Computer-implemented system and method for evaluating a change in fuel requirements for heating of a building

• US 10,354,025 B1
• Filed: 03/20/2015
• Issued: 07/16/2019
• 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): Cook, Brian S
• Application Number:
  US14/664,729
• Time in Patent Office: 1,579 Days
• Field of Search: 703 2
• 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 assist consumers with decisions affecting a change in fuel requirements is provided. Fuel consumption for heating can be considered by evaluating changes that would affect thermal conductivity, average indoor temperature, HVAC efficiency, and solar gain. In a further embodiment, a computer-implemented system and method to evaluate investment'"'"'s in a building'"'"'s shell is provided. Thermal conductivity and the surface area of a surface that is under consideration for improvement are obtained, after which revised thermal conductivity can be modeled based on the existing and proposed thermal performance of that building surface. In a still further embodiment, fuel consumption for heating modeling results can be comparatively evaluated, with one fuel consumption model operating over an annual (or periodic) scope and another fuel consumption model operating on an hourly (or interval) scope.

Claims

1. A method for evaluating a change in fuel requirements for heating of a building with the aid of a digital computer, comprising the steps of:

obtaining data for thermal conductivity, indoor temperature, an efficiency of an HVAC system of the building, and solar gains recorded for a building over a heating season;

expressing fuel consumption for heating of the building over the heating season in parameterized terms that represent the thermal conductivity, the indoor temperature averaged, the HVAC efficiency, and the solar gains averaged;

modeling an effect of an optimization of the heating of the building on the fuel consumption, the optimization comprising one of an improvement of the shell of the building, a change in the effective window area of the building, a change in the operation of the HVAC system of the building, and an upgrade of the HVAC system, further comprising;

taking a derivative of the fuel consumption expression with respect to one of the parameterized terms as taken as a variable of interest; and

finding a change in the fuel consumption relative to the variable of interest by solving the derivative based on the data obtained, wherein the steps are performed on a suitably-programmed computer and wherein heating of the building is optimized based on the change in fuel consumption.

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

obtaining data for the average outdoor temperature for the building over the heating season with the outdoor temperature averaged;

finding balance point thermal conductivity as a function of internal heating gains within the building over a temperature difference between the average indoor and the average outdoor temperatures, and duration of the heating season; and

expressing the fuel consumption of the building as a function of the total thermal conductivity versus the balance point thermal conductivity multiplied by a difference in the average indoor and the average outdoor temperatures and the duration of the heating season, all over the HVAC efficiency.

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

finding the fuel consumption for heating Q^Fuel for the heating season in accordance with;

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

evaluating the balance point thermal conductivity UA^{Balance Point} of the building in accordance with;

UA^{Balance Point}=UA^Occupants+UA^Electric+UA^Solar

where UA^Occupants, UA^Electric, and UA^Solar represent the thermal conductivities of the internal heating gains respectively comprising occupant, electric, and solar sources of heating gain.

5. A method according to claim 3, further comprising the steps of:

selecting the thermal conductivity UA^Total of the building as the variable of interest; and

evaluating the change in the fuel consumption

6. A method according to claim 3, further comprising the steps of:

selecting the average indoor temperature T^Indoor of the building as the variable of interest; and

evaluating the change in the fuel consumption

7. A method according to claim 3, further comprising the steps of:

selecting the HVAC efficiency η

^HVAC of the building as the variable of interest; and

evaluating the change in the fuel consumption

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

selecting the average solar gains Solar of the building as the variable of interest, which are represented by an effective window area W of the building; and

evaluating the change in the fuel consumption

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

10. A computer-implemented method for evaluating a building shell improvement affecting a change in thermal conductivity, comprising the steps of:

obtaining existing thermal conductivity and finding the surface area of a surface for which an improvement to the building'"'"'s shell is under consideration;

finding existing and proposed thermal performances of the surface; and

evaluating revised thermal conductivity of the building based on the existing thermal conductivity and on the surface area and the existing and the proposed thermal performances of the surface in accordance with;

=UA^Total+Δ

UA^Total

where UA^Total represents the existing thermal conductivity, and

11. A method according to claim 10, further comprising the steps of:

evaluating fuel savings Δ

Q^Fuel in accordance with;

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

finding the fuel consumption Q^Fuel in accordance with;

13. A method according to claim 12, further comprising the step of:

evaluating the balance point thermal conductivity UA^{Balance Point} of the building in accordance with;

UA^{Balance Point}=UA^Occupants+UA^Electric+UA^Solar

where UA^Occupants, UA^Electric, UA^Solar represent the thermal conductivities of the internal heating gains respectively comprising occupant, electric, and solar sources of heating gain.

14. A method according to claim 10, further comprising the steps of:

evaluating economic value Annual Savings in accordance with;

15. A non-transitory computer readable storage medium storing code for executing on a computer system to perform the method according to claim 10.

16. A method for comparatively evaluating fuel consumption for heating with the aid of a digital computer, comprising the steps of:

determining a periodic heating fuel consumption of a building over a time period based on total thermal conductivity, balance point thermal conductivity, temperature difference between average indoor and average outdoor temperatures, HVAC system efficiency, and duration of the time period;

determining an interval heating fuel consumption of the building over the time period based on total thermal conductivity, the temperature difference, an average occupancy, a non-HVAC electricity consumption and a solar resource; and

comparing the periodic heating fuel consumption and the interval heating fuel consumption over the time period,

wherein the steps are performed on a suitably-programmed computer and wherein heating of the building is optimized based on at least one of the periodic heating fuel consumption and the interval heating fuel consumption, the optimization comprising at least one of changing a shell of the building, changing a size of an HVAC system within the building, and performing one or more upgrades to the HVAC system.

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

obtaining the total thermal conductivity of the building and the HVAC system efficiency and finding the temperature difference;

identifying internal heating gains over the time period;

finding balance point thermal conductivity as a function of the internal heating gains over the temperature difference and the time period; and

solving the periodic fuel consumption as a function of the difference between the total thermal and the balance point thermal conductivity, the temperature difference, and the time period, all over the HVAC system efficiency.

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

finding the balance point thermal conductivity UA^{Balance Point} in accordance with;

19. A method according to claim 18, further comprising the step of:

finding the periodic fuel consumption for heating Q^Fuel in accordance with;

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

recording the building'"'"'s non-HVAC electricity consumption and the temperature difference over an empirical test conducted in the absence of solar gain with constant indoor temperature and no HVAC;

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

recording the building'"'"'s non-HVAC electricity consumption, the temperature difference, and change in indoor temperature over another empirical test conducted in the absence of solar gain and no HVAC;

finding 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 the building'"'"'s non-HVAC electricity consumption, the temperature difference, and change in indoor temperature over a further empirical test conducted in the presence of solar gain and no HVAC; and

finding 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; and

determining the interval 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.

21. A method according to claim 20, 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 fuel consumption based on H hours in the heating season and an 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.

22. A non-transitory computer readable storage medium storing code for executing on a computer system to perform the method according to claim 16.