U.S. patent application number 14/297587 was filed with the patent office on 2014-12-11 for methods and systems for optimized hvac operation.
The applicant listed for this patent is Robert C.B. Cooper, Jason Hanna. Invention is credited to Robert C.B. Cooper, Jason Hanna.
Application Number | 20140365017 14/297587 |
Document ID | / |
Family ID | 52006119 |
Filed Date | 2014-12-11 |
United States Patent
Application |
20140365017 |
Kind Code |
A1 |
Hanna; Jason ; et
al. |
December 11, 2014 |
METHODS AND SYSTEMS FOR OPTIMIZED HVAC OPERATION
Abstract
Heating, cooling, and ventilation equipment in a building may be
controlled to improve building performance and/or occupant comfort.
For a building, such as a low-load building, with multiple
sub-systems of an overall HVAC system that can be actuated to
impact indoor environmental conditions, an operational mode used to
control such HVAC equipment may be selected. The selection may be
based on input data from sensors, including indoor and outdoor
environmental conditions, and occupancy level in combination with
multiple models. Data collected over time may be used to form
multiple types of models, including predictive models of building
performance, future indoor conditions, and occupancy levels, and/or
energy usage. The models may be used to select a control strategy.
Based on the selected strategy and user preferences, a set of rules
may be applied to generate control signals that control operation
of HVAC subsystems.
Inventors: |
Hanna; Jason; (Lakeville,
MA) ; Cooper; Robert C.B.; (Wellesley Hills,
MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Hanna; Jason
Cooper; Robert C.B. |
Lakeville
Wellesley Hills |
MA
MA |
US
US |
|
|
Family ID: |
52006119 |
Appl. No.: |
14/297587 |
Filed: |
June 5, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61831274 |
Jun 5, 2013 |
|
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|
Current U.S.
Class: |
700/276 |
Current CPC
Class: |
F24F 11/30 20180101;
F24F 11/47 20180101; F24F 11/46 20180101; F24F 2110/00
20180101 |
Class at
Publication: |
700/276 |
International
Class: |
F24F 11/00 20060101
F24F011/00 |
Claims
1. A system for controlling indoor environmental conditions of a
building, the system comprising: at least one processor configured
to: store at least one user preference; acquire indoor
environmental conditions from sensor data; acquire an occupancy
level; acquire outdoor environmental conditions; predict future
building conditions based on the indoor environmental conditions,
the occupancy level, the at least one user preference, and the
outdoor environmental conditions; select at least one control
output based on the future building conditions; and transmit a
control signal based on the at least one control output to at least
one of heating equipment, cooling equipment, and ventilation
equipment.
2. The system of claim 1, wherein at least one of the acquired
indoor environmental conditions, outdoor environmental conditions,
and occupancy levels comprises historical data values.
3. The system of claim 1, the at least one processor is further
configured to: acquire an energy metric from at least one energy
meter; detect at least one of heating, cooling, and ventilation
equipment requires service based on the energy metric; and transmit
a message signal to a user interface.
4. The system of claim 3, wherein the user interface is operated by
a service provider.
5. The system of claim 1, wherein the occupancy level is acquired
from a location signal transmitted by a portable electronic
device.
6. The system of claim 5, wherein the occupancy level is based on
the location signal indicating within a proximity of the at least
one processor.
7. The system of claim 1, wherein: the processor is further
configured to execute at least one predictive model; and the at
least one predictive model is an occupancy predictive model and
determines an occupancy level for a future time point, the
occupancy level indicating a likelihood of presence or activity of
occupants in the building.
8. The system of claim 1, wherein: the at least one processor is
further configured to execute at least one predictive model and
acquire energy consumption data values; and the at least one
predictive model is an energy consumption model and determines
energy consumption levels for at least one of the heating
equipment, cooling equipment, and ventilation equipment.
9. The system of claim 8, wherein the at least one processor is
further configured to transmit a notification when a current energy
consumption data value differs from a predicted energy consumption
value by more than a threshold amount, the notification
recommending maintenance on at least one of the heating equipment,
the cooling equipment, and the ventilation equipment.
10. The system of claim 1, wherein the at least one processor is
further configured to: simulate at least one scenario based on a
building performance model and control inputs for at least one of
the heating equipment, the cooling equipment, and the ventilation
equipment select a scenario based on selection criteria; determine
a target state based on the selected scenario and the occupancy
level; and select at least one control output based on the target
state.
11. The system of claim 10, wherein the building performance model
is based on historical data having at least one of indoor
environmental conditions, outdoor environmental conditions,
occupancy levels, and energy consumption values for previous time
points.
12. The system of claim 11, wherein the building performance model
determines a rate of change of indoor conditions in response to at
least one of outdoor conditions and energy consumption.
13. The system of claim 1, wherein the indoor environmental
conditions are at least one of temperature values, humidity values,
and indoor air quality values.
14. The system of claim 1, wherein the at least one processor is
further configured to: transmit a notification to a portable
electronic device, the notification having a recommendation to a
user for improving building performance.
15. The system of claim 1, wherein the at least one control signal
is to increase ventilation by controlling a fan based on a high
occupancy level.
16. A method of operating equipment to control indoor environmental
conditions of a building, the method comprising: acquiring at least
one current indoor state from at least one indoor sensor;
predicting a future occupancy level based on occupancy data;
setting, selectively based on the predicted future occupancy level,
a target state based on user preferences; setting, selectively
based on the predicted future occupancy level, the target state
based on at least one of a duration of time to reach user
preferences and a minimization of at least one energy metric; and
controlling at least one of heating equipment, cooling equipment,
and ventilation equipment based on the target state and the at
least one current indoor state.
17. The method of claim 16, the method further comprising:
acquiring energy usage data from at least one energy meter;
monitoring performance information of at least one of heating
equipment, cooling equipment, and ventilation equipment; transmit
energy usage data and performance information to at least one
processor;
18. The method of claim 17, the method further comprising:
determining energy efficiency data based on the energy usage data
and the performance information; and sending a user alert signal
when energy efficiency data is below a threshold value.
19. The method of claim 16, wherein the occupancy data is derived
from a signal transmitted by a portable electronic device.
20. The method of claim 16, wherein: the at least one sensor is a
plurality of sensors; and a plurality of sensors are located within
at least one zone of the building or at least one sensor is in more
than one zone.
21. The method of claim 16, wherein the target state is at least
one of a temperature value and humidity value.
