# US 10,503,194 B2 · Mechanism for weather induced facility energy consumption characterization

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- Number: US 10,503,194 B2
- Document ID: US10503194B2
- Status: Granted
- Kind: B2
- Application number: 16/055,206
- Filed: 2018-08-06
- Published: 2018-12-13
- Granted: 2019-12-10
- Earliest claimed: 2015-03-31
- Assignees: Enel X North America, Inc.
- Applicants: Enernoc, Inc.
- Inventors: Husain Al-Mohssen; Angela S. Bassa; Richard R. Paradis
- Web page: https://patentgrep.com/patent/US10503194B2

## CPC

- G05F 1/66: Regulating electric power
- G05B 13/048: {using a predictor}
- H02J 3/00: Circuit arrangements for AC mains or AC distribution networks
- H02J 3/003: {Load forecast, e.g. methods or systems for forecasting future load demand}
- H02J 3/0075: {for providing alternative feeding paths between load and source according to economic or energy efficiency considerations, e.g. economic dispatch}
- H02J 2103/30: Simulating, planning, modelling, reliability check or computer assisted design [CAD] of electric power networks
- Y02B 90/20: Smart grids as enabling technology in buildings sector (smart grids supporting the management or operation of end-user stationary applications in general, or like technologies with no associated climate change mitigation effect Y04S20/00)
- Y02E 60/00: Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
- Y04S 10/50: Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S 20/00: Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof
- Y04S 40/20: Information technology specific aspects, e.g. CAD, simulation, modelling, system security
- G05F: SYSTEMS FOR REGULATING ELECTRIC OR MAGNETIC VARIABLES
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)
- H02J: ELECTRIC POWER NETWORKS; CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- Y02B: CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
- Y02E: REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
- Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS

## Abstract

A method for characterizing buildings, including retrieving a plurality of baseline energy use data sets for the buildings from a baseline data stores; generating energy use data sets for each of the buildings, each of the energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, where the energy consumption values within each of the sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and where each of the plurality of lag values is different from other ones of the plurality of lag values; performing a non-linear parabolic analysis on the each of the plurality of energy use data sets to yield corresponding non-linear parabolic model parameters and a corresponding residual; determining a least valued residual from all residuals, the least valued residual indicating a corresponding energy lag for the each of the buildings; and categorizing the buildings into types according to similar energy lags.

## Claims

### Claim 1

A building characterization apparatus, comprising:
baseline data storages, configured to store a plurality of baseline energy use data sets for buildings;
a building lag optimizer circuit, configured to receive identifiers for said buildings, and configured to retrieve said plurality of baseline energy use data sets from said baseline data storages for said buildings, and configured to generate energy use data sets for each of said buildings, each of said energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, wherein said energy consumption values within said each of said energy use data sets are shifted by one of a plurality of lag values relative to said corresponding time and outside temperature values, and wherein each of said plurality of lag values is different from other ones of said plurality of lag values, and wherein said plurality of lag values indicates shifts of said energy consumption values to different time and outside temperature values, and wherein said corresponding time values are less than or equal to similar energy lags, and configured to perform a regression analysis on said each of said energy use data sets to yield corresponding regression model parameters and a corresponding residual, and configured to determine a least valued residual from all residuals yielded, said least valued residual indicating a corresponding energy lag for said each of said buildings, and regression model parameters that correspond to said least valued residual, and wherein said corresponding energy lag describes a transient energy consumption period preceding a change in outside temperature;
a dispatch processor, configured to provide said identifiers to said building lag optimizer circuit, and configured to receive a plurality of energy lags, each associated with a corresponding one of said buildings, and configured to generate a dispatch schedule for a demand response program event according to a prioritization of said plurality of energy lags; and
a dispatch control circuit, coupled to said dispatch processor, configured to control a specified load shedding by performing load shedding actions in the order provided by said dispatch schedule, wherein said dispatch schedule directs for dispatch of ones of said buildings having greater energy lags prior to others of said buildings having lesser energy lags.

### Claim 2 (depends on 1)

The apparatus as recited in claim 1, wherein said corresponding time values comprise hourly values and said plurality of lag values spans a 24-hour period.

### Claim 3 (depends on 1)

The apparatus as recited in claim 1, wherein said similar energy lags comprise energy lags having the same value.

### Claim 4 (depends on 1)

The apparatus as recited in claim 1, wherein said similar energy lags comprise energy lags within a range of values.

### Claim 5 (depends on 1)

The apparatus as recited in claim 1, wherein said each of said energy use data sets comprises a first portion of a corresponding each of said plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of said corresponding each of said plurality of baseline energy use data sets.

