System and method for modeling building heating energy consumption with the aid of a digital computer

• US 10,503,847 B2
• Filed: 07/01/2019
• Issued: 12/10/2019
• 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): Garber, Charles D
• Assistant Examiner(s): Sabur, Alia
• Application Number:
  US16/458,502
• Publication Number:
  US 20190325097A1
• Time in Patent Office: 162 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 system and method to evaluate building heating fuel consumption with the aid of a digital computer is described. The evaluation can be used for quantifying personalized electric and fuel bill savings. Such savings may be associated with investment decisions relating to building envelope improvements; HVAC equipment improvements; delivery system efficiency improvements; and fuel switching. The results can also be used for assessing the cost/benefit of behavioral changes, such as changing thermostat temperature settings. Similarly, the results can be used for optimizing an HVAC control system algorithm based on current and forecasted outdoor temperature and on current and forecasted solar irradiance to satisfy consumer preferences in a least cost manner. Finally, the results can be used to correctly size a photovoltaic (PV) system to satisfy needs prior to investments by anticipating existing energy usage and the associated change in usage based on planned investments.

Claims

1. A system for modeling periodic building heating energy consumption, comprising:

a computer coupled to a memory and comprising a processor configured to execute code stored in the memory, the computer configured to;

obtain total thermal conductivity of a building with an HVAC system;

evaluate thermal conductivity of a building based on a balance point up to which the building can be thermally sustained using only internal heating gains over a time period for a heating season;

determine fuel consumption as a function of the total thermal conductivity less the balance point thermal conductivity, the average indoor temperature less the average outdoor temperature and duration of the time period, over the HVAC system'"'"'s efficiency; and

model an effect of an optimization of heating of the building on the determined fuel consumption, the optimization comprising at least one of an improvement of a shell of the building, a change in an effective window area of the building, a change in operation of the HVAC system of the building, and an upgrade of the HVAC system, wherein the heating is optimized based on the modeling.

2. A system according to claim 1, the computer further configured to:

determine total thermal conductivity as a function of an average number of occupants in the building over the time period, average indoor electricity consumption over the time period, over the average indoor temperature less the average outdoor temperature.

3. A system according to claim 1, the computer further configured to:

determine the balance point thermal conductivity, comprising one or more steps of;

determine occupant thermal conductivity as a function of an average number of occupants inside the building during the time period, the average indoor temperature less the average outdoor temperature and duration of the time period;

determine electric thermal conductivity as a function of electricity consumption of electric devices in operation in the building during the time period, the average indoor temperature less the average outdoor temperature and duration of the time period; and

determine solar thermal conductivity as a function of solar energy that entered the building during the time period, the average indoor temperature less the average outdoor temperature and duration of the time period.

4. A system according to claim 3, the computer further configured to:

find auxiliary heating thermal conductivity as a function of the auxiliary heating gains over the average indoor temperature less the average outdoor temperature and duration of the time period; and

determine the total thermal conductivity of the building as a function of the balance point thermal conductivity and the auxiliary heating thermal conductivity.

5. A system according to claim 1, the computer further configured to:

evaluate a change in the fuel consumption by taking a derivative of the fuel consumption function with respect to one or more of the changed total thermal conductivity, a changed average indoor temperature, a changed HVAC system'"'"'s efficiency, and changed internal heating gains.

6. A system for determining heating energy consumption of a building over a fixed time period with the aid of a digital computer, comprising:

a computer coupled to a memory and comprising a processor configured to execute code stored in the memory, the computer configured to;

obtain total thermal conductivity of a building and an efficiency for an HVAC system that provides the heating to the building;

identify a temperature difference between an average temperature outside and an average temperature inside the building over a time period for a heating season;

identify internal heating gains within the building over the time period;

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

determine fuel consumption for heating over the time period as a function of the difference between the total thermal conductivity and the balance point thermal conductivity, the temperature difference and the duration of the time period, over the efficiency of the HVAC system; and

model an effect of an optimization of heating of the building on the determined fuel consumption, the optimization comprising at least one of an improvement of a shell of the building, a change in an effective window area of the building, a change in operation of the HVAC system of the building, and an upgrade of the HVAC system, wherein the heating is optimized based on the modeling.