22. The method of claim 21, wherein the target state is temporarily
set to a different value based on a user defined range of values
and a time period when the target state is allowed to be
changed.
23. The method of claim 16, wherein controlling the cooling
equipment includes setting a target state to pre-cool or pre-heat
the building to a certain temperature value.
24. At least one non-transitory, tangible computer readable storage
medium having computer-executable instructions, that when executed
by a processor, perform a method of operating equipment, the method
comprising: acquiring at least one current indoor state from at
least one indoor sensor; predicting a future occupancy level based
on measured occupancy data; receiving input indicating a user
preference; setting a target state based on the user preference by:
when the user preference is a first preference, selecting the
target state such that the user preference can be reached within a
duration of time; and when the user preference is a second
preference, selecting the target state based on at least one energy
metric; and controlling at least one of heating, cooling, and
ventilation equipment based on the target state and the at least
one current indoor state.
25. The at least one non-transitory, tangible computer readable
storage medium of claim 24, wherein controlling at least one of
heating, cooling, and ventilation equipment comprises: generating
control signals to a ventilation subsystem and generating control
signals to a heating or cooling subsystem.
26. A system for controlling indoor environmental conditions of a
building by generating control signals to a plurality of subsystems
of an HVAC system, the system comprising: at least one processor
configured to: receive user input indicating a user preferred
environmental condition; acquire sensor data; for each of a
plurality of scenarios for controlling the plurality of subsystems:
simulate control of the HVAC system in accordance with the strategy
and the acquired sensor data; compare a simulated result of control
according to the scenario to a criteria relating to building
operation; and based on the comparison and a comparison made for at
least one other scenario of the plurality of scenarios, determine
whether to apply the control scenario; and generate to control
values to the subsystems of the HVAC system in accordance with a
control scenario determined to be applied.
27. The system of claim 26, wherein the at least one processor is
further configured to: detect at least one of heating, cooling, and
ventilation equipment requires service based on comparing a
simulated result of control according to the scenario to a criteria
relating to building operation; and transmit a message signal to a
user interface recommending maintenance on at least one subsystem
of the HVAC system.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. provisional
application Ser. No. 61/831,274, titled "Methods and Systems for
Optimized HVAC Operation," filed Jun. 5, 2013, which is hereby
incorporated by reference in its entirety.
BACKGROUND
[0002] Heating, ventilation, and air condition (HVAC) equipment are
used to maintain indoor environmental conditions in buildings. The
indoor environmental conditions may be set based on user
preferences in order to maintain adequate comfort and indoor air
quality. Temperature set points and data from associated
temperature sensors may be used to control of operation of the HVAC
equipment.
[0003] Design of a building and associated HVAC equipment may vary
widely, influencing overall building performance and energy
consumption. Operation modes of different HVAC equipment may vary
in energy consumption.
SUMMARY
[0004] Aspects of the present application are directed to methods
and systems of operating HVAC equipment, which include heating
equipment, cooling equipment, and ventilation equipment.
[0005] According to an aspect of the present application, a system
for controlling indoor environmental conditions of a building is
provided. The system comprises at least one processor and at least
one of heating equipment, cooling equipment, and ventilation
equipment. The at least one processor is configured to store at
least one user preference, acquire indoor environmental conditions
from sensor data, acquire an occupancy level, acquire outdoor
environmental conditions, predict future building conditions based
on the indoor environmental conditions, the occupancy level, the at
least one user preference, and the outdoor environmental
conditions, select at least one control output based on the future
building conditions, transmit a control signal based on the at
least one control output to at least one of heating equipment,
cooling equipment, and ventilation equipment.
[0006] According to an aspect of the present application, a method
of operating equipment to control indoor environmental conditions
of a building is provided. The method comprises acquiring at least
one current indoor state from at least one indoor sensor, and
predicting a future occupancy level based on occupancy data. The
method further comprises setting, selectively based on the
predicted future occupancy level, a target state based on user
preferences and setting, selectively based on the predicted future
occupancy level, the target state based on at least one of a
duration of time to reach user preferences and a minimization of at
least one energy metric. The method further comprises controlling
at least one of heating equipment, cooling equipment, and
ventilation equipment based on the target state and the at least
one current indoor state.
[0007] According to an aspect of the present application, at least
one non-transitory, tangible computer readable storage medium
having computer-executable instructions, that when executed by a
processor, perform a method of operating equipment is provided. The
method comprises acquiring at least one current indoor state from
at least one indoor sensor, predicting a future occupancy level
based on measured occupancy data, and receiving input indicating a
user preference. The method further comprises setting a target
state based on the user preference by when the user preference is a
first preference, selecting the target state such that the user
preference can be reached within a duration of time, and when the
user preference is a first preference, selecting the target state
based on at least one energy metric. The method further comprises
controlling at least one of heating, cooling, and ventilation
equipment based on the target state and the at least one current
indoor state.
[0008] According to an aspect of the present application, a system
for controlling indoor environmental conditions of a building by
generating control signals to a plurality of subsystems of an HVAC
system is provided. The system comprises at least one processor
configured to receive user input indicating a user preferred
environmental condition and acquire sensor data. The at least one
processor is further configured to, for each of a plurality of
scenarios for controlling the plurality of subsystems, simulate
control of the HVAC system in accordance with the strategy and the
acquired sensor data, compare a simulated result of control
according to the scenario to a criteria relating to building
operation, based on the comparison and a comparison made for at
least one other scenario of the plurality of scenarios, determine
whether to apply the control scenario. The at least one processor
is further configured to generate to control values to the
subsystems of the HVAC system in accordance with a control scenario
determined to be applied.
BRIEF DESCRIPTION OF DRAWINGS
[0009] The accompanying drawings are not intended to be drawn to
scale. In the drawings, each identical or nearly identical
component that is illustrated in various figures is represented by
a like numeral. For purposes of clarity, not every component may be
labeled in every drawing. In the drawings:
[0010] FIG. 1 is a schematic of components in a system for
optimization of HVAC equipment in a building;
[0011] FIG. 2 is a block diagram illustrating an exemplary HVAC
optimization system;
[0012] FIG. 3 is a block diagram illustrating inputs and outputs of
a building performance model;
[0013] FIG. 4 is a block diagram illustrating inputs and outputs of
an occupancy prediction model;
[0014] FIG. 5 is a flowchart illustrating modelling scenarios for
operating HVAC equipment to select a target indoor state; and
[0015] FIG. 6 is a flowchart illustrating an exemplary HVAC
optimization process.
