METHODS AND SYSTEMS FOR AUTO BENCHMARKING OF ENERGY CONSUMING ASSETS ACROSS DISTRIBUTED FACILITIES

• US 20170213177A1
• Filed: 03/08/2016
• Published: 07/27/2017
• Est. Priority Date: 01/22/2016
• Status: Abandoned Application

• Current Assignee: Carrier Corporation (Carrier Global Corporation)
• Original Assignee: Wipro Limited
• Inventors: MANDAL, Subhasis, MEGHANI, Ravi
• Application Number:
  US15/063,882
• Publication Number:
  US 20170213177A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y02P 90/82 Energy audits or management systems therefor

Abstract

In one embodiment, a method of benchmarking energy assets is disclosed. The method includes filtering asset data received from a plurality of energy assets based on constraints to generate filtered asset data; creating a plurality of data profiles using the filtered asset data based on profiling variables; identifying at least one benchmarking variable and at least one normalizing variable for the plurality of energy assets for a data profile in the plurality of data profiles; iteratively determining correlation between the at least one benchmarking variable and the at least one normalizing variable; and normalizing the at least one benchmarking variable using the at least one normalizing variables in response to determining the correlation to generate benchmarks for each of the at least one benchmarking variable.

Claims

6-1. The method of claim 1, wherein the at least one profiling variable is selected from a group comprising type of operations, facility type, day of the week, climate zones, and asset make.

10. A system for benchmarking energy assets, the system comprising:

at least one processors; and

a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising;

filtering asset data received from a plurality of energy assets based on constraints to generate filtered asset data;

creating a plurality of data profiles using the filtered asset data based on profiling variables;

identifying at least one benchmarking variable and at least one normalizing variable for the plurality of energy assets for a data profile in the plurality of data profiles;

iteratively determining correlation between the at least one benchmarking variable and the at least one normalizing variable; and

normalizing the at least one benchmarking variable using the at least one normalizing variables in response to determining the correlation to generate benchmarks for each of the at least one benchmarking variable.

11. The system of claim 10, wherein the operation of iteratively determining correlation comprises operation of determining at least one normalization coefficient associated with the at least one normalizing variable for the at least one benchmarking variable.

12. The system of claim 11, wherein the operation of normalizing comprises operation of applying a normalization coefficient within the at least one normalization coefficients to an associated benchmark variable to generate normalized asset data.

13. The system of claim 10, wherein the operations further comprises presenting benchmarked values for each asset along with the minimum, maximum and mean values.

14. The system of claim 10, wherein the operations further comprise collecting asset data from the plurality of energy assets, the plurality of energy assets being distributed across multiple locations.

15. The system of claim 10, wherein asset data for an asset is selected from a group comprising temperature of the asset, pressure associated with the asset, flow associated with the asset, power associated with the asset, run-hours of the asset, utilization level of the asset, damper states of the asset, operating speeds of the asset, operation state of the asset, humidity levels of the asset, consumption of the asset.

16. The system of claim 10, wherein the at least one profiling variable is selected from a group comprising type of operations, facility type, day of the week, climate zones, and asset make.

17. The system of claim 10, wherein the at least one benchmarking variable is selected from a group comprising zone temperature for an asset or an asset group, supply temperature for an asset, supply static pressure for an asset, refrigerant pressure for an asset, run-hours for an asset, temperature difference across asset input/output, consumption of an asset or an asset group, and setpoints maintained.

18. The system of claim 10, wherein the at least one normalizing variable is selected from a group comprising outside air temperature, outside air humidity, outside air dewpoint, age of an asset, area served, available capacity of the group, and zone temperature maintained by the group.

20. A non-transitory computer-readable storage medium for benchmarking energy assets, when executed by a computing device, cause the computing device to:

filter asset data received from a plurality of energy assets based on constraints to generate filtered asset data;

create a plurality of data profiles using the filtered asset data based on profiling variables;

identify at least one benchmarking variable and at least one normalizing variable for the plurality of energy assets for a data profile in the plurality of data profiles;

iteratively determine correlation between the at least one benchmarking variable and the at least one normalizing variable; and

normalize the at least one benchmarking variable using the at least one normalizing variables in response to determining the correlation to generate benchmarks for each of the at least one benchmarking variable.