Research on Energy Management of Pressurized Oxygen-Supplemented Buildings

Abstract

The energy system of supercharged and oxygenated buildings is a hybrid energy system. The energy used is solar energy, electric energy, pressure energy, etc. In order to make the hybrid energy system more stable and controllable, and to achieve the purpose of energy saving under the condition of stable power consumption of supercharged and oxygenated buildings, a power consumption prediction and management model of supercharged and oxygenated buildings based on neural network is proposed. According to the power consumption system structure of the pressurized oxygenation building, this model establishes a power consumption prediction model based on neural network, and then verifies by simulation that the model can better meet the power consumption prediction conditions of the pressurized oxygenation building. Finally, according to the experiment, this power consumption prediction model can make the power consumption management of the pressurized oxygenation building more stable and controllable. When meeting the daily and stable power consumption requirements of the pressurized oxygenation building, the model can be used to predict the power consumption of the pressurized oxygenation building. Green energy is also reasonably used to save energy in pressurized and oxygen-supplemented buildings.