Integrating renewable energy into power systems often involves challenges related to grid power quality, reliability, and feasibility. Photovoltaic (PV) installations and their management require detailed analysis because factors like solar-radiation fluctuations, soiled solar panels, and poor panel performance can cause unexpected and undesirable oscillations in power output and generation.
PATTERN (Photovoltaic Plant Fault Detection and Energy Production) is a tool that was developed to not only detect damage in PV panels, but also forecast their energy output. Using data from the Copernicus Atmosphere Monitoring Service (CAMS), PATTERN’s AI algorithm makes use of a combination of supervised machine learning and deep learning technologies to deliver accurate generation forecasts for a given PV energy production plant.
Xilbi Sistemas de Informacion SL
Pedro Branco, Luísa Trino, Fernando Branco