Computer-implemented system and method for determining building thermal performance parameters through empirical testing

• US 10,467,355 B1
• Filed: 03/20/2015
• Issued: 11/05/2019
• Est. Priority Date: 02/25/2015
• Status: Active Grant

• Current Assignee: Clean Power Research LLC
• Original Assignee: Clean Power Research LLC
• Inventors: Hoff, Thomas E.
• Primary Examiner(s): Shah, Kamini S
• Assistant Examiner(s): Guill, Russ
• Application Number:
  US14/664,742
• Time in Patent Office: 1,691 Days
• CPC Class Codes: F24F 11/62 characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
• CPC Class Codes: F24F 11/64 using pre-stored data
• CPC Class Codes: F24F 2140/50 Load
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G06F 17/10 Complex mathematical operations function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544
• CPC Class Codes: G06F 2111/10 Numerical modelling
• CPC Class Codes: G06F 30/20 Design optimisation, verification or simulation optimisation, verification or simulation of circuit designs G06F30/30

Abstract

A computer-implemented system and method to determine building thermal performance parameters through empirical testing is described. Three building-specific parameters, thermal conductivity, thermal mass, and effective window area, are empirically derived. Thermal conductivity is evaluated through an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC. Thermal mass is evaluated through a second empirical test conducted in the absence of solar gain and no HVAC. Effective window area is evaluated through a third empirical test conducted in the presence of solar gain and no HVAC. Thermal HVAC system power rating and conversion and delivery efficiency are also parametrized. The parameters are estimated using short duration tests that last at most several days. The parameters and estimated HVAC system efficiency can be used to simulate a time series of indoor building temperature, annual fuel consumption, or maximum indoor temperature.

Claims

1. A computer-implemented method for modeling interval building heating energy consumption, comprising the steps of:

finding by a computer processor total thermal conductivity, thermal mass, and effective window area for a building through a series of sequentially-performed empirical tests, at least one of the tests conducted using an electric controllable interior heat source, each successive empirical test building on findings of the earlier empirical tests;

measuring by the computer processor a difference between average indoor and average outdoor temperatures over the course of each of the empirical tests using an indoor thermometer and an outdoor thermometer; and

determining by the computer processor interval heating fuel consumption of the building over a heating season based on the total thermal conductivity, the temperature difference, and average occupancy, non-HVAC electricity consumption and solar resource,

modeling by the computer processor a change in the thermal conductivity associated with replacing a material of a portion of an envelope of the building with a further material using an R-value of the material and an R-value of the further material; and

calculating by the computer processor a value of energy savings associated with the replacement using the interval heating fuel consumption and the change in the thermal conductivity;

wherein the replacement is performed based on the value of the energy savings.

2. A method according to claim 1, further comprising the steps of:

finding the total thermal conductivity based on the occupancy and the non-HVAC electricity consumption through an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC;

finding the thermal mass based on the thermal conductivity, the occupancy and the non-HVAC electricity consumption through another empirical test conducted in the absence of solar gain and no HVAC; and

finding the effective window area based on the thermal mass, the thermal conductivity, the occupancy and the non-HVAC electricity consumption through a further empirical test conducted in the presence of solar gain and no HVAC.

3. A method according to claim 2, further comprising the step of:

finding the interval fuel consumption for heating in accordance with;

R^Furnaceη

^HVACStatus(H)=UA^Total(T^Indoor−

T^Outdoor)(H)−

[(C₁)P+Electric(C₂)+WSolar(C₂)](H)

where R^Furnaceη

^HVACStatus(H) represents the total energy gained from the heating based on H hours in the heating season and the HVAC system for the building having an efficiency of η

^HVAC and a furnace with a rating of R^Furnace, UA^Total represents the thermal conductivity, T^Indoor represents the average indoor temperature throughout the heating season, T^Outdoor represents the average outdoor temperature throughout the heating season, C₁ represents a conversion factor for occupant heating gains, P represents the average number of occupants throughout the heating season, Electric represents average indoor electricity consumption throughout the heating season, C₂ represents a conversion factor for non-HVAC electric heating gains, W represents the effective window area, and Solar represents the average solar energy produced throughout the heating season.