DETAILED DESCRIPTION
[0016] The inventors have recognized and appreciated that the
operation of heating, ventilation, and air conditioning (HVAC)
systems may be improved by predicting future conditions, including
environmental state and occupancy level, to asses and select the
operation modes of the HVAC equipment. Such an approach may improve
comfort level for a user in a building having HVAC equipment
operated using such techniques. Additionally, such HVAC operation
techniques may improve energy usage, such as by reducing costs,
increasing efficiency, and/or reducing greenhouse gas emissions.
Accordingly, the inventors have developed a system, which may
include a computing device that receives information from indoor
sensors and generates control signals for the HVAC equipment. From
an electronic device, a user may access information on the
computing and provide control signals through an application. The
application may contain a graphical user interface for
visualization of the information on a display and/or for a user to
input control settings. The electronic device may be a portable
electronic device or a personal computer. A display may also be
built-in and/or incorporated into one or more components of an HVAC
system to visualize such an application graphical user
interface.
[0017] The techniques of the present invention include methods and
systems for controlling heating, ventilation, and air conditioning
(HVAC) systems in buildings to provide improvements in energy
usage. These methods or systems may be implemented with programs
and/or algorithms for automatic optimization. In some embodiments,
a user may be able to monitor and/or control operation of HVAC
equipment, from a smartphone, portable electronic device or other
suitable user interface.
[0018] In some embodiments, control may be implemented using a
suite of predictive models. These models may be obtained in any
suitable way, including being built by the system by logging sensor
readings over time. The logs may be processed to develop
correlations or patterns that may be applied to relate a state
measured at a future time, to relate measured operating conditions
at a present time to future conditions. Alternatively or
additionally, the models may predict operating characteristics,
such as energy usage or future environmental conditions.
[0019] These models, once constructed, may be used to determine
target set points, which may vary based on measured or modeled
conditions. Such set points may include a temperature at which HVAC
equipment aims to keep an internal or indoor air temperature of a
building. Set points may also include a humidity at which HVAC
equipment aims to keep an internal or indoor air humidity of a
building. In buildings in which there are multiple subsystems of an
HVAC system that could be controlled, the subsystem or subsystems
that are controlled may be selected by modeling results of multiple
control scenarios. A modeled scenario providing a highest degree of
a modeled result, such as comfort or energy usage, may be selected
and control may be implemented according to the selected
scenario.
[0020] Moreover, selection of the scenario may be based on a user
input, such as a first preference that specifies comfort or a
second preference that specifies energy efficiency. For example,
when control is to be provided to implement comfort, a scenario in
which the temperature within a building is computed to reach a user
specified preferred temperature faster than other scenarios may be
selected. Conversely, when the user's control preference is energy
efficiency, the scenario that is predicted to maintain the indoor
environmental conditions within some threshold level of deviation
of a set point and uses less energy than other scenarios may be
selected.
[0021] The design of the building may influence the operation of
heating, cooling, and ventilation systems to maintain a comfortable
environment for a user. Some buildings have extensive insulation
and low air leakage. In these buildings, the heating and cooling
load may be low and mechanical ventilation may be primarily used to
circulate air. Such buildings may be "low-load" buildings and may
include net zero and energy positive buildings by the addition of
on-site energy generation. A smaller heating and cooling system,
such as a minisplit heat pump, may be used in such low-load
buildings. Additionally, for buildings with reduced air leakage it
may be suitable to use a variety of ventilation systems to bring in
adequate fresh air and to move air within the building to provide
even heating and humidity conditions. Such ventilation systems may
include active ventilation, heat recovery ventilation (HRV), energy
recovery ventilation (ERV), central-fan-integrated supply
ventilation, and exhaust only ventilation. Control of indoor
environmental conditions in the building may be implemented by
controlling some or all of these components.
[0022] Further, the inventors appreciate that operation of a
ventilation system may be a dominant energy consumer in an HVAC
system and may be the mechanical system with the most significant
influence on indoor conditions. As an example, a fan in a central
HVAC system may consume up to 800 W while ERV and HRV power
consumption may vary between 35 to 240 W. It is important to
efficiently operate the ventilation system in a building to
generally reduce energy consumption and maintain a healthy indoor
environment. Ventilation devices have been operated continuously or
manually controlled and do not typically have their controls
integrated with heating and cooling controls. Embodiments as
described herein may generate control signals to both to achieve
control of indoor operating conditions by coordinated control of
both a ventilation subsystem and a subsystem for heating or
cooling.
[0023] The presence of occupants within a building and their
behavior may also influence the appropriate control of HVAC
equipment. Occupants may produce heat and humidity through
activities such as cooking, showering, doing laundry, or
exercising. The load on a building may be affected by an occupant
opening or closing windows, doors, and shades. In some buildings,
occupant behavior may have a dominant effect on the building. For
an example, a low-load building may retain heat effectively and
heat-generating occupant behavior may increase the indoor
temperature.
[0024] Conventional building operation may typically operate in one
of three operating modes: heating, cooling, or "off," which is
neither actively heating nor cooling. However, some buildings may
operate in a more complex set of modes, including some low-load
buildings. In order to identify and operate in these modes,
analytical algorithms may be used to process sensor inputs,
including their historical values and produce output control
signals. In some embodiments, occupant action may be elicited
through electronic action via a user device.
[0025] A schematic of components in a system for optimization of
HVAC equipment in a building is illustrated by system 100 in FIG.
1. A user 104 may input user preferences for environmental
conditions inside the building. Such user preferences may be used
to control the HVAC equipment 114 to maintain a user preferred
environment that is monitored by indoor sensors 102A and 102B.
[0026] Indoor sensors 102A and 102B are located inside a building.
Such indoor sensors may be placed in at least one room and may
measure indoor conditions. Indoor conditions that may be obtained
from signals from the sensors may include environmental conditions
such as temperature, relative humidity (RH), carbon dioxide, carbon
monoxide, volatile organic compounds, and other indoor air quality
(IAQ) measures. The indoor sensors 102A and 102B may also measure
motion and/or occupancy via passive infrared, ultrasonic or other
suitable occupant detection mechanisms. These indoor sensors may
integrate multiple functions in a single module, such as by
combining temperature, relative humidity, and passive infrared
occupancy. Indoor sensors 102A and 102B may be battery-powered,
powered by energy harvesting, or powered by AC or DC power. In some
embodiments, "sensors" may acquire information other than by direct
measurement. For example, a wireless receiver may serve as an
occupancy sensor by receiving signals indicative of presence or
motion of a wireless transmitter, such as might occur when an
occupant is carrying a smartphone.
