IP Library › Granted Patent US 12676503
Granted Patent B2
US 12676503 · App. 17/724,264 · Granted Jul 7, 2026

Smart energy platforms and methods for a property

Inventor: Alexander Cardona (Gilbert, AZ)
Assignee: State Farm Mutual Automobile Insurance Company
H02J13/13G06Q50/06H04L12/2818H04L2012/2847
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Quick Facts
Patent No.
US 12676503
App. No.
17/724,264
Granted
Jul 7, 2026
Kind
B2
Abstract

A smart energy platform for controlling energy consumption at a property, the smart energy platform configured to: (i) receive an input from a user associated with the property indicating a maximum comfort temperature and a minimum comfort temperature of the property; (ii) receive property data; (iii) retrieve weather data; (iv) determine property usage; (v) receive energy pricing data from an energy company; (vi) build a model based upon the input from the user, the property data, the weather data, and the property usage; (vii) input the energy pricing data and the weather data into the model; (viii) output an energy schedule for the property to maintain a temperature of the property within the maximum comfort temperature and the minimum comfort temperature at a minimum cost to the user; and/or (ix) control the temperature of the property based upon the energy schedule for the property.

Claims (45)

1 . A smart energy platform for controlling energy consumption at a property, the smart energy platform comprising a controller including one or more processors, a memory device, a plurality of sensors, and at least one local power generation source located at the property, the one or more processors programmed to:

build a model for outputting an energy schedule for a described property based upon historical data for described properties, wherein the historical data includes historical local power generation data and historical property usage data including contextual conditions under which a user has historically been present at the property;

input current energy pricing data corresponding to a location of the property, current local power generation data received from the at least one local power generation source, and current contextual data corresponding to the contextual conditions into the model;

receive an energy schedule for the property output by the model in response to the input, the energy schedule specifying, over a predefined period, at least (i) an operating setting for an at least one heating, ventilation, and air conditioning (HVAC) unit and (ii) an operating setting for the at least one local power generation source, the energy schedule associated with a minimized predicted energy cost over the predefined period while maintaining a temperature of the property within a predefined maximum comfort temperature and a predefined minimum comfort temperature during periods in which the user is predicted to be present at the property; and

control the at least one HVAC unit and the at least one local power generation source based upon the received energy schedule.

2 . The smart energy platform of claim 1 , wherein the plurality of sensors includes a smart thermostat.

3 . The smart energy platform of claim 1 , wherein the processors are further programmed to determine property usage based upon a user presence schedule inputted by the user.

4 . The smart energy platform of claim 1 , wherein the processors are further programmed to determine property usage based upon location data associated with a user computer device of the user.

5 . The smart energy platform of claim 1 , wherein the processors are further programmed to determine property usage based upon data received from the plurality of sensors.

6 . The smart energy platform of claim 1 , wherein the processors are further programmed to update the model based upon a change to one or more of the current energy pricing data, the current local power generation data, and the current contextual data.

7 . The smart energy platform of claim 1 , wherein the current local power generation data includes solar generation data from an at least one solar panel associated with the property indicating an amount of solar energy generated by the at least one solar panel.

8 . The smart energy platform of claim 7 , wherein the processors are further programmed to:

input the solar generation data into the model;

output an energy schedule for the property, wherein the energy schedule is based upon the amount of solar energy generated by the at least one solar panel; and

control the at least one solar panel based upon the energy schedule for the property, wherein the at least one solar panel may be controlled to:

use the generated solar energy in controlling the temperature of the property;

store the generated solar energy in an energy storage system associated with the property; or

send the generated solar energy back to an electric grid connected to the property.

9 . The smart energy platform of claim 1 , wherein the processors are further programmed to determine the location associated with the property based upon location data associated with a user computer device of the user.

10 . The smart energy platform of claim 1 , wherein the processors are further programmed to determine the location associated with the property based upon data received from the plurality of sensors.

11 . A computer-implemented method of using a smart energy platform to control energy consumption at a property, the method implemented using a controller including one or more processors, a memory device, a plurality of sensors, and at least one local power generation source located at the property, the method comprising:

building a model for outputting an energy schedule for a described property based upon historical data for described properties, wherein the historical data includes historical local power generation data and historical property usage data including contextual conditions under which a user has historically been present at the property;

inputting current energy pricing data corresponding to a location of the property, current local power generation data received from the at least one local power generation source, and current contextual data corresponding to the contextual conditions into the model;

receiving an energy schedule for the property output by the model in response to the input, the energy schedule specifying, over a predefined period, at least (i) an operating setting for an at least one heating, ventilation, and air conditioning (HVAC) unit and (ii) an operating setting for the at least one local power generation source, the energy schedule associated with a minimized predicted energy cost over the predefined period while maintaining a temperature of the property within a predefined maximum comfort temperature and a predefined minimum comfort temperature during periods in which the user is predicted to be present at the property; and

controlling the at least one HVAC unit and the at least one local power generation source based upon the received energy schedule.

12 . The computer-implemented method of claim 11 , wherein the plurality of sensors includes a smart thermostat.

13 . The computer-implemented method of claim 11 , wherein the method further comprises determining property usage based upon a user presence schedule inputted by the user.

14 . The computer-implemented method of claim 11 , wherein the method further comprises determining property usage based upon location data associated with a user computer device of the user.

15 . The computer-implemented method of claim 11 , wherein the method further comprises determining property usage based upon data received from the plurality of sensors.

16 . The computer-implemented method of claim 11 , wherein the method further comprises updating the model based upon a change to one or more the current energy pricing data, the current local power generation data, and the current contextual data.

17 . The computer-implemented method of claim 11 , wherein the current local power generation data includes solar generation data from an at least one solar panel associated with the property indicating an amount of solar energy generated by the at least one solar panel.

18 . The computer-implemented method of claim 17 , wherein the method further comprises:

inputting the solar generation data into the model;

outputting an energy schedule for the property, wherein the energy schedule is based upon the amount of solar energy generated by the at least one solar panel; and

controlling the at least one solar panel based upon the energy schedule for the property, wherein the at least one solar panel may be controlled to:

use the generated solar energy in controlling the temperature of the property;

store the generated solar energy in an energy storage system associated with the property; or

send the generated solar energy back to an electric grid connected to the property.

19 . The computer-implemented method of claim 11 , wherein the method further comprises determining the location associated with the property based upon location data associated with a user computer device of the user.

20 . The computer-implemented method of claim 11 , wherein the method further comprises determining the location associated with the property based upon data received from the plurality of sensors.

21 . At least one non-transitory computer-readable storage medium having computer-executable instructions embodied thereon, wherein when executed by one or more processors of a controller of a property, the computer-executable instructions cause the one or more processors to:

build a model for outputting an energy schedule for a described property based upon historical data for described properties, wherein the historical data includes historical local power generation data and historical property usage data including contextual conditions under which a user has historically been present at the property;

input current energy pricing data corresponding to a location of the property, current local power generation data received from at least one local power generation source, and current contextual data corresponding to the contextual conditions into the model;

receiving an energy schedule for the property output by the model in response to the input, the energy schedule specifying, over a predefined period, at least (i) an operating setting for an at least one heating, ventilation, and air conditioning (HVAC) unit and (ii) an operating setting for the at least one local power generation source, the energy schedule associated with a minimized predicted energy cost over the predefined period while maintaining a temperature of the property within a predefined maximum comfort temperature and a predefined minimum comfort temperature during periods in which the user is predicted to be present at the property; and

control the at least one HVAC unit and the at least one local power generation source based upon the received energy schedule.