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Real-time fault detection system for large scale grid integrated solar photovoltaic power plants

Authors
Iqbal, Muhammad SaadNiazi, Yasir Amir KhanAmir Khan, UmerLee, Bang-Wook
Issue Date
Sep-2021
Publisher
Elsevier Ltd
Keywords
Fault detection and identification; Large-scale solar power plants; Solar photovoltaic
Citation
International Journal of Electrical Power and Energy Systems, v.130, pp 1 - 13
Pages
13
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Electrical Power and Energy Systems
Volume
130
Start Page
1
End Page
13
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/615
DOI
10.1016/j.ijepes.2021.106902
ISSN
0142-0615
1879-3517
Abstract
A new fault detection system is proposed in this study for large-scale grid-tied PV power plants. The fault detection system performs string level comparison of DC power of Actual PV Plant and a simulated PV plant, referred as Theoretical PV Plant. The comparison is performed with a statistical tool which distinguishes a faulty condition and identifies the nature of the fault. This statistical tool is used as outlier detector based on the William Gosset's (Student's) T-Test. The Theoretical PV Plant generates power in a simulation tool using inputs of irradiance and PV module temperature, both obtained from sensors at the Actual PV Plant. The string power of Actual PV Plant is also obtained in the simulation from the data logger in real-time environment. These string powers of Actual and Theoretical PV Plants are compared to find a faulty condition. A GUI is developed where the fault alarms appear on Real-time Status Monitor whenever a fault occurs in the Actual PV Plant. The proposed fault detection system has been validated on a 125 kWp grid-connected PV plant. © 2021 Elsevier Ltd
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ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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