[0027] The location and placement of the indoor sensors 102A and
102B may be selected in any suitable way. A building may have
multiple zones with environmental conditions for each zone. The
zones may be locations within a building where certain aspects of
the indoor environmental conditions are similar. As an example, one
area of a building, such as a room or floor, may have a higher
temperature than another area. Additionally, zones may be locations
within a building where the indoor environmental conditions are
predominantly influenced by heating, cooling, and/or ventilation
equipment. Such zones may be called heating, cooling, and
ventilation zones. In some buildings, heating, cooling, and
ventilation zones may be different regions of the building and a
zone of one type may not coincide with a zone of another type. As
an example, a heating zone may occupy a region of a building that
does not correspond to a ventilation zone or cooling zone. In
another example, a radiant floor heating zone may overlap with part
of a forced air heating zone, where the forced air heating zone may
be larger than the radiant floor heating zone. Individual sensors
may be placed within each zone, such as separate rooms or floors of
a building. Although only two indoor sensors are shown in FIG. 1,
any suitable number of indoor sensors may be used. In some
embodiments, one or more sensors may be placed within a zone. When
more than one sensor is located within a zone, additional data
related to the indoor conditions of the zone may be obtained than
if only one sensor were in the zone. Using more than one sensor in
a zone may provide additional information than when one sensor is
used per a zone and such additional information for a zone may be
used to improve building performance and/or HVAC operation. An
outdoor sensor 118 may be located outside a building to obtain the
environmental conditions outside the building. Such outdoor
environmental conditions measured by an outdoor sensor may include
humidity, temperature, wind speed, wind direction, and insolation.
Alternatively or additionally, data from a weather service may be
used to obtain outdoor conditions such as temperature, humidity,
wind speed, and cloud coverage. Additionally, data from the weather
service may be used to provide forecast information about predicted
future weather conditions.
[0028] Signals from the indoor sensors 102A and 102B and/or outdoor
sensor 118 may be transmitted to a computer processing device, such
as base station 108. The computer processing device may be a
computer, programmed to receive data from multiple sources and to
perform control techniques as described herein, Alternatively or
additionally, the processing device may be implemented with one or
more semiconductor chips, integrated assembled to form a computer
processing device.
[0029] Such a processing device may be connected to the Internet,
one or more home area networks (HANs), or other local area
networks. Signals may be received and transmitted from base station
108 via wired or wireless communications with other components in
the system 100. The base station 108 may process the received
signals from the sensors and send control signals to a control
module 116 for HVAC equipment 114. Base station 118 may communicate
with remote processing services via the Internet or private
network. The base station may contain software that monitors data
from a variety of sources, including the sensors, executes a suite
of analysis techniques and predictive models, and transmits control
signals to the HVAC equipment. Additionally, the base station may
provide alerts to occupants and/or service providers related to the
performance of the HVAC equipment.
[0030] Control module 116 may be a module or control board that
interfaces between the base station 116 with HVAC equipment 114.
Such HVAC equipment may include components such as a furnace,
boiler, zone controller, damper, zone-valve, mixing valve, air
source heat pump, ground source heat pump, hydronic heater, forced
air heater, energy recovery ventilation (ERV), heat recovery
ventilation (HRV), electrical resistance heating, central air
conditioning, minisplit air conditioner, portable air conditioner,
small diameter/high velocity (SDHV) heating/cooling system,
humidification, dehumidification, air filtration, air cleaning, and
any other suitable heating, cooling, and/or ventilation equipment.
An energy supply 112 for HVAC equipment may be any suitable source
to power the HVAC equipment such as a battery, energy harvesting
source, AC power supply, DC power supply, or combustible fuels,
such as oil, natural gas, propane, and biomass.
[0031] Energy meter 110 may read the energy consumption and
production of energy supply 112. The energy meter 110 may include
Advanced Meter Reading (AMR) and Advanced Meter Infrastructure
(AMI) electric and/or gas meters. Additional energy meters may be
used for oil tanks, propane cylinders, solar photo-voltaic
production, wind energy production, solar hot water production,
geothermal energy production, ground or water source heat pump
energy production, electric vehicle charging and supply.
Additionally or alternatively, a utility service or third party
energy data service may provide energy consumption and production
data. Such data may be accessed via a computer network, such as the
Internet, through wired or wireless communications.
[0032] User 104 may input user preferences and/or control settings
for operation of the HVAC equipment in the building shown in FIG. 1
through any suitable interface, which may be on an electronic
device 106, separate from base station 108. A suitable device may
include one or more hardware components, such as a processor, a
display, memory and/or a transceiver. Such an electronic device may
include an application that controls and receives notifications
from the base station 108. Any suitable electronic device with
hardware components may be used to receive information from base
station 108 or remote processing services. Such electronic devices
may include personal desktop and laptop computers. Additionally or
alternatively, electronic device 106 may be a portable electronic
device, such as a smartphone or tablet. Although only one
electronic device is shown in FIG. 1, multiple devices may be used
to access information from the base station or remote processing
service. In some embodiments, one or more HVAC components may
contain suitable interfaces to input user preferences and/or
control settings for operation of the HVAC equipment in the
building. Such interfaces may include displays on one or more
components of the HVAC system, including the base station, sensors,
and/or control modules. In such embodiments, a display may be
built-in one or more components of an HVAC system to visualize data
and/or information.
[0033] The electronic device may receive notifications or alerts to
the user about the system operation and performance from another
component in the system. As an example, the user may receive
information about equipment faults and/or maintenance needs via the
electronic device. Such maintenance notifications may be
transmitted when a current energy consumption value differs from
predicted energy consumption. A range of values may be used to
compare current energy consumption and predicted energy
consumption. A single value, a threshold value, a range of values,
and or a percentage may be used to indicate a significant
difference between current and predicted energy consumption. In
some embodiments, a notification may be transmitted by a processor
in a device when a current energy consumption data value differs
from a predicted energy consumption value by more than a threshold
amount. For an example, when the current energy consumption of a
building is greater or less than a predicted energy consumption
value, a notification may be sent to a user and/or service provider
recommending maintenance on one or more HVAC components. A range of
acceptable values for an energy consumption level to differ from a
predicted energy consumption value may be used to indicate when
maintenance is advised and/or required. Additionally, the user may
receive notifications about ways to improve building performance
and equipment operation, such as by reducing energy usage and
enabling control to more stably retain environmental conditions at
a set point. These notifications may include advice to the user,
such as opening or closing windows. Notifications may be received
on the electronic device through any suitable notification
communication method such as text message, email, popup message, or
voicemail.
