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Enhanced Predictive Model Control Based DMPPT for Standalone Solar Photovoltaic System

  • Halima IkaouassenEmail author
  • Kawtar Moutaki
  • Abderraouf Raddaoui
  • Miloud Rezkallah
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 912)

Abstract

This paper discussed an enhanced predictive model control (PMC) strategy based distributed maximum power point tracking DMPPT with a prediction horizon of one sampling time in order to achieve high performances from standalone solar photovoltaic system in the presence of dynamic weather variations and partial shading. In this paper, three PV modules are interfaced to the DC-BUS through three cascaded DC-DC boost power converters used with the enhanced PMC based DMPPT algorithm, the proposed technique calculates all possible switching states before applying to the three converters, and the adequate switching state is selected by minimization of a defined cost function, to regulate the duty cycle of the power converters independently, and to supervise maximum power point of the three cascaded PV modules, in order to avoid mismatching phenomena between modules which is considered the main cause for performance degradation and efficiency drop. The performances of the proposed system and control strategy are verified and confirmed when comparing with other conventional MPPT methods such Perturb and Observe (P&O) algorithm based DMPPT using MATLAB/Simulink interface.

Keywords

Enhanced PMC DMPPT 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Halima Ikaouassen
    • 1
    Email author
  • Kawtar Moutaki
    • 1
  • Abderraouf Raddaoui
    • 1
  • Miloud Rezkallah
    • 2
  1. 1.MEAT, EST-SaléMohammed 5 UniversityRabatMorocco
  2. 2.Electrical Engineering DepartmentETS-MontréalNotre DameCanada

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