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Improving Solar Power Generation and Defects Detection Using a Smart IoT System for Sophisticated Distribution Control (SDC) and Independent Component Analysis (ICA) Techniques

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Abstract

These days, peoples are more concerned respects petroleum product energy and conservational issues caused on the power generation networks and renewable power resources at any other time. Amongst the renewable power resources, solar and windmill power generations are essential competitors. Photovoltaic modules additionally have moderately least transformation effectiveness. General system price was decreased utilizing significant productivity control which are made to determine for most significant achievable energy from solar PV array module utilizing MPPT procedures. Existing solar power generation likewise have the burden of being for the day outputs is less immediate introduction from natural sun radiation. By utilizing the Internet of Things (IoT) strategies for monitoring and controlling the solar power generation was significantly enhance the performance, and maintenance of the solar power plant. In this work explicitly argue advances IoT technique to increase output result of solar power generation at the system level. Covering turning the photovoltaic system in the position of maximum sunlight, obtaining significant available power obtained from the solar PV array and significant battery health management by using sophisticated distribution control (SDC) and independent component analysis techniques (ICA).The simulation work done under with the MATLAB software using proposed SDC and ICA logics the simulation results demonstrate the efficiency of the proposed method and its ability to track the maximum power of the PV panel. Over 97% efficiency achieved by using SDC and ICA methods.

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References

  1. 1.

    Wu, T., Wu, F., Redouté, J.-M., & Yuce, M. R. (2017). An autonomous wireless body area network implementation towards IoT connected healthcare applications. IEEE Access, 5, 11413–11422.

  2. 2.

    Adhya, S., Saha, D., Das, A., Jana, J., & Saha, H. (2016). An IoT based smart solar photovoltaic remote monitoring and control unit. In 2016 2nd international conference on control, instrumentation, energy & communication (CIEC).

  3. 3.

    El-Khozondar, H. J., El-Khozondar, R. J., Matter, K., & Suntio, T. (2016). A review study of photovoltaic array maximum power tracking algorithms. Renewables: Wind, Water, and Solar, 3, 3.

  4. 4.

    Ahmed, A. S., Abdullah, B. A., Abdelaal, W. G. A. (2016). MPPT algorithms: Performance and evaluation. In 2016 11th International conference on IEEEcomputer engineering & systems (ICCES).

  5. 5.

    Babaa, S. E., Armstrong, M., & Pickert, V. (2014). Overview of maximum power point tracking control methods for PV systems. Journal of Power and Energy Engineering, 2, 59–72.

  6. 6.

    Szura, D. (2017). Synthesis of dye-sensitized solar cells. Efficiency cells as a thickness of titanium dioxide. In EPJ web of conferences (Vol. 133, p. 03003).

  7. 7.

    Abadi, I., Soeprijanto, A., & Mustafa, A. (2014). Design of single axis solar tracking system at photovoltaic panel using fuzzy logic controller. In 5th Brunei international conference on engineering and technology (BICET). IEEE.

  8. 8.

    Kabalcı, E., Calpbinici, A., & Kabalci, Y. (2015). A single-axis solar tracking system and monitoring software. In 7th International conference on electronics, computers and artificial intelligence (ECAI). IEEE.

  9. 9.

    Kaur, T., Mahajan, S., Verma, S., Priyanka, & Gambhir, J. (2016). Arduino based low cost active dual axis solar tracker. In International conference on power electronics, intelligent control and energy systems (ICPEICES). IEEE.

  10. 10.

    Mirdanies, M., & Saputra, R. P. (2016). Dual-axis solar tracking system: A combined astronomical estimation and visual feedback. In International conference sustainable energy engineering and application (ICSEEA).

  11. 11.

    Mamun, N., Samrat, N. H., Mohamma, N., Islam, M.J., Abdullah-Al-Mamun, Prince, M. H. R., Adib, R., & Iftakherahmed, M. (2014). Multi-directional solar tracker using low-cost photosensor matrix. In International conference on informatics, electronics & vision (ICIEV).

  12. 12.

    Das, S., Mohanty, A., & Dey, A. (2015). An integrated design of an auto clean and cooling smart PV panel. International Journal of Innovations in Engineering and Technology (IJIET), 4, 80–88.

  13. 13.

    Tang, X., Quan, Z., Zhao, Y. (2010). Experimental investigation of solar panel cooling by a novel micro heat pipe array. In Energy and Power Engineering.

  14. 14.

    Visweswara, K. (2013). An investigation of incremental conductance-based maximum power point tracking for photovoltaic system. In 4th International conference on advances in energy research 2013. ELSEVIER.

  15. 15.

    Alam, S. M. S., & Rahman, A. N. M. M. (2016). Performance comparison of mirror reflected solar panel with tracking and cooling. In 4th International conference on the development in the in renewable energy technology (ICDRET), 29 February 2016.

  16. 16.

    Francis, E. D., Raghu, B., & VeraNarayana, D. (2016). Cooling techniques for photovoltaic module for improving its conversion efficiency. International Journal of Engineering Inventions.

  17. 17.

    Bijjargi, Y. S., Kale S.S., & Shaikh, K. A. (2016). Cooling techniques for photovoltaic module for improving its conversion efficiency: A review. International Journal of Mechanical Engineering and Technology (IJMET).

  18. 18.

    Alshehri, A., Parrott, B., & Outa, A. (2014). Dust mitigation in the desert: Cleaning mechanisms for solar panels in arid regions. In Smart grid conference (SASG), 2014 Saudi Arabia. IEEE.

  19. 19.

    Abhilash, B., & Panchal, A. K. (2016). Self-cleaning and tracking solar photovoltaic panel for improving efficiency. In 2nd International conference on advances in electrical, electronics, information, communication, and bio-informatics (AEEICB), 11 August 2016. IEEE Xplore.

  20. 20.

    He, G., Zhou, C., & Li, Z. (2011). Review of self-cleaning method for solar cell array. International Workshop on Automobile, Power and Energy Engineering Procedia Engineering, 16, 640–645.

  21. 21.

    Jaradat, M. A., Tauseef, M., Altaf, Y., Saab, R., Adel, H., Yousuf, N., & Zurigat, Y. H. (2015). A fully portable robot system for cleaning solar panels. In 10th International symposium on mechatronics and its applications (ISMA), 07 January 2016. IEEE Xplore.

  22. 22.

    Bohari, Z. H., Jamal, S. N. A. S. B., Sidin, S. B. M., & Nasir, M. N. M. (2015). Solar tracker module with automated module cleaning system. The International Journal of Engineering and Science (IJES).

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Correspondence to A. L. Mayilvahanan.

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Mayilvahanan, A.L., Stalin, N. & Sutha, S. Improving Solar Power Generation and Defects Detection Using a Smart IoT System for Sophisticated Distribution Control (SDC) and Independent Component Analysis (ICA) Techniques. Wireless Pers Commun 102, 2575–2595 (2018). https://doi.org/10.1007/s11277-018-5278-4

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Keywords

  • Internet of things (IoT)
  • Photovoltaic system
  • Maximum power point tracking (MPPT)
  • MATLAB simulator
  • Incremental conductance algorithm
  • Sophisticated distribution control
  • Independent component analysis