No title
This thesis explores the use of Reinforcement Learning (RL) to optimize residential energy usage in a system composed of photovoltaic (PV) panels, a battery, an electric vehicle (EV), household consumption, and the electricity grid. A Deep Q-Network (DQN) agent was developed to minimize the electricity bill by optimizing battery usage and EV charging using real residential data supplied by Siemens
