ARCHITECTURE FOR ENERGY MANAGEMENT OF MULTI CUSTOMER MULTI TIME ZONE DISTRIBUTED FACILITIES

• US 20130261833A1
• Filed: 08/24/2012
• Published: 10/03/2013
• Est. Priority Date: 04/02/2012
• Status: Active Grant

• Current Assignee: Carrier Corporation (Carrier Global Corporation)
• Original Assignee: Sudipta Ghosh
• Inventors: Srivastava, Anurag, Meghani, Ravi, Srivastava, Rohit, Mandal, Subhasis, Ghosh, Sudipta
• Granted Patent: US 10,013,725 B2
• Time in Patent Office: Days
• US Class Current: 700/297
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 50/06 Energy or water supply
• CPC Class Codes: Y02P 90/84 Greenhouse gas [GHG] management systems

Abstract

A system and method for energy management for multi customer multi time zone distributed facilities are disclosed. In one embodiment, data associated with the energy management of the multi customer distributed facilities located in different time zones is obtained based on associated energy models by a data acquisition/integration layer. Further, the obtained data for energy management of the multi customer distributed facilities is transformed by a data management layer. Furthermore, control commands are generated using the transformed data and associated one or more pre-defined thresholds and set-points by an energy transaction layer. Also, energy of the multi customer distributed facilities is substantially simultaneously managed using the generated control commands by the energy transaction layer.

Claims

1. A computer implemented method for energy management of multi customer distributed facilities located in different time zones, comprising:

obtaining data associated with energy management of the multi customer distributed facilities located in different time zones based on associated energy models by a data acquisition/integration layer;

transforming the obtained data for energy management of the multi customer distributed facilities by a data management layer;

generating control commands using the transformed data and associated one or more pre-defined thresholds and set-points by an energy transaction layer; and

substantially simultaneously managing energy of the multi customer distributed facilities using the generated control commands by the energy transaction layer.

2. The computer implemented method of claim 1, wherein the data associated with the energy management of the multi customer distributed facilities comprises automated meter data, emissions data, digital invoice data, device and sensor data, enterprise resource planning (ERP) data, weather data, emergency alert data and/or service desk data.

3. The computer implemented method of claim 1, wherein transforming the obtained data for energy management of the multi customer distributed facilities by the data management layer comprises:

mediating the obtained data by a data mediation module in the data management layer;

normalizing the mediated data by a data normalization module in the data management layer; and

validating the normalized data by a data validation module in the data management layer.

4. The computer implemented method of claim 1, further comprising:

forming the associated energy models of the multi customer distributed facilities based on parameters selected from the group consisting of facility characteristics, device characteristics, service characteristics, customer needs, available energy sources, customer policies, and regulatory policies using a user interface layer.

5. The computer implemented method of claim 4, further comprising:

inputting the customer policies and regulatory policies in to an energy efficiency management layer using the user interface layer.

6. The computer implemented method of claim 5, wherein generating the control commands using the transformed data and associated one or more pre-defined thresholds and set-points by the energy transaction layer comprises:

generating control commands based on the transformed data, associated updated one or more pre-defined thresholds and set-points and dynamic decisions obtained from the energy efficiency management layer by the energy transaction layer.

7. The computer implemented method of claim 6, further comprising:

dynamically updating the one or more predefined thresholds and set-points based on operational data obtained from the energy transaction layer by the energy efficiency management layer.

8. The computer implemented method of claim 6, further comprising:

updating the one or more predefined thresholds and set-points based on an energy knowledge base in a framework and utilities layer by the energy efficiency management layer.

9. The computer implemented method of claim 8, further comprising:

performing statistical and root-cause analysis on operational data by the framework and utilities layer to obtain energy optimization data upon receiving a request from the energy efficiency management layer; and

updating energy management information using the energy optimization data by the energy efficiency management layer.

10. The computer implemented method of claim 9, further comprising:

intelligently reporting performance, compliance and efficacy of a system for the multi customer distributed facilities by the framework and utilities layer via the user interface layer.

11. The computer implemented method of claim 1, wherein the control commands comprise thermal control, consumption control, operational modes control, utilization control, demand control, eco-mode control, energy source control, carbon emission control, and/or performance monitoring control.

12. The computer implemented method of claim 1, wherein managing the energy comprises event management, asset management and/or billing, invoicing and cost optimization management.

