# US 10,371,405 B2 · Building power management systems

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 10,371,405 B2
- Document ID: US10371405B2
- Status: Granted
- Kind: B2
- Application number: 14/778,956
- Filed: 2014-03-21
- Published: 2016-03-03
- Granted: 2019-08-06
- Earliest claimed: 2013-03-21
- Assignees: Cornell University
- Applicants: Cornell University
- Inventors: David H. Albonesi; Howard Chong; Brandon Hencey; Christine A. Shoemaker
- Web page: https://patentgrep.com/patent/US10371405B2

## CPC

- F24F 11/47: Responding to energy costs
- F24F 11/30: for purposes related to the operation of the system, e.g. for safety or monitoring
- F24F 11/58: using Internet communication
- F24F 11/62: characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F 11/63: Electronic processing
- F24F 11/70: Control systems characterised by their outputs; Constructional details thereof
- F24F 11/89: Arrangement or mounting of control or safety devices
- G05B 15/02: electric
- H02J 3/14: by switching loads on to, or off from, the networks, e.g. progressively balanced loading
- F24F 11/46: Improving electric energy efficiency or saving
- F24F 11/56: Remote control
- F24F 11/65: for selecting an operating mode
- F24F 2110/00: Control inputs relating to air properties
- F24F 2110/10: Temperature
- F24F 2120/10: Occupancy
- F24F 2120/12: Position of occupants
- F24F 2120/14: Activity of occupants
- F24F 2120/20: Feedback from users
- F24F 2140/50: Load
- F24F 2140/60: Energy consumption
- G05B 2219/2614: HVAC, heating, ventillation, climate control
- H02J 2105/42: Home appliances
- 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
- Y02B 70/3225: Demand response systems, e.g. load shedding, peak shaving
- Y04S 20/222: Demand response systems, e.g. load shedding, peak shaving
- Y04S 20/242: Home appliances
- Y04S 20/244: the home appliances being or involving heating ventilating and air conditioning [HVAC] units
- F24F: AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING (removing dirt or fumes from areas where they are produced B08B15/00; vertical ducts for carrying away waste gases from buildings E04F17/02; tops for chimneys or ventilating shafts, terminals for flues F23L17/02)
- 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
- 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

Methods, systems, and devices are disclosed for managing building power, in one aspect, a method for managing building power includes determining values for power usage of a heating, ventilation, or air conditioning (HVAC) system in one or more zones of a building, the values including a cost of power value, a comfort value, a weighting function between the cost of power value and the comfort value, or a thermal storage value, in which the determining the values is based on a plurality of parameters including a price of power, a time of use, a total power allocation, or random variables including weather and building occupancy factors, and determining a power level for a plurality of states based on the determined values, the plurality of states corresponding to different levels of power to operate the HVAC system in the one or more zones.

## Claims

### Claim 1

A system for managing power in a building, comprising:
hardware sensors distributed in a building to obtain measurements and data from the building; and
one or more computer servers in communication with the hardware sensors and power appliances in the building including appliances for heating, ventilation, or air conditioning (HVAC) in the building,
the one or more computer servers including software modules that receive sensor data from the hardware sensors, receive information on preferences or requests from building occupants, process information in the sensor data received and information from building occupants to dynamically optimize operations of power appliances and use of building resources to generate optimized power state settings of the power appliances in the building, and send control sequences to the power appliances in the building to operate according to the optimized power state settings, building,
the one or more computer servers including information on different pre-set power state settings of the power appliances in the building at different power consumption levels, and are programmed to:
set a zone in the building at a first power state setting selected from the different pre-set power state settings as an initial default power state setting for the zone based on an expected initial need of a temperature control in the zone;
initiate a transition of the zone from the first power state setting to a second, different power state setting when an event is detected to trigger a need to set the zone to the second power state setting; and
after completion of the transition of the zone to the second power state setting, maintain the zone at the second power state setting until a subsequent event is detected to cause a change in the zone, and
wherein the control sequences are determined through stochastic dynamic programming using a radial basis function as response surfaces, and the radial basis function is built using a cost of power value, a comfort value, and a weighting function between the cost of power value and the comfort value.

