research and achievement, Renewable Sustainable Energy Rev., 2013, vol. 20, pp. 443–461.

    Article  Google Scholar 

  10. 10

    Komilov, A., Improving the design of a photoconverter with a heat sink using mathematical simulation, Appl. Sol. Energy, 2011, vol. 47, no. 3, pp. 229–233.

    Article  Google Scholar 

  11. 11

    Atia, Y., Zahran, M., and al-Hossain, A., Solar ell curves measurement based on labVIEW microcontroller interfacing, in Proceedings of the 12th WSEAS International Conference on Automatic Control, Modelling and Simulation, 2010, pp. 59–64.

  12. 12

    Touati, F., Al-Hitmi, M.A., Chowdhury, N.A., et al., Investigation of solar PV performance under Doha weather using a customized measurement and monitoring system, Renewable Energy, 2016, vol. 89, pp. 564–577.

    Article  Google Scholar 

  13. 13

    Gad, H.E. and Gad, H.E., Development of a new temperature data acquisition system for solar energy applications, Renewable Energy, 2015, vol. 74, pp. 337–343.

    Article  Google Scholar 

  14. 14

    Kuznetsov, P.N., Lyamina, N.V., and Yuferev, L.Yu., Remote monitoring device of electrical parameters and performance of solar power plant, Geliotekhnika, 2019, vol. 55, no. 3, pp. 249–257.

    Google Scholar 

  15. 15

    Rezky, A., Devara, K., Wardana, N.S., et al., Simple method for I-V characterization curve for low power solar cell using Arduino nano, E3S Web of Conf., 2018, vol. 67, p. 01020.

  16. 16

    Mohrem, A., Chetate, B., and Guia, H.E., Measurement and monitoring system with real time data logging based on microcontroller, Int. J. Meas. Technol. Instrum. Eng., 2018, vol. 7, no. 2, pp. 20–21.

    Google Scholar 

  17. 17

    El Hammoumi, A., Motahhir, S., Chalh, A., et al., Low-cost virtual instrumentation of PV panel characteristics using Excel and Arduino in comparison with traditional instrumentation, Renewables: Wind,Water Solar, 2018, vol. 5, no. 3. https://doi.org/10.1186/s40807-018-0049-0

  18. 18

    Skoplaki, E. and Palyvos, J.A., On the temperature dependence of photovoltaic module electrical performance: A review of efficiency/power correlations, Sol. Energy, 2009, vol. 83, pp. 614–624.

    Article  Google Scholar 

  19. 19

    Suryavanshi, S., Tiwari, Sh., and Kumar, Sh., Online monitoring and controlling of the PV generated solar power through AVR microcontroller ATmega16, in Proceedings of the 2nd International Conference for Convergence in Technology,2017, pp. 169–173.

  20. 20

    Aung, W.M.M., Win, Y., and Zaw, N.W., Implementation of solar photovoltaic data monitoring system, Int. J. Sci.,Eng. Technol. Res., 2018, vol. 7, no. 8, pp. 591–596.

    Google Scholar 

  21. 21

    Evstifeev, A.V., Mikrokontrollery avr semeistva mega. Rukovodstvo pol’zovatelya (Avr Microcontrollers of the Mega Family. User Guide), Moscow:Dodeka-XX1, 2007.

  22. 22

    I–V Tester for Solar Panels Testing. https://russian.alibaba.com/product-detail/portable-electrical-testers-pv-power-iv-curve-tester-energy-meter-for-solar-panels-testing-0516599644. html?spm=a2700.8699010.normalList.11.488b7d61qPIohH&s=p

  23. 23

    Metrel MI 3108 PS EurotestPV Measuring Installation. https://aredi.ru/metrel_mi_3108_ps_eurotestpv_ izmeritel_ustanovki_7488640130.html

  24. 24

    Davronov, Sh.R., Basic electrophysical characteristics of photoconverters, classification of measurement methods and calculation of current-voltage characteristics, Nauka Mir, 2018, vol. 61, no. 9 (61), pp. 37–40.

  25. 25

    Fermia, N., Granozio, D., Petrone, G., and Vitelli, M., Predictive and adaptive MPPT perturb and observe method, IEEE Trans. Aerospace Electron. Syst., 2007, vol. 43, no. 3, pp. 934–950.

    Article  Google Scholar 

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Correspondence to Sh. R. Davronov.

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Davronov, S.R. Autonomous Multifunctional Measuring Device for Monitoring the Characteristics of Photovoltaic Modules. Appl. Sol. Energy 56, 118–124 (2020). https://doi.org/10.3103/S0003701X2002005X

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Keywords:

  • maximum energy output
  • short circuit current
  • open circuit voltage
  • I–V characteristic
  • efficiency
  • fill factor
  • CIGS
  • solar radiation
  • temperature
  • measurement
  • monitoring