In recent years machine learning has expanded into new fields, including the building energy area. The concept of energy flexibility in buildings has become overwhelmingly in the interests of several scholars, making applications increase over time. Nowadays, control systems under analysis make use of algorithms belonging to a particular machine learning branch, called Deep Reinforcement Learning (DRL). DRL has become increasingly popular because it can control systems in which the dynamic process is very complex, as is mainly the case with HVAC systems. The current state of the art has very few, if any, real applications, but a lot of studies on the subject that are thought to become applicable in the shortest possible time.