Microgrid protection using FACTS controller and machine learning

Sheila H 1, *, Zuhaib Baig 1, Shri Harsha J 2 and Spoorthi SN 1

1 Department of Electrical and Electronics Engineering, Vidya Vikas Institute of Engineering and Technology, Mysuru, Karnataka, India.
2 Department of Electronics and Communication Engineering, G Madegowda Institute of Engineering and Technology, Mandya, Karnataka, India.
Research Article
World Journal of Advanced Research and Reviews, 2024, 22(03), 1796–1800
Article DOI: 10.30574/wjarr.2024.22.3.1902
Publication history: 
Received on 17 May 2024; revised on 26 June 2024; accepted on 28 June 2024
This research presents a method of machine learning approach for microgrid protection using FACTS Controllers. A Microgrid connected to the Distributed Generators connected with different types of load is very prone to faults. This work uses wavelet transform to predict the failure signals, which is then fed into a machine learning model for real-time identification. These current signals from both ends of the transmission lines are analyzed using wavelet-based multi-resolution analysis, and then compare the results to preset thresholds to generate fault indices. This approach offers a power quality enhanced microgrid protection solution with lower losses and increased dependability.
Micro-grid; FACTS; Distributed Generators; Machine Learning; Wavelet Transform
Full text article in PDF: 
Share this