Model Based-Testing of Spatial and Time Domain Artificial Intelligence Smart Antenna for Ultra-High Frequency Electric Discharge Detection in Digital Power Substations - Lorothy M., Singkang; Kismet, Hong Ping; Herman, Kunsei; Kumarasamy S., Senthilkumar; Kandasamy, Pirapaharan; Ahmed Mohamed, Ahmed Haidar; Paul R., P. Hoole (The Electromagnetic Academy (USA), 2021)
This paper presents a fifth-generation (5G) wireless smart antenna for performing both power substation communication (in space domain beam-steering) and electrostatic discharge (in time domain Ultra-high Frequency “UHF” impulse) detection. The same smart antenna used to communicate with other wireless antennas in the switchyard, as well as with the control room, is utilized to cyclically gather data from power apparatus, busbars, and switches where electrostatic discharge (ESD) may occur. The ESD poses a major threat to electrical safety and lifetime of the apparatus as well as the stability of the power system. The same smart antenna on which beam rotation in space-domain is designed by implementing an artificial neural network (ANN) is also trained in time-domain to identify any of the received signals matching the ultra-high frequency band electrostatic discharge pulses that may be superimposed on the power frequency electric current. The proposed system of electrostatic discharge detection is tested for electrostatic pulses empirically simulated and represented in a trigonometric form for the training of the Perceptron Neural model. The working of the system is demonstrated for electrostatic discharge pulses with rising times of the order of one nanosecond. The artificial intelligence system driving the 5G smart antenna performs the dual roles of beam steering for 5G wireless communication (operating in the space domain) and for picking up any ESD generated UHF pulses from any one of the apparatus or nearby lightning leaders (operating in the time domain).