### Claim 2 (depends on 1)

The system as in claim 1, wherein the one or more computer servers further include one or more software modules to generate suggestions, recommendations, rewards or other incentives to building occupants to encourage the building occupants to take power-friendly actions that improve building power use efficiency.

### Claim 3 (depends on 1)

The system as in claim 1, wherein the one or more computer servers further include one or more software modules that update the power state settings of the power appliances in the building based on currently received sensor data or information from building occupants.

### Claim 4 (depends on 1)

The system as in claim 1, wherein the one or more computer servers further include one or more software modules that process requests from building occupants for meetings in the building to provide a meeting schedule in connection with the optimized power state settings of the power appliances in the building to improve building power use efficiency.

### Claim 5 (depends on 1)

The system as in claim 1,
wherein the first and second power state settings, and the timing of the transition from the first power state setting to the second power state setting are selected to minimize a total power consumption in the zone while meeting comfort level in the zone.

### Claim 6 (depends on 5)

The system as in claim 5, wherein the event for triggering the transition is a timing event.

### Claim 7 (depends on 6)

The system as in claim 6, wherein the event for triggering the transition is a time of a day.

### Claim 8 (depends on 6)

The system as in claim 6, wherein the event for triggering the transition is a time of a day when electricity is cost differently from another time of the day.

### Claim 9 (depends on 5)

The system as in claim 5, wherein the event for triggering the transition is a use event of the zone.

### Claim 10 (depends on 9)

The system as in claim 9, wherein the event for triggering the transition is check in of a guest to a hotel room which is the zone.

### Claim 11

A method for managing building power, comprising:
determining values for power usage of a heating, ventilation, or air conditioning (HVAC) system in one or more zones of a building, the values including a cost of power value, a comfort value, and a weighting function between the cost of power value and the comfort value, wherein the cost of power value is determined based on a total power allocation and random variables, and the comfort value is determined based on the total power allocation, the random variables, a thermal state, and a time period, random variables include weather and building occupancy factors, and the thermal state indicates a vector describing thermal storage at a time period in each zone;
determining a power level for a plurality of states based on the determined values, the plurality of states corresponding to different levels of power to operate the HVAC system in the one or more zones; and
generating, based on the power level, a control sequence to be executed by the HVAC system,
wherein the control sequence includes:
setting a zone in the building at a first power state setting selected from the different pre-set power state settings as an initial default power state setting for the zone based on an expected initial need of a temperature control in the zone;
initiating a transition of the zone from the first power state setting to a second, different power state setting when an event is detected to trigger a need to set the zone to the second power state setting; and
after completion of the transition of the zone to the second power state setting, maintaining the zone at the second power state setting until a subsequent event is detected to cause a change in the zone, and
wherein the control sequence is determined through stochastic dynamic programming using a radial basis function as response surfaces, and the radial basis function is built using the cost of power value, a comfort value, and a weighting function between the cost of power value and the comfort value.

### Claim 12 (depends on 11)

The method of claim 11, further comprising providing a message to an occupant in the one or more zones to modify a setting of the HVAC system to reduce the power level.

### Claim 13 (depends on 11)

The method of claim 11, wherein the parameters further includes sensor data from sensors to detect environmental and/or temporal factors and decision history data from previously determined power levels for the states.

### Claim 14 (depends on 11)

The method of claim 11, wherein the plurality of states include an active state, a nap state, and a hibernate state.

### Claim 15

A building power management system, comprising:
a heating, ventilation, or air conditioning (HVAC) system in one or more zones of a building capable of operating in a plurality of states, wherein the plurality of states use different levels of power to operate the HVAC system; and
a module that determines a power level for the plurality of states of the HVAC system, wherein the module determines the power level based on a cost of power value, a comfort value, a weighting function between the cost of power value and the comfort value, or a thermal storage value,
a module that generates a control sequence to be executed by the HVAC system,
wherein the control sequence includes:
setting a zone in the building at a first power state setting selected from the different pre-set power state settings as an initial default power state setting for the zone based on an expected initial need of a temperature control in the zone;
initiating a transition of the zone from the first power state setting to a second, different power state setting when an event is detected to trigger a need to set the zone to the second power state setting; and
after completion of the transition of the zone to the second power state setting, maintaining the zone at the second power state setting until a subsequent event is detected to cause a change in the zone, and
wherein the control sequence is determined through stochastic dynamic programming using a radial basis function as response surfaces, and the radial basis function is built using the cost of power value, the comfort value, and the weighting function between the cost of power value and the comfort value.

