Predictive Model-based Maximum Power Point Tracking Technique for PV Applications with Reduced Sensor Count
Conference: PCIM Europe digital days 2021 - International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management
05/03/2021 - 05/07/2021 at Online
Proceedings: PCIM Europe digital days 2021
Pages: 6Language: englishTyp: PDF
Authors:
Ahmed, Mostafa; Abdelrahem, Mohamed (Institute for Electrical Drive Systems and Power Electronics (EAL), Technical University of Munich (TUM), Munich, Germany & Electrical Engineering Department, Faculty of Engineering, Assiut University, Assiut, Egypt)
Harbi, Ibrahim; Kennel, Ralph (Institute for Electrical Drive Systems and Power Electronics (EAL), Technical University of Munich (TUM), Munich, Germany)
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.