System for building balance-point-based seasonal fuel consumption forecasting with the aid of a digital computer

Patent metadata

Field	Value
Publication number	US-12320534-B2
Application number	US-202418668736-A
Country	US
Kind code	B2
Filing date	May 20, 2024
Priority date	Nov 3, 2016
Publication date	Jun 3, 2025
Grant date	Jun 3, 2025

Abstract

A Thermal Performance Forecast approach is described that can be used to forecast heating and cooling fuel consumption based on changes to user preferences and building-specific parameters that include indoor temperature, building insulation, HVAC system efficiency, and internal gains. A simplified version of the Thermal Performance Forecast approach, called the Approximated Thermal Performance Forecast, provides a single equation that accepts two fundamental input parameters and four ratios that express the relationship between the existing and post-change variables for the building properties to estimate future fuel consumption. The Approximated Thermal Performance Forecast approach marginally sacrifices accuracy for a simplified forecast. In addition, the thermal conductivity, effective window area, and thermal mass of a building can be determined using different combinations of utility consumption, outdoor temperature data, indoor temperature data, internal heating gains data, and HVAC system efficiency as inputs.

First claim

What is claimed is:

1. A system for building balance-point-based seasonal fuel consumption forecasting with the aid of a digital computer, comprising:
a processor configured to execute code, the processor configured to:
obtain historical daily fuel consumption for thermal conditioning of a building during a time period;
identify internal gains within the building over the time period;
determine adjusted internal gains for the building using a plot, comprising:
obtain average daily outdoor temperatures over the time period;
generate the plot of the historical daily fuel consumption averaged on a daily basis versus the average daily outdoor temperatures over the time period;
obtain a balance point temperature for the building using the plot; and
evaluate the adjusted internal gains using the average indoor temperature and the balance point temperature; and

forecast seasonal fuel consumption for the building associated with a change to the building using the historical daily fuel consumption and the adjusted internal gains, further comprising determining a relationship between at least one of one or more variables associated with the building before and after the change, wherein the relationship is used during the forecasting of the seasonal fuel consumption.

2. A system according to claim 1 , wherein the relationship is expressed as a ratio.

3. A system according to claim 1 , wherein the variables comprise one or more of thermal conductivity, indoor temperature, the HVAC system efficiency, and the internal gains.

4. A system according to claim 3 , the processor further configured to determine a slope of the plot and divide the slope by 24 to obtain a ratio of the thermal conductivity of the building over the efficiency of an HVAC system of the building, wherein the adjusted internal gains are further determined using the ratio.

5. A system according to claim 4 , the processor further configured to determine the thermal conductivity before the change using the ratio.

6. A system according to claim 3 , wherein the thermal conductivity before the change is determined using an empirical test.

7. A system according to claim 1 , the processor further configured to obtain a thermal mass of the building, wherein the forecast seasonal fuel consumption is further determined based on the thermal mass.

8. A system according to claim 7 , the processor further configured to determine the thermal mass of the building based on a comparison of a predicted fuel consumption for the building during a further time period and a measured fuel consumption for the building during the time period.

9. A system according to claim 1 , wherein the change is performed based on the forecast.

10. A method for building balance-point-based seasonal fuel consumption forecasting with the aid of a digital computer, comprising:
obtaining by a processor configured to execute code historical daily fuel consumption for thermal conditioning of a building during a time period;
identifying by the processor internal gains within the building over the time period;
determining by the processor adjusted internal gains for the building using a plot, comprising:
obtaining average daily outdoor temperatures over the time period;
generating the plot of the historical daily fuel consumption averaged on a daily basis versus the average daily outdoor temperatures over the time period;
obtaining a balance point temperature for the building using the plot;
evaluating the adjusted internal gains using the average indoor temperature and the balance point temperature;

obtaining a thermal mass of the building; and
forecasting by the processor seasonal fuel consumption for the building associated with a change to the building using thermal mass, the historical daily fuel consumption, and the adjusted internal gains.

11. A method according to claim 10 , further comprising determining a relationship between at least one of one or more variables associated with the building before and after the change, wherein the relationship is used during the forecasting of the seasonal fuel consumption.

12. A method according to claim 11 , wherein the relationship is expressed as a ratio.

13. A method according to claim 11 , wherein the variables comprise one or more of thermal conductivity, indoor temperature, the HVAC system efficiency, and the internal gains.

14. A method according to claim 13 , further comprising determining a slope of the plot and divide the slope by 24 to obtain a ratio of the thermal conductivity of the building over the efficiency of an HVAC system of the building, wherein the adjusted internal gains are further determined using the ratio.

15. A method according to claim 14 , further comprising determining the thermal conductivity before the change using the ratio.

16. A method according to claim 13 , wherein the thermal conductivity before the change is determined using an empirical test.

17. A method according to claim 11 , further comprising determining the thermal mass of the building based on a comparison of a predicted fuel consumption for the building during a further time period and a measured fuel consumption for the building during the time period.

18. A method according to claim 10 , wherein the change is performed based on the forecast.

19. A system for building seasonal fuel consumption forecasting with the aid of a digital computer, comprising:
a processor configured to execute code, the processor configured to:
obtain historical daily fuel consumption for thermal conditioning of a building during a time period;
identify internal gains within the building over the time period;
determine adjusted internal gains for the building using a plot, comprising:
obtain average daily outdoor temperatures over the time period;
generate the plot of the historical daily fuel consumption averaged on a daily basis versus the average daily outdoor temperatures over the time period;
obtain a balance point temperature for the building using the plot; and
evaluate the adjusted internal gains using the average indoor temperature and the balance point temperature;

obtain a thermal mass of the building; and
forecast seasonal fuel consumption for the building

associated with a change to the building using the thermal mass, historical daily fuel consumption, and the adjusted internal gains.

Assignees

• Clean Power Res L L C

Inventors

• Hoff Thomas E

Classifications

• F24F2130/00

  Control inputs relating to environmental factors not covered by group F24F2110/00 · CPC title

• F24F2140/60

  Energy consumption · CPC title

• F24F2110/00

  Control inputs relating to air properties · CPC title

• F24F2130/10

  Weather information or forecasts · CPC title

• G05B2219/2614

  HVAC, heating, ventillation, climate control · CPC title