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DOI:10.35833/MPCE.2021.000793
Direct Power Control Based on Dead-beat Function and Extended Kalman Filter for PV Systems
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Author: Mostafa Ahmed1,2,Ibrahim Harbi1,3,Graduate,Ralph Kennel1,Mohamed Abdelrahem1,2

Author Affiliation: 1.the Chair of High-Power Converter Systems (HLU), Technical University of Munich (TUM), 80333 Munich, Germany;2.the Department of Electrical Engineering, Faculty of Engineering, Assiut University, Assiut 71515, Egypt;3.the Department of Electrical Engineering, Faculty of Engineering, Menoufia University, Shebin El-Koum 32511, Egypt

Foundation:
Abstract: In this paper, a new proposal for the implementation of the well-known direct power control (DPC) technique in grid-connected photovoltaic (PV) systems is suggested. Normally, the DPC is executed using a look-up table procedure based on the error between the actual and reference values of the active and reactive power. Thus, the structure of the DPC is simple and results in a fast transient behavior of the inner current loop (injected currents). Therefore, in the current study, the DPC is reformulated using a dead-beat function. In this formulation, the reference voltage vector (RVV) is obtained in the α-β reference frame. Consequently, the switching states for the inverter can be obtained based on the sign of the components of the RVV. The suggested DPC is compared with the conventional one and other switching tables, which are intended for performance enhancement. Furthermore, an extended Kalman filter (EKF) is utilized to eliminate all grid-voltage sensors. Moreover, the switching frequency of the proposed technique is minimized without any need for weighting factors or cost function evaluation. The overall control technique is validated using a hardware-in-the-loop (HIL) experimental set-up and compared with other schemes under different operating conditions.

Keywords:
Photovoltaic (PV) system ; direct power control (DPC) ; sensorless control ; switching frequency minimization ; weighting factor
Received:December 07, 2021               Online Time:2023/05/23
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