Heating ventilation air conditioner load optimization control method based on imitation learning and reinforcement learning

The invention provides a heating ventilation air conditioner load optimization control method based on imitation learning and reinforcement learning, and relates to the technical field of power demand response, and the method comprises the steps: initializing a deep Q network; historical operation data of the building heating ventilation air conditioner are obtained, and pre-training data are generated according to the historical operation data; pre-training the initialized deep Q network based on imitation learning by using pre-training data; and the pre-trained deep Q network is used to give the optimal building heating ventilation air conditioner temperature setting according to the real-time weather data, and load optimization control is completed. By the adoption of the scheme, the limitation that a simulation environment is difficult to establish in an actual application scene is considered, the method can be rapidly applied to online optimization of heating ventilation air conditioner temperature setti