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Design and Implementation of Maximum Power Point Tracking Algorithm Using Fuzzy Logic and Genetic Algorithm

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Assessment and Simulation Tools for Sustainable Energy Systems

Part of the book series: Green Energy and Technology ((GREEN,volume 129))

Abstract

Recent advances in artificial intelligent techniques embedded into a field programmable gate array (FPGA) allowed the application of such technologies in real engineering problems (robotic, image and signal processing, control, etc.). However, the application of such technologies in the solar energy field is relatively limited. The embedded intelligent algorithm into FPGA can play a very important role in the control of solar energy systems. In this chapter, an intelligent approach based fuzzy logic and genetic algorithm (GA) is developed using a description language (VHDL standing for VHSIC Hardware Description Language), and then is implemented into FPGA-Xilinx (Virtex-II-Pro xc2v1000-4fg456) chip to track the maximal power point (MPP) in a (PV) photovoltaic module. ModelSim-based simulation results confirm the effectiveness of the designed approach in tracking the MPP. In addition, it has been demonstrated that the employed FPGA chip is largely sufficient to implement the designed approach.

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Authors and Affiliations

  1. CRNB Ain Oussera, 180, 17200, Djelfa, Algeria

    Adnane Messai

  2. Renewable Energy Laboratory, Jijel University, Jijel, Algeria

    Adel Mellit

Authors
  1. Adnane Messai
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  2. Adel Mellit
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Correspondence to Adel Mellit .

Editor information

Editors and Affiliations

  1. Department of Economics, Management and Society and Institutions, University of Molise, Campobasso, Italy

    Fausto Cavallaro

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Messai, A., Mellit, A. (2013). Design and Implementation of Maximum Power Point Tracking Algorithm Using Fuzzy Logic and Genetic Algorithm. In: Cavallaro, F. (eds) Assessment and Simulation Tools for Sustainable Energy Systems. Green Energy and Technology, vol 129. Springer, London. https://doi.org/10.1007/978-1-4471-5143-2_14

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  • DOI: https://doi.org/10.1007/978-1-4471-5143-2_14

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-5142-5

  • Online ISBN: 978-1-4471-5143-2

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