# US 10,372,146 B2 · Systems and methods for creating and using combined predictive models to control HVAC equipment > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,372,146 B2 - Document ID: US10372146B2 - Status: Granted - Kind: B2 - Application number: 15/331,755 - Filed: 2016-10-21 - Published: 2018-04-26 - Granted: 2019-08-06 - Earliest claimed: 2016-10-21 - Assignees: Johnson Controls Technology Company - Applicants: Johnson Controls Technology Company - Inventors: Steven R. Vitullo - Web page: https://patentgrep.com/patent/US10372146B2 ## CPC - G05D 23/1917: {using digital means} - F24F 11/61: using timers - F24F 11/62: characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values - F24F 11/63: Electronic processing - G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks - G06N 20/20: Ensemble learning - H04L 12/2823: {Reporting information sensed by appliance or service execution status of appliance services in a home automation network (device-related reporting H04L43/065; arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom H04Q9/00)} - F24F 2110/10: Temperature - F24F 2140/50: Load - F24F 2140/60: Energy consumption - G05D: SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES - F24F: AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING (removing dirt or fumes from areas where they are produced B08B15/00; vertical ducts for carrying away waste gases from buildings E04F17/02; tops for chimneys or ventilating shafts, terminals for flues F23L17/02) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS - H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M) ## Abstract A heating, ventilation, or air conditioning (HVAC) system for a building includes HVAC equipment, a controller, and a predictive modeling system. The HVAC equipment are operable to affect an environmental condition in the building. The controller is configured to determine an operating point for the HVAC equipment and to operate the HVAC equipment at the operating point. The predictive modeling system includes a plurality of HVAC component models and one or more prediction combiners. The HVAC component models are configured to generate a plurality of component model predictions based on the operating point. The prediction combiners are configured to combine the plurality of component model predictions to form a combined model prediction. The controller is configured to use the combined model prediction to optimize the operating point and to operate the HVAC equipment at the optimized operating point. ## Claims ### Claim 1 A heating, ventilation, or air conditioning (HVAC) system for a building, the HVAC system comprising: HVAC equipment operable to affect an environmental condition in the building, a performance of the HVAC equipment characterized by a performance variable; a controller configured to determine an operating point for the HVAC equipment and to operate the HVAC equipment at the operating point; and a predictive modeling system comprising: a first HVAC component model configured to generate a first component model prediction comprising a first predicted value of the performance variable for a particular future time; a second HVAC component model configured to generate a second component model prediction comprising a second predicted value of the performance variable for the particular future time; and one or more prediction combiners configured to combine the first and second component model predictions to form a combined model prediction, wherein the combined model prediction comprises another predicted value of the performance variable at the particular future time; wherein the controller is configured to use the combined model prediction to optimize the operating point and to operate the HVAC equipment at the optimized operating point; and one or more sensors configured to measure one or more measured variables associated with the HVAC equipment; wherein the first and second HVAC component models are configured to generate the component model predictions as functions of the measured variables. ### Claim 2 (depends on 1) The HVAC system of claim 1, wherein the operating point is a setpoint for the HVAC equipment and the performance variable indicates a predicted power consumption of the HVAC equipment at the setpoint. ### Claim 3 (depends on 1) The HVAC system of claim 1, wherein the first and second HVAC component models have different functional forms and use different mathematical relationships to generate the first and second component model predictions. ### Claim 4 (depends on 1) The HVAC system of claim 1, wherein the prediction combiners comprise an equal weighting combiner configured to generate the combined model prediction by calculating an average of the component model predictions. ### Claim 5 (depends on 1) The HVAC system of claim 1, wherein the prediction combiners comprise a variance weighting combiner configured to: identify a variance associated with each of the component model predictions; assign a weight to each of the component model predictions based on the variance associated therewith; and generate the combined model prediction by calculating a weighted average of the component model predictions using the assigned weights. ### Claim 6 (depends on 1) The HVAC system of claim 1, wherein the prediction combiners comprise a trimmed mean combiner configured to: create an initial set of the component model predictions; identify one or more highest values of the component model predictions and one or more lowest values of the component model predictions; create a filtered subset of the component model predictions by removing the identified component model predictions from the initial set; and generate the combined model prediction by calculating an average of the component model predictions in the filtered subset. ### Claim 7 (depends on 6) The HVAC system of claim 6, wherein the trimmed mean combiner is configured to use a variance weighting technique to calculate the average of the component model predictions in the filtered subset, the variance weighting technique comprising: identifying a variance associated with each of the component model predictions in the filtered subset; assigning a weight to each of the component model predictions based on the variance associated therewith; and generating the combined model prediction by calculating a weighted average of the component model predictions in the filtered subset using the assigned weights. ### Claim 8 (depends on 1) The HVAC system of claim 1, further comprising: a model evaluator configured to calculate a score for each of the prediction combiners by comparing the combined model predictions generated by each of the prediction combiners to actual values of the performance variable; and a combiner selector configured use the calculated scores to select one of the prediction combiners; wherein the predictive modeling system is configured to use the selected prediction combiner to generate the combined model prediction.