TY - GEN
T1 - Fault Detection in Solar PV Systems Using Hypothesis Testing
AU - Harrou, Fouzi
AU - Taghezouit, Bilal
AU - Bouyeddou, Benamar
AU - Sun, Ying
AU - Arab, Amar Hadj
N1 - KAUST Repository Item: Exported on 2021-10-14
PY - 2021/7/21
Y1 - 2021/7/21
N2 - The demand for solar energy has rapidly increased throughout the world in recent years. However, anomalies in photovoltaic (PV) plants can reduce performances and result in serious consequences. Developing reliable statistical approaches able to detect anomalies in PV plants is vital to improving the management of these plants. Here, we present a statistical approach for detecting anomalies in the DC part of PV plants and partial shading. Firstly, we model the monitored PV plant. Then, we employ a generalized likelihood ratio test, which is a powerful anomaly detection tool, to check the residuals from the model and reveal anomalies in the supervised PV array. The proposed strategy is illustrated via actual measurements from a 9.54 PV plant.
AB - The demand for solar energy has rapidly increased throughout the world in recent years. However, anomalies in photovoltaic (PV) plants can reduce performances and result in serious consequences. Developing reliable statistical approaches able to detect anomalies in PV plants is vital to improving the management of these plants. Here, we present a statistical approach for detecting anomalies in the DC part of PV plants and partial shading. Firstly, we model the monitored PV plant. Then, we employ a generalized likelihood ratio test, which is a powerful anomaly detection tool, to check the residuals from the model and reveal anomalies in the supervised PV array. The proposed strategy is illustrated via actual measurements from a 9.54 PV plant.
UR - http://hdl.handle.net/10754/672828
UR - https://ieeexplore.ieee.org/document/9557582/
U2 - 10.1109/indin45523.2021.9557582
DO - 10.1109/indin45523.2021.9557582
M3 - Conference contribution
BT - 2021 IEEE 19th International Conference on Industrial Informatics (INDIN)
PB - IEEE
ER -