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Dual tracking of MPP for PV under diffuse irradiation and urban microclimatic conditions using sub-interval prediction via Bayesian-optimized regression

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Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Optimal power extraction from a photovoltaic (PV) plant in urban and rural areas varies due to microclimatic conditions and diffuse irradiations. Traditional methods such as Perturb and Observe (P&O) and Incremental Conductance (INC) are used in urban and rural PV power plants. Diffuse irradiation and microclimatic conditions are different in urban and rural areas. Moreover, one of two sides of the PV characteristics is used for tracking the maximum power point (MPP), i.e., either constant voltage or constant current region. In this paper, a Bayesian-optimized multiple regression-based dual tracking (BM-DT) is proposed for a sub-intervals prediction technique (SIPT) and the tracking of MPP is done using both sides of the PV characteristics. Moreover, the voltage step used for tracking the MPP is not a fixed quantity and is predicted using BM. The proposed BM-DT technique predicts sub-intervals from a specified initial voltage interval. Moreover, the maximum power point is tracked through interval and SIPT, based on microclimatic conditions. As tracking is done along both sides of the photovoltaics (PV), the performance with outstanding power extraction efficiencies at low, medium, and high power levels is 99%, 99.2% and 99.4%, respectively.
Rocznik
Strony
art. no. e153813
Opis fizyczny
Bibliogr. 30 poz., rys., tab., wykr.
Twórcy
  • Loyola-ICAM College of Engineering and Technology, Chennai 600034, India
  • Government College of Engineering, Bargur 635104, India
Bibliografia
  • [1] Pandey, A., Dasgupta, N. & Mukerjee, A. K. Design Issues in Implementing MPPT for Improved Tracking and Dynamic Performance. in IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics 4387-4391 (IEEE, 2006). https://doi.org/10.1109/IECON.2006.348008.
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  • [3] Jiang, Y., Abu Qahouq, J. A. & Haskew, T. A. Adaptive step size with adaptive-perturbation-frequency digital MPPT controller for a single-sensor photovoltaic solar system. IEEE Trans. Power Electron. 28, 3195-3205 (2013). https://doi.org/10.1109/TPEL.2012.2220158.
  • [4] Femia, N., Petrone, G., Spagnuolo, G. & Vitelli, M. Optimization of perturb and observe maximum power point tracking method. IEEE Trans. Power Electron. 20, 963-973 (2005). https://doi.org/10.1109/TPEL.2005.850975.
  • [5] Swaminathan, N., Lakshminarasamma, N. & Cao, Y. A fixed zone perturb and observe MPPT technique for a standalone distributed PV system. IEEE J. Emerg. Sel. Topics Power Electron. 10, 361-374 (2022). https://doi.org/10.1109/JESTPE.2021.3065916.
  • [6] Ali, A. I. M. Sayed, M. A. & Mohamed, E. E. M. Modified efficient perturb and observe maximum power point tracking technique for grid-tied PV system. Int. J. Electr. Power Energy Syst. 99, 192-202 (2018). https://doi.org/10.1016/j.ijepes.2017.12.029.
  • [7] Necaibia, S., Kelaiaia, M. S., Labar, H., Necaibia, A. & Castronuovo, E. D. Enhanced auto-scaling incremental conductance MPPT method, implemented on low-cost microcontroller and SEPIC converter. Sol. Energy 180, 152-168 (2019). https://doi.org/10.1016/j.solener.2019.01.028.
  • [8] Raiker, G. A., Loganathan, U. & Subba Reddy, B. Current control of boost converter for PV interface with momentum-based perturb and observe MPPT. IEEE Trans. Ind. Appl. 57, 4071-4079 (IEEE, 2021). https://doi.org/10.1109/TIA.2021.3081519.
  • [9] Abouadane, H., Fakkar, A., Sera, D., Lashab, A., Spataru, S. & Kerekes, T. Multiple-power-sample based P&O MPPT for fastchanging irradiance conditions for a simple implementation. IEEE J. Photovolt. 10, 1481-1488 (IEEE, 2020). https://doi.org/10.1109/JPHOTOV.2020.3009781.
  • [10] Ahmed, J. & Salam, Z. An improved perturb and observe (P&O) maximum power point tracking (MPPT) algorithm for higher efficiency. Appl. Energy 150, 97-108, 2015. https://doi.org/10.1016/j.apenergy.2015.04.006.
  • [11] Başoğlu, M. E. An enhanced scanning-based MPPT approach for DMPPT systems. Int. J. Electron. 105, 2066-2081 (2018). https://doi.org/10.1080/00207217.2018.1494332.
