System for providing remote building efficiency audits

Patent metadata

Field	Value
Publication number	US-10754918-B2
Application number	US-201615051548-A
Country	US
Kind code	B2
Filing date	Feb 23, 2016
Priority date	Feb 23, 2016
Publication date	Aug 25, 2020
Grant date	Aug 25, 2020

Abstract

The subject disclosure relates to systems and methods for calculating a thermal sensitivity score. In some aspects, the method includes steps for receiving temperature information for a first geographic location, receiving resource consumption data for each of a plurality of similar consumption locations in the first geographic location, and generating, by the processors, a thermal sensitivity model based on the temperature information and the resource consumption data for each of the plurality of similar consumption locations. In some aspects, the steps can further include computing a thermal sensitivity score for each of the similar consumption locations using the thermal sensitivity model. Systems and machine readable media are also provided.

First claim

What is claimed is:

1. A computer-implemented method, comprising:
receiving, by one or more processors, temperature information for a first geographic location over a first time period;
receiving, by the processors, resource consumption data for each of a plurality of consumption locations in the first geographic location over the first time period;
generating, by the processors, a thermal sensitivity model based on the temperature information and the resource consumption data for each of the plurality of consumption locations;
computing, by the processors, a thermal sensitivity score for each of the consumption locations using the thermal sensitivity model, wherein each of the thermal sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to temperature fluctuations in the first geographic location;
comparing the thermal sensitivity scores from each of the plurality of consumption locations and ranking the plurality of consumption locations based at least on the thermal sensitivity scores;
identifying, by the processors, a target consumption location, from among the plurality of consumption locations, wherein identifying the target consumption location further comprises:
calculating a wind sensitivity score for each of the plurality of consumption locations using a wind sensitivity model, wherein each of the wind sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to wind speed fluctuations in the first geographic location;
calculating a solar sensitivity score for each of the plurality of consumption locations using a solar sensitivity model, wherein each of the solar sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to sun light intensity fluctuations in the first geographic location; and
identifying the target consumption location based on one or more of: the thermal sensitivity score, the wind sensitivity score, and the solar sensitivity score;

wherein the target consumption location is identified as at least one location that is a least efficient consumption location from among the consumption locations based on the ranking of the thermal sensitivity scores;
generating, by the processors, a targeted notification for a utility customer associated with the target consumption location identified from the plurality of consumption locations, wherein the targeted notification comprises one or more energy efficiency tips that (i) are selected based on two or more of the thermal sensitivity score, the wind sensitivity score, or the solar sensitivity score associated with the target consumption location, and (ii) include instructions for identifying and eliminating thermal leaks in a structure; and
transmitting, by the processors, the targeted notification to a device associated with the target consumption location.

2. The computer-implemented method of claim 1 , wherein generating the thermal sensitivity model further comprises:
computing a regression model using the temperature information for the first geographic location and the resource consumption data for each of the consumption locations.

3. The computer-implemented method of claim 1 , wherein generating the thermal sensitivity model further comprises:
processing the temperature information and the resource consumption data to calculate a cooling coefficient.

4. The computer-implemented method of claim 1 , wherein generating the thermal sensitivity model further comprises:
processing the temperature information and the resource consumption data to calculate a heating coefficient.

5. The computer-implemented method of claim 1 , wherein computing the thermal sensitivity score, further comprises:
determining one or more temperature difference values using the temperature information for the first geographic location; and
calculating a cooling coefficient using the resource consumption data and the one or more temperature difference values.

6. The computer-implemented method of claim 1 , wherein the resource consumption data comprises one or more of: electric energy consumption data, natural gas consumption data, or water use data.

7. The computer-implemented method of claim 1 , wherein at least two of the consumption locations are selected based on geographic location, square footage, or building height.

8. A computer-implemented method, comprising:
receiving, by one or more processors, two or more of temperature information, wind speed information, and solar exposure information for a first geographic location over a first time period;
receiving, by the processors, resource consumption data for each of a plurality of consumption locations in the first geographic location over the first time period;
generating, by the processors, two or more models selected from: (i) a thermal sensitivity model based on the temperature information and the resource consumption data for each of the plurality of consumption locations, (ii) a wind sensitivity model based on the wind speed information and the resource consumption data for each of the plurality of sir consumption locations, and (iii) a solar sensitivity model based on the solar exposure information and the resource consumption data for each of the plurality of consumption locations;
computing, by the processors, two or more sensitivity scores corresponding to the selected models, comprising:
(i) a thermal sensitivity score for each of the consumption locations using the thermal sensitivity model, wherein each of the thermal sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to temperature fluctuations in the first geographic location;
(ii) a wind sensitivity score for each of the consumption locations using the wind sensitivity model, wherein each of the wind sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to wind speed fluctuations in the first geographic location; and
(iii) a solar sensitivity score for each of the consumption locations using the solar sensitivity model, wherein each of the solar sensitivity scores indicates a relative energy use sensitivity for a corresponding consumption location relative to sun light intensity fluctuations in the first geographic location;

identifying, by the processors, a target consumption location, from among the plurality of consumption locations, based on the two or more sensitivity scores for the target consumption location;
wherein the target consumption location is identified as at least one location that is a least efficient consumption location from among the consumption locations based on the two or more sensitivity scores;
generating, by the processors, a targeted notification for a utility customer associated with the target consumption location identified from the plurality of consumption locations, wherein the targeted notification comprises one or more energy efficiency tips that (i) are selected based on the two or more sensitivity scores associated with the target consumption location, and (ii) include instructions for identifying and eliminating thermal leaks in a structure; and
transmitting, by the processors, the targeted notification to a device associated with the target consumption location.

9. The system of claim 8 , wherein computing the thermal sensitivity score further comprises:
generating, by the processors, the thermal sensitivity model based on the temperature information and the resource consumption data.

10. The system of claim 9 , wherein generating the thermal sensitivity model further comprises:
computing a re

Assignees

• Opower Inc

Inventors

• Yu Suelyn
• Chung Garner
• Packer Benjamin
• Shilts Erik

Classifications

• G05B15/02 Primary

  electric · CPC title

• G06Q10/00

  Administration; Management · CPC title

• G05B17/02

  electric · CPC title

• G06F17/10 Primary

  Complex mathematical operations {(function generation by table look-up G06F1/03; evaluation of elementary functions by calculation G06F7/544)} · CPC title