7. A system according to claim 6, the computer further configured to one or more of:

find occupant thermal conductivity as a function of an average number of occupants inside the building during the time period, the temperature difference and the duration of the time period;

find electric thermal conductivity as a function of electricity consumption of electric devices that deliver all heat that is generated into the interior of the building and in operation in the building during the time period, the temperature difference and the duration of the time period; and

find solar thermal conductivity as a function of solar energy that entered the building during the time period, the temperature difference and the duration of the time period.

8. A system according to claim 7, the computer further configured to:

find the heating gain Q^{Gains-Occupants} attributable to the average number of occupants P in accordance with;

Q^{Gains-Occupants}=C(P)(H)

where C represents a conversion factor for occupant heating gains, H represents the duration of the time period in hours, such that each person in P is assumed to produce units of heat per hour.

9. A system according to claim 8, the computer further configured to:

find the occupant thermal conductivity UA^Occupants in accordance with;

10. A system according to claim 6, the computer further configured to:

identify the electricity consumption of electric devices in operation in the building during the time period, each identified electric device delivering all heat that is generated into the interior of the building; and

determine the heating gain attributable to the electricity consumption of the identified electric devices.

11. A system according to claim 6, the computer further configured to:

determine net electricity consumption in the building over the time period and adjusting the net electricity consumption, comprising the steps of at least one of;

find electricity produced by a photovoltaic system for the building over the time period; and

identify non-heating electricity consumption of those of the electric devices in operation in the building during the time period that did not contribute heat to the interior of a building; and

determine the heating gain attributable to the identified electric devices as the sum of the net electricity consumption and the photovoltaic system-produced electricity less the non-heating electricity consumption.

12. A system according to claim 11, the computer further configured to:

find the heating gain Q^{Gains-Electric} attributable to the electricity consumption of the identified electric devices in accordance with;

Q^{Gains-Electric}=(Net+PV−

External)(H)(C)

where H represents the duration of the time period in hours, C represents a conversion factor for occupant heating gains, Net represents the net electricity consumption, PV represents the photovoltaic system-produced electricity, and External represents the non-heating electricity consumption.

13. A system according to claim 12, the computer further configured to:

finding the electric thermal conductivity UA^Electric in accordance with;

14. A system according to claim 6, the computer further configured to:

identify the solar energy that entered the building during the time period; and

determine the heating gain attributable to the identified solar energy.

15. A system according to claim 14, further comprising the step of:

finding the heating gain Q^Gains-Solar attributable to the identified solar energy Solar in accordance with;

Q^Gains-Solar=(Solar)(W)(H)(C)

where H represents the duration of the time period in hours, C represents a conversion factor for occupant heating gains, and W represents the effective window area of the building, such that Solar is the average direct vertical irradiance available on a south-facing surface of the building.

16. A system according to claim 15, further comprising the step of:

finding the solar thermal conductivity UA^Solar in accordance with;

17. A system according to claim 6, the computer further configured to:

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

18. A system according to claim 6, the computer further configured to:

identify auxiliary heating gains within the building over the time period;

find auxiliary heating thermal conductivity as a function of the auxiliary heating gains over the temperature difference and duration of the time period; and

determine the total thermal conductivity of the building as a function of the balance point thermal conductivity and the auxiliary heating thermal conductivity.

19. A system according to claim 18, the computer further configured to:

finding the auxiliary heating gains Q^Gains-Solar in the building during the time period in accordance with;

Q^{Gains-Auxiliary Heating}=(Q^Fuel)(H)η

^HVAC

where H represents the duration of the time period in hours, Q^Fuel represents average hourly fuel consumed, and η

^HVAC represents HVAC system efficiency.

20. A system according to claim 6, the computer further configured to:

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