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  • [13] Pathak, P. K., Padmanaban, S., Yadav, A. K., Alvi, P. A. & Khan, B. Modified incremental conductance MPPT algorithm for SPVbased grid-tied and stand-alone systems. IET Gener. Transm. Distrib. 16, 776-791 (2022). https://doi.org/10.1049/gtd2.12328.
  • [14] Devi, V. K., Premkumar, K., Bisharathu Beevi, A. & Ramaiyer, S. A modified Perturb & Observe MPPT technique to tackle steady state and rapidly varying atmospheric conditions. Sol. Energy 157, 419-426 (2017). https://doi.org/10.1016/j.solener.2017.08.059.
  • [15] Zadeh, M. J. Z. & Fathi, S. H. A new approach for photovoltaic arrays modelling and maximum power point estimation in real operating conditions. IEEE Trans. Ind. Electron. 64, 9334-9343 (2017). https://doi.org/10.1109/TIE.2017.2711571.
  • [16] Ahmed, M., Abdelrahem, M., Harbi, I. & Kennel, R. An adaptive model-based MPPT technique with drift-avoidance for gridconnected PV systems. Energies 13, 6656-6680 (2020). https://doi.org/10.3390/en13246656.
  • [17] Li, Q. et al. An improved perturbation and observation maximum power point tracking algorithm based on a PV module fourparameter model for higher efficiency. Appl. Energy 195, 523-537 (2017). https://doi.org/10.1016/j.apenergy.2017.03.062.
  • [18] Peng, L., Zheng, S., Chai, X. & Li, L. A novel tangent error maximum power point tracking algorithm for photovoltaic system under fast multi-changing solar irradiances. Appl. Energy 210, 303-316 (2018). https://doi.org/10.1016/j.apenergy.2017.11.017.
  • [19] Li, S., Ping, A., Liu, Y., Ma, X. & Li, C. A variable-weatherparameter MPPT method based on a defined characteristic resistance of photovoltaic cell. Sol. Energy 199, 673-684 (2020). https://doi.org/10.1016/j.solener.2020.02.065.
  • [20] Yap, K. Y., Sarimuthu, C. R. & Lim, J. M.-Y. Artificial intelligence based MPPT techniques for solar power system: A review. J. Mod. Power Syst. Clean Energy 8, 1043-1059 (2020). https://doi.org/10.35833/MPCE.2020.000159.
  • [21] Kermadi, M. & Berkouk, E. M. Artificial intelligence-based maximum power point tracking controllers for photovoltaic systems: Comparative study. Renew. Sustain. Energy Rev. 69, 369-386 (2017). https://doi.org/10.1016/j.rser.2016.11.125.
  • [22] Çelik, Ö. & Teke, A. A hybrid MPPT method for grid connected photovoltaic systems under rapidly changing atmospheric conditions. Electr. Power Syst. Res. 152, 194-210 (2017). https://doi.org/10.1016/j.epsr.2017.07.011.
  • [23] Tang, S. et al. An enhanced MPPT method combining fractionalorder and fuzzy logic control. IEEE J. Photovolt. 7, 640-650 (2017). https://doi.org/10.1109/JPHOTOV.2017.2649600.
  • [24] Bataineh, K. Improved hybrid algorithms-based MPPT algorithm for PV system operating under severe weather conditions. IET Power Electron. 12, 703-711 (2019). https://doi.org/10.1049/iet-pel.2018.5651.
  • [25] Zhou, Y., Ho, C. N. M. & Siu, K. K.-M. A fast PV MPPT scheme using boundary control with second-order switching surface. IEEE J. Photovolt. 9, 849-857 (2019). https://doi.org/10.1109/JPHOTOV.2019.2899470.
  • [26] Kwaśnicki, P. et al. Characterization of the TCO layer on a glass surface for PV IInd and IIIrd generation applications. Energies 17, 3122 (2024). https://doi.org/10.3390/en17133122.
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  • [28] Christy Mano Raj, J. S. & Jeyakumar, A. E. A two stage successive estimation based maximum power point tracking technique for photovoltaic modules. Sol. Energy 103, 43-61 (2014). https://doi.org/10.1016/j.solener.2014.01.042.
  • [29] Padmavathi, N., Chilambuchelvan, A. & Shanker, N. R. Maximum power point tracking during partial shading effect in PV system using machine learning regression controller. J. Electr. Eng. Technol. 16, 737-748 (2021). https://doi.org/10.1007/s42835-020-00621-4.
  • [30] Ishrat, Z., Gupta, A. K. & Nayak, S. A comprehensive review of MPPT techniques based on ML applicable for maximum power in solar power systems. J. Renew. Energy Environ. 11, 28-37 (2024). https://doi.org/10.30501/jree.2023.385661.1556.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-a0bc48c8-4dcd-4537-9851-972dd80d6ab4
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