Highly Efficient MPPT Technique Using Model Predictive Control
ID:52 View Protection:PRIVATE Updated Time:2023-06-12 13:42:24 Hits:1168 Oral Presentation

Start Time:2023-06-18 16:00(Asia/Shanghai)

Duration:20min

Session:S Oral Session » S5Oral Session 8 & Oral Session 11

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Abstract
Maximum power point tracking (MPPT) is a requirement in photovoltaic (PV) systems to improve and boost the efficiency. Therefore, this paper presents an improved MPPT method based on model predictive control (MPC) for a boost converter PV system. The MPPT-based MPC provides a fast transient behavior compared to the conventional methods. Thus, it is employed in this study, where a modified version of the perturb and observe (P&O) method is developed, in which additional control loops are added to the original one to decrease its ripple content at steady-state and improve its divergent behavior at transient-state. Consequently, the efficiency of the whole control algorithm is increased. Then, the MPC algorithm receives the reference from the modified P&O, and based on the cost function design, the optimal switching signal is obtained and sent directly to the switch without the need for modulators, which further simplifies the overall control method. The system is tested at different atmospheric conditions to prove its superiority in comparison with the traditional MPC method.
Keywords
PV systems, MPPT, MPC, P&O
Speaker
Ahmed Mostafa
Technical University of Munich

Mostafa Ahmed was born in Qena, Egypt. He received the B.Sc.(Hons.) and M.Sc. degrees in electrical engineering from Assiut University, Assiut, Egypt, in 2010 and 2015, respectively. He is currently working toward the Ph.D. degree at the Chair of High-Power Converter Systems (HLU), Technical University of Munich (TUM), Munich, Germany. He received a highly prestigious scholarship from the German Academic Exchange Service (DAAD) within the program “German-Egyptian Research Long Term Scholarship (GERLS)” to pursue the Ph.D. degree at the Technical University of Munich, Germany. He serves as a Reviewer for several leading IEEE/IET journals. His research interests include renewable energy systems, modeling of photovoltaic systems, MPPT, predictive control of power electronics converters, and sensorless control of photovoltaic systems.

Harbi Ibrahim

Abdelrahem Mohamed

Jose Rodriguez
Universidad San Sebastian

Kennel Ralph

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Important Date
  • Conference Date

    Jun 16

    2023

    to

    Jun 19

    2023

  • Jun 15 2023

    Contribution Submission Deadline

  • Jul 02 2023

    Registration deadline

Sponsored By
Huazhong University of Science and Technology, China
(IEEE PELS)
IEEE
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