A Smart Ice Monitoring System for Photovoltaic Applications based on Capacitive Graphene Sensors

This work presents an innovative smart system for monitoring ice formation on photovoltaic systems (PV) based on capacitive sensors made of graphene nanoplatelet (GNP) nanocomposites and a low-cost conditioning circuit. At the heart of the methodological approach is integrating a multi-gap sensor configuration, designed to maximise sensitivity to dielectric variations, and an oscillator circuit that converts capacitance variations into frequency signals, ensuring robust and noise-free transmission even in extreme environments. The sensor design includes selecting innovative materials and an optimised electrode configuration. The metrological characterisation of the system shows a sensitivity down to almost 6 Hz/pF and a resolution of less than about 1.3 pF, confirming the system’s excellent performance in variable environmental conditions and ensuring high accuracy in ice detection. Experimental tests with ice thicknesses of up to 10 mm showed perfect alignment with theoretical models. In addition, data analysis using machine learning techniques produced accurate results in classifying the presence of ice, with an accuracy of over 95% and remarkable robustness even in the presence of noise. The results confirm the system’s high performance and versatility for PV, energy and aerospace applications, proposing a smart and energy-efficient solution for ice management in PV systems.