Sensor-Based Occupancy and Behavior Prediction Method for Intelligently Controlling Energy Consumption Within a Building

• US 20100025483A1
• Filed: 07/31/2008
• Published: 02/04/2010
• Est. Priority Date: 07/31/2008
• Status: Abandoned Application

• Current Assignee: Robert Bosch GmbH
• Original Assignee: Robert Bosch GmbH
• Inventors: Hoeynck, Michael, Andrews, Burton W.
• Application Number:
  US12/183,361
• Publication Number:
  US 20100025483A1
• Time in Patent Office: Days
• US Class Current: 236/1.C
• CPC Class Codes: F24F 11/30 for purposes related to the operation of the system, e.g. for safety or monitoring
• CPC Class Codes: F24F 11/32 Responding to malfunctions or emergencies
• CPC Class Codes: F24F 11/46 Improving electric energy efficiency or saving
• CPC Class Codes: F24F 2110/00 Control inputs relating to air properties
• CPC Class Codes: F24F 2120/10 Occupancy
• CPC Class Codes: G05B 2219/2614 HVAC, heating, ventillation, climate control
• CPC Class Codes: G05B 2219/2639 Energy management, use maximum of cheap power, keep peak load low
• CPC Class Codes: H02J 2310/14 The load or loads being home appliances
• CPC Class Codes: H02J 2310/64 The condition being economic, e.g. tariff based load management
• CPC Class Codes: H02J 3/003 Load forecast, e.g. methods or systems for forecasting future load demand
• CPC Class Codes: H02J 3/14 by switching loads on to, or off from, network, e.g. progressively balanced loading
• CPC Class Codes: Y02B 70/30 Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of the management of residential or tertiary loads, i.e. smart grids as climate change mitigation technology in the buildings sector, including also the last stages of power distribution and the control, monitoring or operating management systems at local level
• CPC Class Codes: Y02B 70/3225 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/222 Demand response systems, e.g. load shedding, peak shaving
• CPC Class Codes: Y04S 20/242 Home appliances
• CPC Class Codes: Y04S 20/244 the home appliances being or involving heating ventilating and air conditioning [HVAC] units
• CPC Class Codes: Y04S 50/10 Energy trading, including energy flowing from end-user application to grid

Abstract

A method for controlling energy consumption within a building includes providing at least one environment sensing device and at least one energy consumption sensing device associated with the building. Current data is collected from the environment sensing device and the energy consumption sensing device along with associated time-of-day data. A value of a future energy consumption parameter is predicted based upon the collected current data, the associated time-of-day data, and historic data collected from the environment sensing device and the energy consumption sensing device. A profile of future costs per unit of energy consumption as a function of time is determined. Energy consumption is controlled dependent upon the predicted future energy consumption parameter value and the determined profile of energy consumption costs.

Claims

1. A method for controlling energy consumption within a building, the method comprising the steps of:

providing at least one environment sensing device and at least one energy consumption sensing device associated with the building;

collecting current data from the environment sensing device and the energy consumption sensing device along with associated time-of-day data;

predicting a future value of an energy consumption parameter based upon the collected current data, the associated time-of-day data, and historic data collected from the environment sensing device and the energy consumption sensing device;

determining a profile of future costs per unit of energy consumption as a function of time; and

controlling energy consumption dependent upon the predicted future energy consumption parameter value and the determined profile of energy consumption costs.

2. The method of claim 1 wherein the building includes a plurality of rooms, the future value of the energy consumption parameter being predicted on a room-by-room basis, and the energy consumption being controlled on a room-by-room basis.

3. The method of claim 1 wherein the predicted energy consumption parameter value corresponds to a time that is less than twenty-five hours into the future, and the profile of future costs per unit of energy consumption as a function of time has a horizon of less than twenty-five hours.

4. The method of claim 1 wherein the controlling step includes selecting a future time at which a rate of energy consumption is to be changed.

5. The method of claim 1 wherein the energy consumption parameter comprises a human presence parameter.

6. The method of claim 1 wherein the energy consumption parameter comprises an ambient temperature within the building.

7. The method of claim 1 wherein the environment sensing device comprises at least one of a motion detector, sound detector, carbon dioxide detector, door movement detector, and electronic card reader.

8. A method for controlling energy consumption within a building, the method comprising the steps of:

providing at least one human presence sensing device and at least one energy consumption sensing device associated with the building;

collecting current data from the human presence sensing device and the energy consumption sensing device along with associated time-of-day data;

predicting a future value of a human presence parameter based upon the collected current data, the associated time-of-day data, and historic data collected from the human presence sensing device and the energy consumption sensing device; and

controlling energy consumption dependent upon the predicted future value of the human presence parameter.

9. The method of claim 8 comprising the further step of determining a profile of future costs per unit of energy consumption as a function of time, the controlling step being dependent upon the determined profile of energy consumption costs.

10. The method of claim 8 wherein the building includes a plurality of rooms, the future value of the human presence parameter being predicted on a room-by-room basis, and the energy consumption being controlled on a room-by-room basis.

11. The method of claim 8 wherein the human presence parameter comprises a number of persons in the building.

12. The method of claim 8 wherein the predicting step includes identifying a trend in the historic data and extrapolating the collected current data based on the trend.

13. The method of claim 8 wherein the trend includes future changes in the human presence parameter as a function of a characteristic of the energy consumption sensed by the energy consumption sensing device.

14. The method of claim 8 wherein the controlling step includes selecting at least one of a future time at which a rate of energy consumption is to be changed and a change in the rate of energy consumption.

15. A method for controlling HVAC operation within a building, the method comprising the steps of:

providing at least one environment sensing device associated with the building;

collecting current data from the environment sensing device;

predicting a future temperature associated with the building based upon the collected current data, and historic data collected from the environment sensing device; and

controlling operation of an HVAC system dependent upon the predicted future temperature.

16. The method of claim 15 comprising the future steps of:

providing at least one energy consumption sensing device associated with the building; and

collecting current data from the energy consumption sensing device;

wherein the future temperature associated with the building is predicted based upon the collected current data, and historic data collected from the energy consumption sensing device.

17. The method of claim 15 comprising the further step of determining a profile of future costs per unit of energy consumption as a function of time, the controlling step being dependent upon the determined profile of energy consumption costs.

18. The method of claim 15 wherein the building includes a plurality of rooms, the future temperature associated with the building being predicted on a room-by-room basis, and the energy consumption being controlled on a room-by-room basis.

19. The method of claim 15 wherein the future temperature associated with the building is predicted based upon the HVAC system being idle between a time of the predicting step and a time of the future temperature.

20. The method of claim 15 comprising the further step of predicting a future value of a human presence parameter, the operation of the HVAC system being controlled dependent upon the predicted future value of the human presence parameter.