Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/24981
Title: Fault detection and classification scheme for PV system using array power and cross-strings differential currents
Authors: Aboshady, FM
Taha, IBM
Keywords: Fault classification;PV system;shading;short-circuit
Issue Date: 11-Aug-2021
Publisher: IEEE Xplore
Citation: Aboshady, F.M. and Taha, I.B.M. (2021) 'Fault detection and classification scheme for PV system using array power and cross-strings differential currents', IEEE Access, 9, pp. 1 - 15. doi:10.1109/ACCESS.2021.3104007.
Abstract: Accurate and fast fault monitoring system is important for photovoltaic (PV) systems to reduce the damage and energy loss associated with faults. This paper presents a fast fault detection and classification scheme for PV systems. The rate of change of the measured power at the array level is firstly used to detect and differentiate between shading and PV system short-circuit faults. Then, the measured cross-strings differential currents classify the fault type in the case of short-circuit faults. The proposed method accounts for intra-string, string-to-negative terminal, cross-string (string to string), and pole-to-pole short-circuit faults, as well as open circuit faults. Two current transducers per two strings are only required to apply the method leading to a significant reduction in the number of transducers/sensors compared to the literature, making it a cost-effective solution. The fault is detected and classified in 1 ms. A 400 kW PV system consisting of 4 arrays simulated using MATLAB/Simulink package is used for the evaluation process. Short-circuit faults are imposed at different conditions of mismatch levels and fault resistance values. Also, operation at reduced irradiance level is considered, and shading faults are simulated in different levels. The simulation results prove the ability of the proposed scheme to detect and differentiate between shading and short-circuit faults. The proposed method can correctly classify different fault types in almost all cases. The low implementation cost due to the lower number of required sensors and the fast-operating time (1 ms) boost the feasibility of the proposed method.
Description: ACKNOWLEDGMENT: The author would like to acknowledge the financial support received from Taif University Researchers Supporting Project Number (TURSP-2020/61), Taif University, Taif, Saudi Arabia.
URI: http://bura.brunel.ac.uk/handle/2438/24981
DOI: http://dx.doi.org/10.1109/ACCESS.2021.3104007
ISSN: 2169-3536
Appears in Collections:Dept of Mechanical and Aerospace Engineering Research Papers

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