[0034] Communication methods among the device components in the
system described in FIG. 1 may include any machine to machine
communication technologies, and may include wireless protocols such
as IEEE 802.5.4, ZigBee, ZWave, BlueTooth, or WiFI, and wired
protocols such as Ethernet, powerline communications (such as UPB
or Home Plug), or serial communications (such as RS232 or
RS485).
[0035] Although user 104 is shown as an occupant in FIG. 1, user
104 can also be an installer, an HVAC professional, and/or service
provider. Moreover, user 104 may be outside the premises at the
time device 106 is used to receive information or provide control
inputs. In some embodiments, a service provider may use electronic
device 106 to monitor building performance and associated HVAC
equipment. If the performance of a component of HVAC equipment 114
decreases, an alert or notification may be sent to the service
provider indicating that maintenance may be required for the HVAC
equipment. Additionally, a service provider may collect data from
buildings in order to track performance for future analysis. Such
analysis may include predicting future performance and maintenance
needs. Using such techniques, a service provider may be able to
monitor the HVAC equipment of multiple buildings and/or users. As
an example, some HVAC equipment may fault more readily under a high
load demand, such as an air conditioning unit cooling a building on
a hot day. A service provider may track the performance of multiple
customers' HVAC equipment to identify HVAC equipment that is
susceptible to faults and/or errors under specific weather
conditions.
[0036] Communication between components of an HVAC system,
including data and information signal transfer between components
is illustrated by system 200 in FIG. 2. Indoor sensors 202, outdoor
sensors 204, energy meters 206, and/or weather services 208
communicate with base station 210 to provide data signal inputs.
Data inputs from indoor sensors may indicate indoor climate
conditions, such as temperature, humidity, and indoor air quality.
Indoor occupancy information may also be obtained from indoor
sensors, such as passive infrared sensors, as well as through IAQ
monitors, mobile device presence, and energy consumption patterns.
The number of occupants and the activity level of the occupants may
be inferred by using one or more of these data sources.
Additionally or alternatively, the number of occupants and occupant
activity level may be inferred through sensor fusion. As an
example, occupancy information may be inferred by using data from
passive infrared sensors as a leading indicator of ventilation
needs as compared to relative humidity and carbon dioxide which are
trailing or supplemental indicators. Base station 210 may have
access to information from weather services 208 to receive current
external weather conditions as well as local weather forecast
conditions.
[0037] Information from weather service 208 may be obtained locally
or remotely through a dedicated or shared service providing current
weather conditions such as temperature, humidity, wind speed, or
cloud coverage. The weather service may also provide forecast
information, such as projected temperature and humidity. Such
information may be obtained over a computer network or in any other
suitable way.
[0038] A user may provide inputs into the operation of HVAC
equipment by a user device 216 that communicates with base station
210. Such a user device may include an application 218 programmed
to interpret signals received from the base station and an
associated application graphical user interface represented on
display 220 of user device 216. Such an application may allow a
user to enter in their preferences for environmental conditions,
such as temperature and humidity, inside a building. The
application 218 may also allow a user to input commands, such as a
program for temperature settings throughout the course of a
duration of time, such as an hour, day, month, and/or year. The
application may be an HTML 5 or similar "rich-client" that is
downloadable on demand to an electronic device. The application may
be an iOS or Android application that is downloadable to a user.
Additionally or alternatively, the application may be a web page or
web program with some or all of the programming logic either in a
cloud service or on a base station. Data from either on the cloud
service or base station may be accessed through such a web page or
web program by a user.
[0039] Additionally, the user preferences may include a user
designated default settings as well as commands to enable override
of those default settings for any parameters of system operation,
including communication with the user. Notifications related to
building performance may be provided to a user through the
application such as through pop-up messages, text messages, and
email messages. Additional notifications may provide
recommendations with how to improve energy usage and carbon dioxide
emissions, which may be delivered to the user through the same or
different channels. In some embodiments, the application 218 may
have a graphical user interface on display 220 that may allow a
user to compare performance of multiple buildings and/or HVAC
equipment.
[0040] Data signals from energy meters 236 indicating energy
consumption or production may also be provided to base station 210.
Energy meters may monitor whole building energy production and/or
consumption. As shown in FIG. 2, an energy meter may be associated
with an energy supply or source. In some embodiments, energy meters
may be associated with one or more components of HVAC equipment.
Although not shown in FIG. 2, an energy meter may monitor energy
consumption of heating equipment 226, cooling equipment 228, and/or
ventilation equipment. Regardless of the component an energy meter
is connected to, information about energy usage and/or production
may be transferred to base station 210.
[0041] Data from indoor sensors, outdoor sensors, weather service
208, energy meters 236, and user device 216 may be received by the
base station. The base station may contain an analysis and
prediction utility 212 with software programs for analyzing and
interpreting the data inputs, such as to develop a measure of
building performance. In addition, the base station may contain
software programs for forming predictive models, such as an
predicting future occupancy of the building and or predicting
indoor environmental conditions. Results from analysis and
prediction utility 212 and may be used to select the controls to
operate the HVAC equipment. Selection rules may be stored in rule
utility 214 located within the base station.
[0042] A collection of computing resources, such as cloud
processing service 222, may be accessed via the Internet or private
network and logically connected to the base station 210 or user
interface device 216. Such a cloud processing network may allow
additional processing capabilities to base station and provide
updates on programs, such as for the analysis and predictions.
Additionally, cloud processing service 222 may allow the user to
access data and information stored on base station 210 via user
device 216 as well as provide commands and user preferences to
operation of the base station. The base station may use user input
when selecting the controls to use to operate the HVAC
equipment.