### Claim 16 (depends on 15)

The system of claim 15, further comprising sensors to detect environmental and/or temporal parameters in the one or more zones and actuators to implement an operation of the HVAC system in the one or more zones based on the detected parameters.

### Claim 17 (depends on 15)

The system of claim 15, wherein the plurality of states include an active state, a nap state, and a hibernate state.

### Claim 18

A computer program product comprising a nonvolatile computer-readable storage medium having instructions stored thereon, the instructions comprising:
code for storing a definition of a plurality of states in a heating, ventilation, or air conditioning (HVAC) system in one or more zones of a building, the states corresponding to different levels of power to operate the HVAC system;
code for determining values for power usage, the values including a cost of power value, a comfort value, and a weighting function between the cost of power value and the comfort value, wherein the cost of power value is determined based on a total power allocation and random variables, and the comfort value is determined based on the total power allocation, the random variable, a thermal state, and a time period, and wherein the random variables include weather and building occupancy factors, and the thermal state indicates a vector describing thermal storage at a time period in each zone;
code for determining a power level for the states based on the determined values for power usage; and
code for generating, based on the power level, control sequences to be executed by the HVAC system,
wherein the control sequence includes:
setting a zone in the building at a first power state setting selected from the different pre-set power state settings as an initial default power state setting for the zone based on an expected initial need of a temperature control in the zone;
initiating a transition of the zone from the first power state setting to a second, different power state setting when an event is detected to trigger a need to set the zone to the second power state setting; and
after completion of the transition of the zone to the second power state setting, maintaining the zone at the second power state setting until a subsequent event is detected to cause a change in the zone, and
wherein the control sequences are determined through stochastic dynamic programming using a radial basis function as response surfaces, and the radial basis function is built using the cost of power value, the comfort value, and the weighting function between the cost of power value and the comfort value.

### Claim 19 (depends on 1)

The system of claim 1, wherein the stochastic dynamic programming is represented by a multi stage stochastic control problem that is given by
min
P
⁢
𝔼
w
⁢
{
∑
i
=
1
NT
⁢
[
K
P
⁡
(
P
t
,
w
t
)
+
γ
⁢
⁢
K
c
⁡
(
P
t
,
t
,
X
t
,
w
t
)
+
F
⁡
(
X
NT
)
]
}
where t is time where t=1, . . . , NT, where NT is an integer;
P is a vector of a total building power allocation where Pt, t=1, . . . , NT, in each time period t and zone i;
mine is the minimum over a decision vector P, with components Pt=(Pt1, . . . , PtZ) for each time period t and zone i=1, Z;
Ew is an expected value over random variable w;
Xt=(Xt1, Xt2, . . . , XtZ) is a vector describing thermal storage at time tin building walls and air temperature in each zone i with a total of Z zones; and
F(XNT) is a future value of thermal storage after period NT where the state of the system is XNT at time t=NT.

### Claim 20 (depends on 1)

The system of claim 1, wherein the multi stage stochastic control problem is solved by stochastic dynamic programming with a continuously valued state vector, and wherein the problem is expressed as:
F
t
⁡
(
X
t
)
=
min
P
t
⁢
𝔼
w
⁡
[
K
p
⁡
(
P
t
)
+
γ
⁢
⁢
K
c
⁡
(
P
t
,
t
,
X
t
,
w
t
)
+
F
t
+
1
⁡
(
X
t
+
1
)
]
where Ft(Xt) is a future value of thermal storage after period t;
Kp(Pt) is cost for power;
Kc(Pt, t, Xt, wt) is comfort value; and
γ is a weighting function between cost for power Kp(Pt, wt) and comfort Kc(Pt, t, Xt, wt).