Abstract: The present disclosure provides a heating, ventilation, and air conditioning (HVAC) system including interconnected artificial neural networks trained for respective subsystems that are required for building temperature control. The HVAC system includes: an air conditioning sensor units installed in or outside a building to detect environmental data; an HVAC device configured to supply thermal energy into an inner space of the building using input power; and a predictive controller configured to generate operational data based on the environmental data and control the HVAC device by adjusting the input power.

Abstract: Provided is a power distribution pricing method of the commercial HVAC system and an apparatus and method for load scheduling of the HVAC system utilizing the same. The power distribution pricing method of the commercial HVAC system and the apparatus and method for load scheduling of the HVAC system utilizing the same can provide scheduling of the load according to the price of the input power which set on the previous day, to thereby provide a power distribution pricing method of the commercial HVAC system with high accuracy, high efficiency and high reliability, and an apparatus and method for load scheduling of the HVAC system using the method.

Abstract: A method for implementing a demand response (DR) for a HVAC system in a building is provided. The method comprises: creating a zone temperature determination model that outputs temperatures of the building by considering an input power provided to the HVAC system and a thermal state of the building; generating objective functions for a power supply schedule in which optimal solutions vary with electricity prices and the thermal state, wherein the power supply schedule includes linear equations for emulating the zone temperature determination model; determining the optimal solutions to the objective functions based on a plurality of electricity price profiles and thermal state profiles; and creating a demand response determination model for taking the electricity price profiles and the thermal state profiles as input and producing a power supply schedule for the HVAC system as output.