[0043] When the specific controls are selected, control output
signals may be transmitted from base station 210 and received by
HVAC control module 224. Such control signals are then interpreted
by the HVAC control module 224 to manage HVAC equipment, including
heating equipment 226, cooling equipment 228, and ventilation
equipment 230. Such control instructions may include a target
minimum temperature, target maximum temperature, target humidity
value, heating set point, cooling set point, dehumidification set
point, and/or humidification set point. The control signals may
also include instructions to select a particular stage of heating
or cooling for operating the heating or cooling equipment. Control
signals may be discrete and/or continuous. Such discrete signals
may include instructions to select for a particular discrete mode,
including an "on," "off," stage 1, and/or stage 2. Continuous
signals may include instructions for selecting a value to operate
in a continuously variable mode, such as a percentage value or a
proportional value, for an example 10% firing rate of a burner, 30%
pump speed, or 50% fan speed). Additionally, control signals may
include instructions to select an operation mode for specific HVAC
equipment, such as fan speed for cooling, heating, and/or
ventilation. Such instructions may also include selecting a bypass
mode for ventilation equipment 230. Each of the subsystems of the
HVAC system may have its own set points. However, these set points
may be coordinated to efficiently control indoor environmental
conditions.
[0044] An electrical load controller may interface between one or
more HVAC equipment components and energy supply 234. Electrical
load controller 232 as shown in FIG. 2 interfaces between heating
equipment 226 and energy supply 234, however an electrical load
controller may also interface energy supply 234 with cooling
equipment 228 and/or ventilation equipment 230. In some
embodiments, there may be more than one electrical load controller.
For example, there may be an electrical load controller for each
HVAC equipment component. In other embodiments, an electrical load
controller may not be used in such as system. An electrical load
controller may be used to interface an HVAC component with an
energy supply when the HVAC component lacks operation modes and/or
control settings. Such HVAC equipment may be controlled by altering
the energy source through an electrical load controller. Base
station 210 may transmit control signals to one or more electrical
load controllers. Such signals may include instructions to
disconnect an HVAC component from an energy supply.
[0045] The system may include programming or software algorithms to
determine building performance. Such software programs may execute
on the base station, such as on an analysis and prediction unit, or
on any other suitable computing device.
[0046] FIG. 3 is a functional block diagram of a process 300,
showing steps to obtain inputs into a building performance model
310 and output results from such a modeling process.
[0047] The input steps may consist of measuring indoor conditions
indicated by block 302. The indoor conditions may include
environmental conditions, such as indoor temperature (IT) and
indoor humidity (IH). Another input into a building performance
model may be the ventilation mode (V) in use by ventilation
equipment and block 304 indicates the step of identifying the
current ventilation mode. Such a ventilation mode may be no
ventilation, ventilation with heat recovery, and ventilation with
bypass. In some embodiments, a logistic value may be associated
with each possible ventilation mode available for ventilation
equipment. Such logistic values may be designated model input
values, including numerical values, for each possible ventilation
mode. Outdoor environmental conditions may also be acquired as
indicated by block 306. Such outdoor conditions may include outdoor
temperature (OT), outdoor humidity (OH), wind speed (W), and cloud
cover or insolation (S). The outdoor conditions may be acquired
using one or more outdoor sensors and/or from accessing weather
services to acquire the current outdoor conditions near the
building. Another input into a building performance model may be
energy consumption (E) of the building and possibly one or more
components of the HVAC equipment. Such energy consumption may be
determined as indicated by block 308, such as by acquiring data
signals from energy meters.
[0048] In some embodiments, a building performance model may be
formed based on analyzing previously acquired data for indoor
conditions, outdoor conditions, occupancy, energy consumption, HVAC
equipment state, and/or control settings for HVAC equipment.
Relationships may be formed between recorded data values for indoor
conditions, outdoor conditions, and/or energy consumption. When
current data values are obtained, such building performance model
may examine the historical data to find one or more times under
similar indoor conditions in order to predict indoor conditions. As
an example, the rate of change of indoor temperature and/or
humidity in response to particular combinations of outdoor
temperature, outdoor humidity, wind speed, cloud cover, and/or
building energy consumption may be recorded and used to analyze
current indoor conditions. In this example, the determined rate of
change of indoor temperature and/or indoor humidity may be used
with measured current indoor conditions from indoor sensors to
predict future indoor conditions.
[0049] In some embodiments, a multivariate, autoregressive model
may be used for building performance model 310. Such a model uses
previous values to represent output values. In such embodiments,
indoor temperature (IT) and indoor humidity (IH) at time t depend
on the values of some or all of the variables IT, IH, outdoor
temperature (OT), outdoor humidity (OH), wind speed (W), cloud
cover (S) and energy consumption (E) at times t-1, t-2, . . . t-n
for some n, for each of the possible ventilation modes (V).
[0050] In other embodiments, a multivariate regression may be used
to model building performance. Such a model may determine a formula
to describe how some variables respond simultaneously to other
variables. In such embodiments, IT and IH may be predicted based on
time binned values of some or all of variables OT, OH, W, S, E, and
V. Such time binned values may be obtained by summing or averaging
a series of values within a set of ranges for one or more
variables.
[0051] A building performance model may also be formed based on
building science principles, and may be input by a user or obtained
in any other suitable way. Such a model may estimate the rate of
temperature change based on principles known for conductive heat
loss. In some embodiments, the equation for conductive heat loss
may be q=U*A*(IT-OT), where q (MJh) is heat loss, U (MJh/(m.sup.2
.degree. C.)) is a heat transfer coefficient, A (m.sup.2) is area,
IT (.degree. C.) is indoor temperature, and OT (.degree. C.) is
outdoor temperature. Additionally, infiltration of heat may be
determined from known formulas and may be combined with conductive
heat loss calculations. In some embodiments, an estimate for heat
infiltration may be determined from the equation a
q.sub.infiltration=0.34*Q*(IT-OT), where Q (m.sup.3/h) is the
infiltration air flow. In such a model, heat transfer coefficient
and/or infiltration air flow may be determined based on past
building performance, such as through multiple regression analysis.
In some embodiments, different values for heat transfer coefficient
and/or infiltration air flow may be determined for different
mechanical ventilation modes. As an example, three different values
for U and Q may be found for no ventilation, ventilation with heat
recovery, and/or ventilation with bypass. Moreover, a model may be
developed for an entire building or portions of a building, such as
individual rooms.
[0052] Additionally, the system may include models that may be used
to generate information used to compute control inputs to HVAC
equipment or to determine appropriate set points. For example, the
system may form a model of energy consumption required by the
different heating, cooling and ventilation equipment in a building.
