CLOUD ENABLED BUILDING AUTOMATION SYSTEM

• US 20130274940A1
• Filed: 06/13/2013
• Published: 10/17/2013
• Est. Priority Date: 03/05/2012
• Status: Active Grant

• Current Assignee: Siemens AG
• Original Assignee: Siemens Corp. (Siemens AG)
• Inventors: Wei, Dong, Ji, Kun, Song, Zhen, Darie, Florin
• Granted Patent: US 9,535,411 B2
• Time in Patent Office: Days
• US Class Current: 700/291
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G05B 19/02 electric
• CPC Class Codes: G05B 2219/2642 Domotique, domestic, home control, automation, smart house
• CPC Class Codes: G06Q 50/06 Energy or water supply

Abstract

A method of controlling energy consumption in a building. The method includes receiving occupant request data comprising a plurality of requests, wherein each of the plurality of requests corresponds to one of a plurality of zones in the building wherein the occupant request data is received via a cloud computing resource. The method also includes receiving weather data comprising at least one of current weather measurement data and weather forecast data wherein the weather data is received via a cloud computing resource. In addition, a facility management rule is received via a cloud computing resource. Further, the method includes generating a plurality of output control signals via cloud computing resource, wherein each of the plurality of output control signals is based on one of a plurality of requests and predicted occupant schedules, energy price data and the facility management rule. The control signals are generated by using simulation-based model predictive control method to determine a set of optimized control signals based on optimized energy use or optimized energy cost. The optimized control signals are transmitted to controllers.

Claims

1. A method of controlling energy consumption in a building, comprising:

receiving occupant request data comprising a plurality of requests , wherein each of the plurality of requests corresponds to one of a plurality of zones in the building wherein the occupant request data is received via a cloud computing resource;

receiving occupant schedule data comprising a plurality of predicted occupant schedules , wherein each of the plurality of predicted occupant schedules corresponds to one of the plurality of zones in the building wherein the occupant request data is received via a cloud computing resource;

receiving weather data comprising at least one of current weather measurement data and weather forecast data wherein the weather data is received via a cloud computing resource;

receiving energy price data comprising at least one of current energy price data and predicted energy price data via a cloud computing resource;

receiving sensor and actuator data comprising data collected by controllers located in the building wherein the sensor and actuator data is received via a cloud computing resource;

receiving a facility management rule via a cloud computing resource;

generating a plurality of output control signals (such as set points of temperature, humidity, open/close of valves), wherein each of the plurality of output control signals is based on one of the plurality of requests, one of the plurality of predicted occupant schedules, the energy price data and the facility management rule and each of the plurality of output control signals is configured to adjust building control devices in the plurality of zones in the building wherein the output control signals are generated via a cloud computing resource;

simulating each of the control signals via a cloud computing resource to determine an optimized control signal based on optimized energy use or optimized cost; and

transmitting the optimized output control signal to a building automation system (BAS) of the building.

2. The method of claim 1, further comprising:

determining a peak energy load time based on the energy price data, wherein the output control signal is further configured to pre-cool or pre-heat the building during a time that does not correspond to the peak energy load time.

3. The method of claim 1, further comprising:

generating a notification indicating that the current request does not comply with the facility management rule upon determining that the current request does not comply with the facility management rule; and

transmitting the output control signal to the BAS upon determining that the current request complies with the facility management rule, wherein the output control signal reflects the current request.

4. The method of claim 3, further comprising:

transmitting the output control signal to the BAS upon determining that the current request does not comply with the facility management rule, wherein the output control signal reflects a closest value relative to the current request that complies with the facility management rule.

5. The method of claim 1, wherein the occupant request data includes a preferred temperature.

6. The method of claim 1, wherein the occupant schedule data includes preferred office hours, meeting rooms and schedules.

7. The method of claim 1, wherein the output control signal comprises a set-point corresponding to a target temperature and the building control device is a thermostat.

8. The method of claim 1, wherein the output control signal comprises a set-point corresponding to a target luminance value and the building control device is a lighting system.

9. The method of claim 1, further comprising:

setting a schedule for receiving at least one of the occupancy data, the weather data, and the energy price data.

10. The method of claim 1, wherein at least one of the occupancy data, the weather data, and the energy price data are received from a remote database.

11. A method of controlling energy consumption in a building, comprising:

providing a run-time module configured to receive occupant schedule data comprising a predicted occupant schedule, and weather data comprising at least one of current weather measurement data and weather forecast data wherein the occupant schedule data and weather forecast data are provided by a cloud computing resource;

providing a human-machine interface (HMI) configured to receive occupant request data comprising a current request;

simulating each of the control signals via a cloud computing resource to determine a simulated signal based on optimized energy use or optimized cost; and

providing an interface module configured to receive an output control signal from the run-time module and transmit the output control signal to a building automation system (BAS) of a building, wherein the output control signal is based on the occupant schedule data, the weather data, the occupant request data, and the simulated signal, and the output control signal is configured to adjust a building control device in a zone in the building.

12. The method of claim 11, further comprising:

receiving energy price data including at least one of current energy price data and predicted energy price data wherein the output control signal is further based on the energy price data.

13. The method of claim 12, further comprising:

determining a peak energy load time based on the energy price data, wherein the output control signal is further configured to pre-cool or pre-heat the building during a time that does not correspond to the peak energy load time.

14. The method of claim 11, further comprising:

receiving a facility management rule wherein the output control signal is further based on the facility management rule.

15. The method of claim 14, further comprising:

generating a notification indicating that the current request does not comply with the facility management rule upon determining that the current request does not comply with the facility management rule; and

transmitting the output control signal to the BAS upon determining that the current request complies with the facility management rule, wherein the output control signal reflects the current request.

16. The method of claim 11, wherein the output control signal comprises a set-point corresponding to a target temperature and the building control device is a thermostat.

17. An energy management controller, comprising:

a run-time module configured to receive occupant schedule data comprising a predicted occupant schedule, and weather data comprising at least one of current weather measurement data and weather forecast data wherein the occupant schedule data and weather forecast data are received via a cloud computing resource;

a human-machine interface (HMI) configured to receive occupant request data comprising a current request; and

an interface module configured to receive an output control signal from the run-time module and transmit the output control signal to a building automation system (BAS) of a building, wherein the output control signal is based on the occupant schedule data, the weather data, and the occupant request data, and the output control signal is configured to adjust a building control device in a zone in the building.

18. The energy management controller of claim 17, wherein the run-time module is further configured to receive energy price data comprising at least one of current energy price data and predicted energy price data, and the output control signal is further based on the energy price data.

19. The energy management controller of claim 18, wherein the run-time module is further configured to determine a peak energy load time based on the energy price data, and the output control signal is further configured to pre-cool or pre-heat the zone in the building during a time that does not correspond to the peak energy load time.

20. The energy management controller of claim 17, wherein the HMI is further configured to receive a facility management rule, and the output control signal is further based on the facility management rule.