Využití metod umělé inteligence v technické diagnostice fotovoltaické elektrárny

Abstract

This thesis focuses on the application of modern artificial intelligence methods for the analysis and diagnostics of historical operational data from a photovoltaic power plant, with the main goal being the detection of anomalies. The theoretical part begins with an analysis of the basic components of a photovoltaic system, followed by a review of data processing and analysis methods suitable for this domain. The practical part includes the design and implementation of an application for working with data stored in a PostgreSQL database system, as well as the development of a visual interface. The thesis also involves testing selected algorithms for anomaly detection, including an evaluation of their performance and suitability for real-world deployment.