Online Monitoring System for Photovoltaic Systems Using Anomaly Detection with Machine Learning

This paper presents a novel method from the field of machine learning for monitoring photovoltaic systems by detecting anomalies. Self-learning algorithms considerably reduce the measuring effort and at the same time offer reliable monitoring of occurring faults. As a prototype, a Raspberry Pi is used in combination with a contactless current sensor.