A method for controlling temperature in a thermal zone within a building , comprising: using a processor , receiving a desired temperature range for the thermal zone ; determining a forecast ambient temperature value for an external surface of the building proximate the thermal zone ; using a predictive model for the building , determining set points for a heating, ventilating, and air conditioning ("HVAC") system associated with the thermal zone that minimize energy use by the building ; the desired temperature range and the forecast ambient temperature value being inputs to the predictive model ; the predictive model being trained using respective historical measured value data for at least one of the inputs; and, controlling the HVAC system with the set points to maintain an actual temperature value of the thermal zone within the desired temperature range for the thermal zone ; characterised in that : the method further comprising receiving a demand response signal from a utility demand response control system associated with the building and further determining the set points using the demand response signal as one of the inputs to the predictive model ; and, determining a demand response capacity of the building as a difference between a high electric power demand limit and a low electric power demand limit , wherein the demand response capacity is available for bidding at least a portion thereof into at least one of a frequency response market, an electric power market, and an ancillary services market associated with a utility grid. using a processor , receiving a desired temperature range for the thermal zone ; determining a forecast ambient temperature value for an external surface of the building proximate the thermal zone ; using a predictive model for the building , determining set points for a heating, ventilating, and air conditioning ("HVAC") system associated with the thermal zone that minimize energy use by the building ; the desired temperature range and the forecast ambient temperature value being inputs to the predictive model ; the predictive model being trained using respective historical measured value data for at least one of the inputs; and, controlling the HVAC system with the set points to maintain an actual temperature value of the thermal zone within the desired temperature range for the thermal zone ; characterised in that : the method further comprising receiving a demand response signal from a utility demand response control system associated with the building and further determining the set points using the demand response signal as one of the inputs to the predictive model ; and, determining a demand response capacity of the building as a difference between a high electric power demand limit and a low electric power demand limit , wherein the demand response capacity is available for bidding at least a portion thereof into at least one of a frequency response market, an electric power market, and an ancillary services market associated with a utility grid. the method further comprising receiving a demand response signal from a utility demand response control system associated with the building and further determining the set points using the demand response signal as one of the inputs to the predictive model ; and, determining a demand response capacity of the building as a difference between a high electric power demand limit and a low electric power demand limit , wherein the demand response capacity is available for bidding at least a portion thereof into at least one of a frequency response market, an electric power market, and an ancillary services market associated with a utility grid. <EOS>