4. A non-transitory computer readable storage medium storing code for executing on a computer system to perform the method according to claim 1.

5. A computer-implemented method for determining building thermal performance parameters through empirical testing, comprising the steps of:

recording by a computer processor a building'"'"'s indoor electricity consumption and difference in indoor and outdoor average temperatures over an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC;

finding by the computer processor thermal conductivity of the building as a function of occupancy and the electricity consumption over the average temperature difference;

recording by the computer processor the building'"'"'s indoor electricity consumption, difference in indoor and outdoor average temperatures, and change in indoor temperature over another empirical test conducted in the absence of solar gain and no HVAC;

finding by the computer processor thermal mass of the building as a function of the thermal conductivity and the average temperature difference, occupancy, and the electricity consumption, all over the indoor temperature change;

recording by the computer processor the building'"'"'s indoor electricity consumption, difference in indoor and outdoor average temperatures, and change in indoor temperature over a further empirical test conducted in the presence of solar gain and no HVAC; and

finding by the computer processor effective window area of the building as a function of the thermal mass and the change in indoor temperature, the thermal conductivity and the average temperature difference, occupancy, the electricity consumption, all over the average solar energy produced during the empirical test;

modeling by the computer processor a value of energy savings associated with changing the effective window area using the effective window area and a further effective window area,

wherein the effective window area in the building is changed to the further effective window area based on the modeling.

6. A method according to claim 5, further comprising the steps of:

recording the building'"'"'s indoor electricity consumption, difference in indoor and outdoor average temperatures, change in indoor temperature, and HVAC status over a final empirical test conducted with HVAC and in the absence of solar gain; and

finding HVAC efficiency for the building as a function of the thermal mass and the change in indoor temperature, the thermal conductivity and the average temperature difference, the occupancy, and the electricity consumption, all over furnace efficiency and average HVAC status during the final empirical test.

7. A method according to claim 6, the step of finding the thermal conductivity further comprising the steps of:

performing the empirical test over a short duration in the absence of solar gain into the building during which the HVAC for the building is not operated, comprising the steps of;

maintaining the constant indoor temperature throughout the empirical test using an electric controllable interior heat source and expressing the constant indoor temperature as an average indoor temperature;

measuring the outdoor temperature throughout the empirical test, over which an average is taken;

measuring the indoor electricity consumption during the empirical test, over which an average is taken; and

tallying the occupancy within the building, over which an average is taken;

finding the temperature difference between the average indoor and the average outdoor temperatures; and

evaluating the thermal conductivity as a function of the average occupancy and the average indoor electricity consumption over the temperature difference.

8. A method according to claim 7, further comprising the step of:

finding the thermal conductivity UA^Total of the building in accordance with;

9. A method according to claim 7, the step of finding the thermal mass further comprising the steps of:

performing the another empirical test over a short duration in the absence of solar gain into the building during which HVAC for the building is not operated, comprising the steps of;

measuring the indoor temperature throughout the another empirical test, over which an average is taken;

measuring the outdoor temperature throughout the another empirical test, over which an average is taken;

measuring the indoor electricity consumption during the another empirical test, over which an average is taken; and

tallying the occupancy within the building, over which an average is taken;

finding the temperature difference between the average indoor and the average outdoor temperatures;

finding the change in the indoor temperature over the another empirical test; and

evaluating the thermal mass as a function of the thermal conductivity and the temperature difference, the average occupancy, and the average indoor electricity consumption, all over the change in the indoor temperature.

10. A method according to claim 9, further comprising the step of:

finding the thermal mass M of the building in accordance with;

11. A method according to claim 9, the step of finding the effective window area further comprising the steps of:

performing the further empirical test over a short duration in the presence of solar gain into the building during which HVAC for the building is not operated, comprising the steps of;

measuring the indoor temperature throughout the further empirical test, over which an average is taken;

measuring the outdoor temperature throughout the further empirical test, over which an average is taken;

measuring the indoor electricity consumption during the further empirical test, over which an average is taken;

tallying the occupancy within the building, over which an average is taken; and

measuring solar energy produced throughout the further empirical test, over which an average is taken;

finding the temperature difference between the average indoor and the average outdoor temperatures;

finding the change in the indoor temperature over the further empirical test; and

finding the effective window area as a function of the thermal mass and the change in the indoor temperature, the thermal conductivity and the average temperature difference, the average occupancy, and the average electricity consumption, all over the average solar energy.

