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Development of a dual-tracking technique for extracting maximum power from PV systems under rapidly changing environmental conditions

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  • Jately, V.
  • Arora, S.

Abstract

Maximum power point tracking (MPPT) is the back bone of most photovoltaic (PV) systems. The MPPT technique helps in extracting the maximum power available from a PV panel under varying atmospheric and load conditions. As the environmental conditions fluctuate throughout the day, maximum power point tracker along with the power converter forces the PV panel to deliver maximum power to the load. Performance indices like speed of convergence, accuracy, steady state losses, implementation complexity, cost, etc. determine the overall suitability of a maximum power point tracking technique. Researchers have proposed different techniques to achieve fast and accurate tracking of the maximum power point (MPP). Among these techniques, hill-climbing based algorithms are widely used for commercial and industrial applications. In this paper, the authors have developed an efficient dual-tracking MPPT technique for rapidly changing atmospheric conditions. A comparative performance analysis of several conventional MPPT techniques and this dual-tracking technique has been carried out in Matlab/Simulink environment. Validation of the proposed technique has been done by comparing its energy yield with that of a recent single-tracking technique reported in literature under a typical one-day irradiance profile. The same irradiance profile has been used to show the economic gain of the technique.

Suggested Citation

  • Jately, V. & Arora, S., 2017. "Development of a dual-tracking technique for extracting maximum power from PV systems under rapidly changing environmental conditions," Energy, Elsevier, vol. 133(C), pages 557-571.
    • Handle: RePEc:eee:energy:v:133:y:2017:i:c:p:557-571
    DOI: 10.1016/j.energy.2017.05.049
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    Cited by:

    1. Obeidi, Nabil & Kermadi, Mostefa & Belmadani, Bachir & Allag, Abdelkrim & Achour, Lazhar & Mesbahi, Nadhir & Mekhilef, Saad, 2023. "A modified current sensorless approach for maximum power point tracking of partially shaded photovoltaic systems," Energy, Elsevier, vol. 263(PA).
    2. Jately, Vibhu & Azzopardi, Brian & Joshi, Jyoti & Venkateswaran V, Balaji & Sharma, Abhinav & Arora, Sudha, 2021. "Experimental Analysis of hill-climbing MPPT algorithms under low irradiance levels," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    3. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    4. Zhang, Xiaoshun & Li, Shengnan & He, Tingyi & Yang, Bo & Yu, Tao & Li, Haofei & Jiang, Lin & Sun, Liming, 2019. "Memetic reinforcement learning based maximum power point tracking design for PV systems under partial shading condition," Energy, Elsevier, vol. 174(C), pages 1079-1090.
    5. Sakshi Sharma & Vibhu Jately & Piyush Kuchhal & Peeyush Kala & Brian Azzopardi, 2023. "A Comprehensive Review of Flexible Power-Point-Tracking Algorithms for Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 16(15), pages 1-28, July.

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