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Design and real time implementation of a novel rule compressed fuzzy logic method for the determination operating point in a photo voltaic system

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  • Rajesh, R.
  • Mabel, M. Carolin

Abstract

In the PhotoVoltaic (PV) system characteristics, a maximum power operating point exists for each value of solar irradiance. The operating point continuously varies as the solar irradiance vary and therefore tracking of maximum power in PV system is significant. This paper introduces a new rule compressed fuzzy logic method to track optimal power operating point of photovoltaic system under non-uniform irradiance. The method has three-input parameters and a single output parameter. The input parameters are the change in power, the change in voltage and change in duty cycle and the output parameter is the reference current to the converter. With respect to each combination of two input parameters, three set of output rules are developed and then compressed to a single set of rules based on tracking conditions. The step response, analysis under partial shading and with one day solar irradiance data are implemented in Matlab/simulink platform. The method confirms its effectiveness by attaining the optimal power at 2.46s with a low steady state error of 0.35%. The energy capitulation efficiency is obtained as 99.5%. The performance of the proposed method is also evaluated experimentally and its efficiency is proved by comparing with perturb & observe algorithm.

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  • Rajesh, R. & Mabel, M. Carolin, 2016. "Design and real time implementation of a novel rule compressed fuzzy logic method for the determination operating point in a photo voltaic system," Energy, Elsevier, vol. 116(P1), pages 140-153.
    • Handle: RePEc:eee:energy:v:116:y:2016:i:p1:p:140-153
    DOI: 10.1016/j.energy.2016.09.068
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    1. Aatabe, Mohamed & El Guezar, Fatima & Vargas, Alessandro N. & Bouzahir, Hassane, 2021. "A novel stochastic maximum power point tracking control for off-grid standalone photovoltaic systems with unpredictable load demand," Energy, Elsevier, vol. 235(C).
    2. Boukenoui, R. & Ghanes, M. & Barbot, J.-P. & Bradai, R. & Mellit, A. & Salhi, H., 2017. "Experimental assessment of Maximum Power Point Tracking methods for photovoltaic systems," Energy, Elsevier, vol. 132(C), pages 324-340.
    3. Muhammad Mateen Afzal Awan & Muhammad Yaqoob Javed & Aamer Bilal Asghar & Krzysztof Ejsmont, 2022. "Performance Optimization of a Ten Check MPPT Algorithm for an Off-Grid Solar Photovoltaic System," Energies, MDPI, vol. 15(6), pages 1-31, March.
    4. Mao, Mingxuan & Zhang, Li & Duan, Pan & Duan, Qichang & Yang, Ming, 2018. "Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller," Energy, Elsevier, vol. 143(C), pages 181-190.

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