12. A method according to claim 11, further comprising the steps of:

finding the effective window area W of the building in accordance with;

13. A method according to claim 11, the step of finding the HVAC efficiency further comprising the steps of:

performing the final empirical test over a short duration during which HVAC for the building is operated in the absence of solar gain into the building, comprising the steps of;

measuring the indoor temperature throughout the final empirical test, over which an average is taken;

measuring the outdoor temperature throughout the final empirical test, over which an average is taken;

measuring the indoor electricity consumption during the final empirical test, over which an average is taken;

tallying the occupancy within the building, over which an average is taken;

measuring solar energy produced throughout the final empirical test, over which an average is taken; and

observing HVAC status throughout the final empirical test, over which an average is taken;

obtaining the rating of a furnace for the HVAC;

finding the temperature difference between the average indoor and the average outdoor temperatures;

finding the change in the indoor temperature over the final empirical test; and

finding the HVAC efficiency as a function of the thermal mass and the change in the indoor temperature, the thermal conductivity and the average temperature difference, the average occupancy, and the average electricity consumption, all over the furnace rating and the average HVAC status.

14. A method according to claim 13, further comprising the steps of:

finding the efficiency of the HVAC system η

^HVAC of the building in accordance with;

15. A method according to claim 6, further comprising the step of:

generating a time series of temperature data points with each successive data point in the time series determined as a function of the inverse of the thermal mass, the thermal conductivity, the difference between the outdoor temperature and the indoor temperature of the building at the time of the current data point, occupancy at the time of the current data point, the indoor electricity consumption in the building at the time of the current data point, the effective window area, the solar energy produced for the building at the time of the current data point, the rating of the furnace of the HVAC system, the HVAC efficiency, and the status of the furnace at the time of the current data point.

16. A method according to claim 15, further comprising the steps of:

finding each successive data point T<sub>t+Δ

t</sub>^Indoor in the time series of temperature data of the building at time t+Δ

t in accordance with;

17. A method according to claim 15, further comprising the step of:

determining maximum indoor temperature as the minimum of the data points in the temperature time series and the maximum indoor temperature recorded for the building during the heating season.

18. A method according to claim 17, further comprising the steps of:

finding the maximum indoor temperature T<sub>t+Δ

t</sub>^Indoor of the building at time t+Δ

t in accordance with;

19. A method according to claim 5, further comprising the step of:

determining annual fuel consumption as a function of the thermal conductivity, the average temperature difference, the occupancy, the electricity consumption, the effective window area, the solar energy produced for the building, and the duration of the heating season.

20. A method according to claim 19, further comprising the steps of:

finding the annual fuel consumption for heating based on accordance with;

R^Furnaceη

^HVACStatus(H)=UA^Total(T^Indoor−

T^Outdoor)(H)−

[(C₁)P+Electric(C₂)+WSolar(C₂)](H)

where R^Furnaceη

^HVACStatus(H) represents the total energy gained from the heating based on H hours in the heating season and the HVAC system for the building having an efficiency of η

^HVAC and a furnace with a rating of R^Furnace, UA^Total represents the thermal conductivity, T^Indoor represents the average indoor temperature throughout the heating season, T^Outdoor represents the average outdoor temperature throughout the heating season, C₁ represents a conversion factor for occupant heating gains, P represents the average number of occupants throughout the heating season, Electric represents average indoor electricity consumption throughout the heating season, C₂ represents a power unit conversion factor, W represents the effective window area, and Solar represents the average solar energy produced throughout the heating season.

21. A non-transitory computer readable storage medium storing code for executing on a computer system to perform the method according to claim 5.