A Hybrid Reinforcement Learning and Tree Search Approach for Network Topology Control

The growing demand for electricity, driven by widespread adoption of heat pumps, electric vehicles, and industrial electrification, strains power grids and introduces challenges for a reliable and secure supply amidst intermittent renewable energy integration. Network topology control offers flexibility, altering connections to redirect power...

Detection and Classification of Faults in Residential PV Systems with a Synthetic PV Training Database: A Machine Learning-Based Approach Using the PVMD Toolbox to Generate Synthetic PV Yield Data

In this thesis, a new photovoltaic fault detection and classification method is proposed. It combines the generation of a synthetic photovoltaic training database and the use of a machine learning model to detect and classify faults in small-scale residential PV systems. The database was generated in Matlab, and the machine learning modeling was...