### Claim 6

An apparatus for characterizing buildings participating in a demand response program, the apparatus comprising:
baseline data storages, configured to store a plurality of baseline energy use data sets for the buildings;
a building lag optimizer circuit, configured to determine an energy lag for one of the buildings, said building lag optimizer circuit comprising:
a thermal response processor, configured to receive one of a plurality of identifiers for said one of the buildings, and configured to retrieve one of said plurality of energy use data sets from said baseline data storages for said one of the buildings, and configured to generate a plurality of energy use data sets for said one of the buildings, each of said plurality of energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, wherein said energy consumption values within said each of said plurality of energy use data sets are shifted by one of a plurality of lag values relative to said corresponding time and outside temperature values, and wherein said plurality of lag values indicates shifts of said energy consumption values to different time and outside temperature values, and wherein said corresponding time values are less than or equal to similar energy lags, and wherein each of said plurality of lag values is different from other ones of said plurality of lag values; and
a regression engine circuit, coupled to said thermal response processor, configured to receive said plurality of energy use data sets, and configured to perform a regression analysis on said each of said plurality of energy use data sets to yield corresponding regression model parameters and a corresponding residual;
wherein said thermal response processor determines a least valued residual from all residuals yielded by said regression engine circuit, said least valued residual indicating said energy lag for said one of the buildings, wherein said energy lag describes a transient energy consumption period preceding a change in outside temperature;
a dispatch processor, configured to retrieve corresponding ones of said plurality of identifiers for all of the buildings, to provide said corresponding ones of said plurality of identifiers to said building lag optimizer circuit, and to receive corresponding energy lags for all of the buildings, and configured to generate a dispatch schedule for a demand response program event according to a prioritization of said corresponding energy lags; and
a dispatch control circuit, coupled to said dispatch processor, configured to control a specified load shedding by performing load shedding actions in the order provided by said dispatch schedule, wherein said dispatch schedule directs for dispatch of ones of the buildings having greater energy lags prior to others of the buildings having lesser energy lags.

### Claim 7 (depends on 6)

The apparatus as recited in claim 6, wherein said corresponding time values comprise hourly values and said plurality of lag values spans a 24-hour period.

### Claim 8 (depends on 6)

The apparatus as recited in claim 6, wherein said similar corresponding energy lags comprise energy lags having the same value.

### Claim 9 (depends on 6)

The apparatus as recited in claim 6, wherein said similar corresponding energy lags comprise energy lags within a range of values.

### Claim 10 (depends on 6)

The apparatus as recited in claim 6, wherein said each of said plurality of energy use data sets comprises a first portion of a corresponding each of said plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of said corresponding each of a plurality of baseline energy use data sets.

### Claim 11

A method for characterizing buildings participating in a demand response program, the method comprising:
retrieving a plurality of baseline energy use data sets for the buildings from a baseline data storages;
receiving identifiers and generating a plurality of energy use data sets for each of the buildings, each of the plurality of energy use data sets comprising energy consumption values along with corresponding time and outside temperature values, wherein the energy consumption values within the each of the plurality of energy use data sets are shifted by one of a plurality of lag values relative to the corresponding time and outside temperature values, and wherein the plurality of lag values indicates shifts of the energy consumption values to different time and outside temperature values, and wherein the corresponding time values are less than or equal to similar energy lags, and wherein each of the plurality of lag values is different from other ones of the plurality of lag values;
performing a regression analysis on the each of the plurality of energy use data sets to yield regression model parameters and a corresponding residual;
determining a least valued residual from all residuals yielded by said performing a regression analysis, the least valued residual indicating a corresponding energy lag for the each of the buildings, wherein the corresponding energy lag describes a transient energy consumption period preceding a change in outside temperature;
employing the corresponding energy lag for the each of the buildings to generate a dispatch schedule for a demand response program event according to a prioritization of energy lags corresponding to the each of the buildings; and
controlling a specified load shedding by performing load shedding actions in the order provided by the dispatch schedule, wherein the dispatch schedule directs for dispatch of ones of the buildings having greater energy lags prior to others of the buildings having lesser energy lags.

### Claim 12 (depends on 11)

The method as recited in claim 11, wherein the corresponding time values comprise hourly values and the plurality of lag values spans a 24-hour period.

### Claim 13 (depends on 11)

The method as recited in claim 11, wherein the similar energy lags comprise energy lags having the same value.

### Claim 14 (depends on 11)

The method as recited in claim 11, wherein the similar energy lags comprise energy lags within a range of values.

### Claim 15 (depends on 11)

The method as recited in claim 11, wherein the each of the plurality of energy use data sets comprises a first portion of a corresponding each of the plurality of baseline energy use data sets, and wherein required energy consumption values resulting from shifts are taken from a second portion of the corresponding each of the plurality of baseline energy use data sets.