In some embodiments, energy and/or fuel meters may measure energy
consumption during different time periods in the heating and/or
cooling process. Such time periods may be indicated by stages of
heating or cooling, such as a first, second, or third stage. In
other embodiments, energy consumption input values may be manually
entered by a user and/or an installer and used in models when
energy consumption is unknown and/or lacks sufficient data. In such
embodiments, control values for HVAC equipment may be obtained by
identifying the circumstances when use of specific energy sources
will lower or minimize energy usage, greenhouse gas emissions or
other operating conditions. By identifying when certain energy
sources are to be used, control of the HVAC equipment may be
selected to reduce energy usage, energy costs, and/or greenhouse
gas emissions. As an example, energy costs may be reduced by
decreasing the use of expensive energy sources, such as electrical
resistance heat, fuel oil, or propane. In some embodiments, the
relative efficiency of certain HVAC equipment based on different
outdoor environmental conditions may be measured from data acquired
by base station and/or from user input. For example, the efficiency
of an air source heat pump may be determined for different outdoor
temperatures by the computer device monitoring energy usage by that
component as a function of outdoor temperature and recording that
information.
[0053] The system may include an occupancy prediction model to
predict an occupancy level of a whole building and/or a space
within a building. The occupancy level may be based on the number
of occupants and/or the activity or behavior of the occupants. A
predicted future value of an occupancy level may be used to select
a target indoor state or conditions, such as based on whether the
building is occupied or which portions are occupied. The model may
also be used in generating control values for subsystems of the
HVAC system. As an example, computed control values, which might
otherwise increase output of heat from an HVAC subsystem, may be
scaled back when occupancy is high.
[0054] Process 400 as illustrated in FIG. 4 indicates
representative input steps into an occupancy prediction model and
steps that follow. An occupancy prediction model may be developed
by acquiring occupancy information over time. Occupancy information
may be measured, as indicated by block 402, from occupancy sensors
and/or indoor environmental sensors when occupants are present. The
time and date may be acquired by block 404 to provide context and
organize the occupancy information. As an example, such occupancy
information data may be organized by day of week and/or time of
day. Relationships between occupancy level and time and/or day may
be formed by organizing the data. Such relationships may indicate a
higher occupancy level for specific days of the week and/or certain
times. These relationships may form an occupancy prediction model
406 that may be used to predict future occupancy level as indicated
by block 408. A future occupancy level may be used to select a
target indoor state. When the occupancy level is high, such as a
90% likelihood of an occupant being present, user preferences are
used to select the target indoor state, as indicated by block 410.
When the occupancy level is moderate, such as a 50-90% likelihood
of a present occupant, then scenarios may be modeled to select the
target indoor state, as indicated by block 412 and further
described in reference to FIG. 5.
[0055] A target state may be used to determine the control signals
sent to HVAC equipment by using a set of rules for selecting
control values. The rules may define actions for operating HVAC
equipment based on a target state and/or a future predicted indoor
condition. Among a set of rules, a subset of rules may be selected
based on the target indoor state which may include both a target
indoor temperature value and a target indoor humidity value. The
selected control rules may indicate specific actions for
controlling the indoor environmental conditions. Such indicated
actions determined by control rules may be used to select control
signals to be executed by HVAC equipment, including heating,
cooling, and/or ventilation equipment. Additionally, the control
rules may determine whether notifications are sent to a user and/or
service provider based on conditions.
[0056] Different operation modes for HVAC equipment may be modelled
to predict potential future indoor conditions and energy metrics,
such as energy costs, energy usage, or greenhouse gas emissions.
The multiple scenarios may be modelled for a duration of time to
determine if the resulting indoor conditions are compatible with
the user preferences. Such compatible indoor conditions may include
the ability, under certain operation modes, to reach user
preferences for indoor conditions within a certain period of time.
When there is a moderate likelihood of occupancy, a target indoor
state may be selected from which the building reaches indoor
conditions consistent with user preferences within a period of time
after occupancy is detected. Such a technique may reduce energy use
or cost while providing user comfort. For example, a building may
be pre-cooled during a period when the outdoor temperature is
cooler than forecasted when the building is expected to be occupied
or pre-heated when the outdoor temperature is warmer than
forecasted. These pre-heated or pre-cooled states may be achieved
with little energy usage, but may enable the building to easily
reach user preferences when occupancy occurs. Additionally or
alternatively, reaching a certain threshold for an energy metric
when modelling a certain scenario may be used to select a target
indoor state.
[0057] Selecting a target indoor temperature based on modelling
different scenarios is shown by process 500 in FIG. 5. A possible
scenario for operating HVAC equipment is selected as indicated by
block 502. Each scenario may use a specified combination of
operating modes for heating, cooling, and ventilation equipment.
Possible ventilation modes may include no ventilation, ventilation
with heat recovery, and ventilation with bypass. Different heating
modes may include no heating, first stage, second stage, or third
stage of heating. Similarly, different cooling modes may include no
cooling, or first stage, second stage, or third stage of cooling.
Example combinations of operation modes may include, no ventilation
and no heating or cooling, ventilation with heat recovery and no
heating or cooling, ventilation with bypass and no heating or
cooling, ventilation with heat recovery and different possible
stages of heating or cooling. Techniques used for applying a
building performance model may be used to model such scenarios to
predict future outcomes of combinations of operation modes.
[0058] In some embodiments, a system may be pre-programmed with a
set of possible scenarios and one or more scenarios may be selected
to model. The scenarios to model may be selected based on the
current indoor temperature and a target temperature from user
preferences. If the current indoor temperature is above a user
defined target temperature, then cooling scenarios may be modelled.
If the current indoor temperature is below a user defined target
temperature, then heating scenarios may be modelled. Some
embodiments may select an order of scenarios to model based on
results from energy consumption analysis. Historical data may
determine that specific operating modes for HVAC equipment may
reduce an energy metric, such as energy usage. An order for
modelling the different scenarios may be selected based on such
energy consumption analysis. For example, scenarios with operation
modes that have historically shown reduced energy consumption may
be modelled first. If a target indoor state is selected, then
additional scenarios may not be modelled until a new target indoor
state needs to be selected.
[0059] A selected scenario may be modelled for a duration of time
using current environmental conditions as an input as indicated by
block 504. The time period may be selected by a user or service
provider or defined as a default setting. Though, it should be
appreciated that the duration of modeling may be determined
dynamically, such as by stopping modeling when the scenario is
determined to be worse than a previously selected scenario. In
other embodiments, past occupancy data may be used to determine the
duration of time for modelling the selected scenario.