13. The computer implemented method of claim 1, further comprising:

processing data by the energy transaction layer to obtain energy efficiency improvement features selected from the group consisting of consumption profiling by an operation mode, thermal profiling by service consumption, normalization of data obtained from multiple time zones, consumption data profiling by service type using virtual meters and model information and intelligent estimation techniques for missing consumption information, thermal profiling of service consumption areas (SCAs), eco-mode profiling, savings estimation, asset utilization and capacity profiling, data validation based on customer and region characteristics, correlated validation, correlated data, device characteristic validation, industry, past performance, climate, policies, load conditions, and service for validation, device, area and service chain based event/ticket enrichment of dependent devices, services, and areas.

14. An energy management system (EMS) for energy management of multi customer distributed facilities located in different time zones, comprising:

a processor;

memory coupled to the processor; and

an energy management engine residing in the memory, wherein the energy management engine comprises;

a data acquisition/integration layer for obtaining data associated with energy management of the multi customer distributed facilities based on associated energy models;

a data management layer for transforming the obtained data for energy management of the multi customer distributed facilities; and

an energy transaction layer for;

generating control commands using the transformed data and associated one or more pre-defined thresholds and set-points; and

managing energy of the multi customer distributed facilities using the generated control commands.

15. The EMS of claim 14, wherein the data associated with the energy management of the multi customer distributed facilities comprises automated meter data, emissions data, digital invoice data, device and sensor data, enterprise resource planning (ERP) data, weather data, emergency alert data and/or service desk data.

16. The EMS of claim 14, wherein the data management layer further comprises a data validation module, a data normalization module, and/or a data mediation module, wherein the data mediation module mediates the obtained data, wherein the data normalization module normalizes the mediated data and wherein the data validation module validates the normalized data.

17. The EMS of claim 14, wherein the energy management engine further comprises a user interface layer, wherein the associated energy models of the multi customer distributed facilities are formed based on parameters selected from the group consisting of facility characteristics, device characteristics, service characteristics, customer needs, available energy sources, customer policies, and regulatory policies using the user interface layer.

18. The EMS of claim 17, wherein the framework and utilities layer is further configured to:

intelligently report performance, compliance and efficacy of the EMS for the multi customer distributed facilities via the user interface layer.

19. The EMS of claim 17, wherein the user interface layer is further configured to:

input the customer policies and regulatory policies in to an energy efficiency management layer.

20. The EMS of claim 18, wherein the energy efficiency management layer is further configured to:

dynamically update the one or more predefined thresholds and set-points based on operational data obtained from the energy transaction layer.

21. The EMS of claim 18, wherein the energy efficiency management layer is further configured to:

update the one or more predefined thresholds and set-points based on an energy knowledge base in the framework and utilities layer.

22. The EMS of claim 18, wherein the energy transaction layer is configured to:

generate control commands based on the transformed data and associated updated one or more pre-defined thresholds and set-points and dynamic decisions obtained from the energy efficiency management layer.

23. The EMS of claim 18, wherein the framework and utilities layer is further configured to:

perform statistical and root-cause analysis on operational data to obtain energy optimization data upon receiving a request from the energy efficiency management layer.

24. The EMS of claim 23, wherein the energy efficiency management layer is further configured to:

update energy management information using the energy optimization data.

25. The EMS of claim 14, wherein the control commands comprise thermal control, consumption control, operational modes control, utilization control, demand control, eco-mode control, energy source control, carbon emission control, and/or performance monitoring control.

26. The EMS of claim 14, wherein managing the energy comprises event management, asset management and/or billing, invoicing and cost optimization management.

27. The EMS of claim 14, wherein the energy transaction layer is further configured to:

process data to obtain energy efficiency improvement features selected from the group consisting of consumption profiling by an operation mode, thermal profiling by service consumption, normalization of data obtained from multiple time zones, consumption data profiling by service type using virtual meters and model information and intelligent estimation techniques for missing consumption information, thermal profiling of service consumption areas (SCAs), eco-mode profiling, savings estimation, asset utilization and capacity profiling, data validation based on customer and region characteristics, correlated validation, correlated data, device characteristic validation, industry, past performance, climate, policies, load conditions, and service for validation, device, area and service chain based event/ticket enrichment of dependent devices, services, and areas.

28. At least one non-transitory computer-readable storage medium for energy management of multi customer distributed facilities located in different time zones, when executed by a computing device, cause the computing device to:

obtain data associated with energy management of the multi customer distributed facilities located in different time zones based on associated energy models by a data acquisition/integration layer;

transform the obtained data for energy management of the multi customer distributed facilities by a data management layer;

generate control commands using the transformed data and associated one or more pre-defined thresholds and set-points by an energy transaction layer; and

substantially simultaneously manage energy of the multi customer distributed facilities using the generated control commands by the energy transaction layer.