Abstract: Disclosed is a machine learning energy management system that regulates incoming energy sources into compressed air storage operations and energy generation. Compressed air is directed into a thermoregulation system that cycles storage tanks according to physical qualities. A boost impulse creates energy to initiate the electrical energy generation. The compressed air operations and energy generation leverage the heating and cooling of an external HVAC system to improve performance and conservation of the heating and cooling for an external building. The system combines real-time data, historical performance data, algorithm control, variable air pressure for demand-based generation, tank-to-tank thermal cycling, building air heat exchanger, and boost pulsation to achieve optimized system efficiency and responsiveness.

Abstract: Disclosed is a machine learning energy management system that regulates incoming energy sources into compressed air storage operations and energy generation. Compressed air is directed into a thermoregulation system that cycles storage tanks according to physical qualities. A boost impulse creates energy to initiate the electrical energy generation. The compressed air operations and energy generation leverage the heating and cooling of an external HVAC system to improve performance and conservation of the heating and cooling for an external building, wherein compressed air is used to drive a coolant compressor. The system combines real-time data, historical performance data, algorithm control, variable air pressure for demand-based generation, tank-to-tank thermal cycling, building air heat exchanger, and boost pulsation to achieve optimized system efficiency and responsiveness.