Building energy management system with energy analytics

Patent metadata

Field	Value
Publication number	US-11268732-B2
Application number	US-201916728858-A
Country	US
Kind code	B2
Filing date	Dec 27, 2019
Priority date	Jan 22, 2016
Publication date	Mar 8, 2022
Grant date	Mar 8, 2022

Abstract

A building energy management system includes building equipment, a data collector, an analytics service, a timeseries database, and an energy management application. The building equipment monitor and control one or more variables in the building energy management system and provide data samples of the one or more variables. The data collector collects the data samples from the building equipment and generates a data timeseries including a plurality of the data samples. The analytics service performs one or more analytics using the data timeseries and generates a results timeseries including a plurality of result samples indicating results of the analytics. The timeseries database stores the data timeseries and the results timeseries. The energy management application retrieves the data timeseries and the results timeseries from the timeseries database in response to a request for timeseries data associated with the one or more variables.

First claim

What is claimed is:

1. A building energy management system of a building comprising:
one or more memory devices configured to store instructions thereon, that, when executed by one or more processors, cause the one or more processors to:
collect data samples of one or more variables of the building from building equipment and generate a resource consumption timeseries indicating resource consumption of the building at a plurality of points in time;
perform one or more energy analytics using the resource consumption timeseries and generate an energy usage metric timeseries comprising a plurality of result samples indicating an energy usage metric for the building;
store the energy usage metric timeseries in a database; and
receive a request for timeseries data associated with the one or more variables and retrieve the energy usage metric timeseries from the database.

2. The building energy management system of claim 1 , further comprising the building equipment operable to monitor and control the one or more variables in the building energy management system and to provide the data samples of the one or more variables.

3. The building energy management system of claim 1 , wherein the resource consumption timeseries includes at least one of electric consumption values, water consumption values, or natural gas consumption values.

4. The building energy management system of claim 1 , wherein the instructions cause the one or more processors to:
identify a type of the building associated with the resource consumption timeseries; and
generate a plot comprising a graphical representation of the energy usage metric for the building and one or more benchmark energy usage metrics for other buildings of the type.

5. The building energy management system of claim 1 , wherein the instructions cause the one or more processors to:
use the data samples of the resource consumption timeseries to calculate a plurality of night-to-day load ratios, one night-to-day load ratio for each day of a plurality of days associated with the resource consumption timeseries;
compare each of the plurality of night-to-day load ratios to a threshold load ratio;
generate a result sample for each of the plurality of days associated with the resource consumption timeseries, wherein the result sample for each of the plurality of days indicates whether a particular night-to-day load ratio for a corresponding day exceeds the threshold load ratio; and
store the result sample for each of the plurality of days as a results timeseries.

6. The building energy management system of claim 1 , wherein the instructions cause the one or more processors to:
use the data samples of the resource consumption timeseries to calculate a plurality of weekend-to-weekday load ratios, one weekend-to-weekday load ratio of the plurality of weekend-to-weekday load ratios for each week of a plurality of weeks associated with the resource consumption timeseries;
compare each of the plurality of weekend-to-weekday load ratios to a threshold load ratio;
generate a result sample for each of the plurality of weeks associated with the resource consumption timeseries, wherein the result sample for each of the plurality of weeks indicates whether a particular weekend-to-weekday load ratio for a corresponding week exceeds the threshold load ratio; and
store the result sample for each of the plurality of weeks as the energy usage metric timeseries.

7. The building energy management system of claim 1 , wherein the instructions cause the one or more processors to perform one or more analytics using the resource consumption timeseries and generate the energy usage metric timeseries, the energy usage metric timeseries comprising the plurality of result samples indicating results of the one or more analytics;
wherein the one or more analytics comprise an energy benchmarking analytic that uses the energy usage metric timeseries to calculate the energy usage metric for the building associated with the resource consumption timeseries, the energy usage metric comprising at least one of energy usage intensity (EUI) or energy density.

8. The building energy management system of claim 7 , wherein the instructions cause the one or more processors to calculate the EUI for the building by:
identifying a total area of the building associated with the resource consumption timeseries;
determining a total resource consumption of the building over a time period associated with the resource consumption timeseries based on the data samples of the resource consumption timeseries; and
using the total area of the building and the total resource consumption of the building to calculate the resource consumption per unit area of the building.

9. The building energy management system of claim 1 , wherein the instructions cause the one or more processors to generate a results timeseries by removing an effect of weather from the resource consumption timeseries.

10. The building energy management system of claim 9 , wherein the instructions cause the one or more processors to remove the effect of weather from the resource consumption timeseries by:
generating a regression model that defines a relationship between the data samples of the resource consumption timeseries and one or more weather-related variables;
determining values of the one or more weather-related variables during a time period associated with the resource consumption timeseries;
applying values of the one or more weather-related variables as inputs to the regression model to estimate weather-normalized values of the data samples; and
storing the weather-normalized values of the data samples as the energy usage metric timeseries.

11. The building energy management system of claim 10 , wherein:
the one or more weather-related variables comprise at least one of a cooling degree day (CDD) variable and a heating degree day (HDD) variable;
the regression model is an energy consumption model that defines energy consumption as a function of at least one of the CDD variable and the HDD variable.

12. The building energy management system of claim 10 , wherein generating the regression model comprises:
using weather data for a baseline period to calculate a value for at least one of a cooling degree day (CDD) variable and a heating degree day (HDD) variable for each day of a plurality of days in the baseline period;
determining at least one of a plurality of first average daily values for the CCD variable, one first average daily value of the plurality of first average daily values for each time interval of a plurality of time intervals in the baseline period and a plurality of second average daily values of the HDD variable, one second average daily value of the plurality of second average daily values for each of the plurality of time intervals in the baseline period;
using energy consumption data for the baseline period to determine a plurality of average daily energy consumption values, one average daily energy consumption value of the plurality of average daily energy consumption values for each of the plurality of time intervals in the baseline period; and
generating regression coefficients for the regression model by fitting the plurality of average daily energy consumption values to at least one of the plurality of first average daily values of the CDD variable and the plurality of second average daily values of the HDD variable.

13. A method of building management comprising:
collecting, by one or more processing circuits, data samples of one or more variables of a building from building equipment and generate a resource consumption timeseries indicating resource

Assignees

• Johnson Controls Tech Co

Inventors

• Boettcher Andrew J
• Vitullo Steven R
• Narain Vivek
• Park Youngchoon
• Asp Gerald A
• Craig Peter A
• Chennupati Vijaya S

Classifications

• H02J2103/30

  Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks · CPC title

• H02J13/12

  Monitoring network conditions, e.g. electrical magnitudes or operational status · CPC title

• H02J13/14 Primary

  the power network being locally controlled, e.g. home energy management systems [HEMS] · CPC title

• H02J3/14

  by switching loads on to, or off from, the networks, e.g. progressively balanced loading · CPC title

• F24F11/62 Primary

  characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values · CPC title