Predictive model-based maximum power point tracking technique for pv applications with reduced sensor count

Mostafa Ahmed, Mohamed Abdelrahem, Ibrahim Harbi, Ralph Kennel

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

Abstract

Maximum power point tracking (MPPT) is an essential control for any photovoltaic (PV) system. This paper develops a new predictive technique to extract the maximum power from the PV source. The system under study is composed of a PV source followed by a boost DC-DC converter to interface the resistive load. The proposed MPPT strategy combines the idea of the well-known model predictive control (MPC) with the model of the PV source. By doing so, the switching state can be directly generated without the need of the discrete-time model’s derivation as the case in the conventional finite set model predictive control (FS-MPC). Furthermore, the developed scheme decreases the number of required sensors for MPPT. Finally, the superiority of the proposed technique is confirmed, in comparison with the conventional MPC, via simulation results conducted in Matlab platform.

OriginalspracheEnglisch
TitelPCIM Europe 2021 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management
Herausgeber (Verlag)Mesago PCIM GmbH
Seiten1347-1352
Seitenumfang6
ISBN (elektronisch)9783800755158
PublikationsstatusVeröffentlicht - 2021
Veranstaltung2021 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2021 - Virtual, Online
Dauer: 3 Mai 20217 Mai 2021

Publikationsreihe

NamePCIM Europe Conference Proceedings
Band2021-May
ISSN (elektronisch)2191-3358

Konferenz

Konferenz2021 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2021
OrtVirtual, Online
Zeitraum3/05/217/05/21

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