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Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm

Author

Listed:
  • Abdelilah Chalh

    (Innovative Technologies Laboratory, EST, SMBA University, Fez 30000, Morocco)

  • Aboubakr El Hammoumi

    (Innovative Technologies Laboratory, EST, SMBA University, Fez 30000, Morocco)

  • Saad Motahhir

    (Engineering, Systems and Applications Laboratory, ENSA, SMBA University, Fez 30000, Morocco)

  • Abdelaziz El Ghzizal

    (Innovative Technologies Laboratory, EST, SMBA University, Fez 30000, Morocco)

  • Umashankar Subramaniam

    (Renewable Energy Lab, College of Engineering, Prince Sultan University, Riyadh 12435, Saudi Arabia)

  • Aziz Derouich

    (Innovative Technologies Laboratory, EST, SMBA University, Fez 30000, Morocco)

Abstract

The real implementation of the maximum power point tracking (MPPT) controllers for the photovoltaic (PV) systems is still a big challenge for researchers working in this field. Often, they use simulation tools to assess the performance of their MPPT algorithms before actual implementation. In this context, this paper aims to propose a trusted simulation of a PV system designed under Proteus software. The proposed PV simulator can be used to verify and evaluate the performance of MPPT algorithms with a closer approximation to the real implementation. The main advantage of this model that it contains a real microcontroller, as can be found in reality, so that same code for the MPPT algorithm used in the simulation will be used in real implementation. In contrast, when using (Powersim Software) PSIM or Matlab/Simulink, the code of the algorithm must be rewritten once the real experiment begins, because these tools don’t provide a microcontroller or an electronic board in which our algorithm can be implemented and tested in the same way as the real experiment. After this section, a modified Hill-Climbing (HC) algorithm is introduced. The proposed algorithm can avoid the drift problem posed by conventional HC under a fast variation in insolation. The simulation results show that this method presents good performance in terms of efficiency (99.21%) and response time (10 ms), which improved by 1.2% and 70 ms respectively compared to the conventional HC algorithm.

Suggested Citation

  • Abdelilah Chalh & Aboubakr El Hammoumi & Saad Motahhir & Abdelaziz El Ghzizal & Umashankar Subramaniam & Aziz Derouich, 2020. "Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm," Energies, MDPI, vol. 13(8), pages 1-12, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1943-:d:345768
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    References listed on IDEAS

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    1. Jesús Ferrero Bermejo & Juan Francisco Gómez Fernández & Rafael Pino & Adolfo Crespo Márquez & Antonio Jesús Guillén López, 2019. "Review and Comparison of Intelligent Optimization Modelling Techniques for Energy Forecasting and Condition-Based Maintenance in PV Plants," Energies, MDPI, vol. 12(21), pages 1-18, October.
    2. Umashankar Subramaniam & Sridhar Vavilapalli & Sanjeevikumar Padmanaban & Frede Blaabjerg & Jens Bo Holm-Nielsen & Dhafer Almakhles, 2020. "A Hybrid PV-Battery System for ON-Grid and OFF-Grid Applications—Controller-In-Loop Simulation Validation," Energies, MDPI, vol. 13(3), pages 1-19, February.
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    Cited by:

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    3. Antonella Meneghetti & Chiara Pagnin & Patrizia Simeoni, 2021. "Decarbonizing the Cold Chain: Long-Haul Refrigerated Deliveries with On-Board Photovoltaic Energy Integration," Sustainability, MDPI, vol. 13(15), pages 1-19, July.
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    5. Fateh Mehazzem & Maina André & Rudy Calif, 2022. "Efficient Output Photovoltaic Power Prediction Based on MPPT Fuzzy Logic Technique and Solar Spatio-Temporal Forecasting Approach in a Tropical Insular Region," Energies, MDPI, vol. 15(22), pages 1-21, November.

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