[0060] Once the scenario has been modelled, one or more
requirements may be used to select whether the operating conditions
for that scenario are used to select a target indoor state. In some
embodiments, a selection requirement may include whether user
preferences may be reached as indicated by block 506. In some
instances, the modelled scenario may result in control values that
are predicted to reach user defined comfort settings for indoor
conditions. In other instances, the modelled scenario may result in
control values that are predicted to reach indoor conditions from
which the HVAC system may be controlled to reach user preferences
within a certain duration of time. For example, the system may be
operated to establish a temperature from which a preferred
temperature can be reached within 15 minutes of a detected
condition, such as a high level of occupancy.
[0061] In some embodiments, a selection requirement may include
whether the modelled scenario reaches a certain energy metric
value. Such energy metrics may include energy consumption, energy
cost, and/or greenhouse gas emissions. A threshold value may also
be used to determine whether an energy metric value is reached.
Such a threshold value may be determined by user input and/or from
analysis of energy consumption data. As an example, different
stages of heating may have different energy consumption rates and
operational mode may be selected to reduce energy consumption by
selecting a stage of heating that has a reduced energy consumption
rate than using multiple heating stages. Optimized performance of
the HVAC equipment may occur when a single stage of heating occurs
for a longer period of time instead of operating at a second or
third stage for a shorter period of time.
[0062] When a scenario modelled for a duration of time reaches one
or more requirements, a target indoor state may be selected based
on the scenario as indicated by block 510. The target indoor state
may include user preferences. The selected target indoor state may
indicate pre-cooling or pre-heating of the building to easily reach
user comfort preferences when the building is occupied. If none of
the scenarios produce a satisfactory result based on the
requirements, a different duration of time may be used to model one
or more scenarios by block 504.
[0063] After a target indoor state is selected, rules may be
selected based on the target indoor state. Such a target indoor
state may include both a target indoor temperature value and a
target indoor humidity value. Control rules may indicate a specific
action based on one or more conditions. Such indicated actions
determined by control rules may be used to select control signals
to be executed by HVAC equipment, including heating, cooling,
and/or ventilation equipment. Additionally, the control rules may
determine whether notifications are sent to a user and/or service
provider based on conditions. Such notifications may include advice
about window and shade operation. Shades may be advised to be open
or closed based on cloud cover. If shades are automatic, then they
may be automatically operated. Windows may be advised to be open or
closed based on a comparison between indoor and outdoor
temperature. Notifications concerning advice to users may be
filtered to minimize the number of changes in advice given during a
single day.
[0064] The following are exemplary operating settings for
controlling indoor environmental conditions that may be determined
using the techniques of the present invention. In these examples,
the building has heating, cooling, and ventilation equipment. The
ventilation equipment may circulate the heat throughout the spaces,
such as by using an ERV or an HRV.
[0065] On a cold day, they system may choose an optimal strategy by
analyzing energy consumption of the heating equipment and
ventilation equipment over time. When the building contains zones,
heating of the building may be obtained by operating the control of
each zone region. One option may be to run only the heating units
on the lowest floor and increase the fan speed of the ventilation
equipment to circulate the heat. Another option is to run all
heating units at appropriate levels to heat the spaces they occupy.
When the building does not include zones, the central heating may
be run along with sufficient ventilation to maintain adequate
indoor air quality. If the building includes a forced air system,
the central fan is run if the heat is not circulated evenly
throughout the indoor spaces. If it is an overcast day or night, an
alert may be sent to a user or an occupant of the building to
advise to close the shades. If it is a sunny day, an alert may be
sent a user or an occupant to advice to open the shades.
[0066] On a moderately hot day, the operating mode selected may be
to turn on a ventilation device to ensure adequate indoor air
quality. The system may also advise an occupant to leave all
windows closed an lower shades for particular locations on the
building, such as on the south side of a building located in a
northern climate.
[0067] When there is a cold overcast day or night after a hot day,
the target maximum temperature or cooling set point may be
temporarily changed to a higher value in order to reduce operation
of cooling equipment. The temporary higher set point may be defined
by a user preference, such as by a delta in degrees of Celsius or
Fahrenheit above the normally defined cooling set point. A user
preference may also include a duration of time that the normally
defined cooling set point may be exceeded during a period of time,
such as a day. In this example scenario, forecast information may
be used to trigger such an operating mode. The system may receive
forecast information predicting when the outdoor air temperature
and/or humidity will be lower than indoor conditions. Such a
temporary higher set point may be selected also when occupant
presence and/or behavior is predicted to be high, such as use of
appliances.
[0068] On a very hot and/or humid day, the operating mode selected
may be to run cooling equipment, such as a heat pump in cooling
mode or a central air conditioning unit, and use ventilation
equipment to ensure adequate indoor air quality. Past building
performance under similar conditions may be analyzed and, based on
the analysis, the operating conditions may be selected. In this
example for a hot day, past building performance may indicate that
precooling the building by a modest amount may improve performance.
Notifications may be sent to an occupant to advise closing the
windows and/or to close shades.
[0069] When a high point source of internal humidity is detected,
such as from cooking or showering, the operating mode selected may
be to increase ventilation to bring in outside air and to
redistribute the humidity. Increasing ventilation may be achieved
by increasing the fan speed of the ventilation equipment. If the
outdoor humidity is high, a dehumidification mode for an HVAC
equipment, such as a heat pump or an AC unit, may be selected.
[0070] A high occupant level may occur from a large number of
occupants and/or an occupant induced heat load, such as from
exercise, cooking, and or electronics use. When the occupant level
is high, the operating mode for the HVAC equipment may be to
increase the ventilation and adjust the heating set point and/or
cooling set point based on an anticipated higher cooling load
and/or higher heating load. The ventilation may be increased by
running ventilation equipment at a higher fan speed.
[0071] When the occupant level is low or if no occupants are
detected, the operating mode selected may adjust the fan of the
ventilation device to run at a slower speed or turn off the
ventilation device. In some embodiments, when a building is
detected as unoccupied, similar rules may be applied except that a
target indoor temperature and/or humidity range are used. In some
instances, a target indoor state may be ignored. If the building is
identified to be leaky or poorly insulated based on building
performance analysis, set points for indoor humidity and
temperature may be modified.
[0072] The techniques of the present invention may be combined for
an optimization process for operating HVAC equipment. An exemplary
process 600 is shown in FIG. 6. In such a process, user settings
may be collected by block 602. Such user settings may be collected
by user input into an electronic device. Forecast weather
information may be collected from accessing a weather services as
shown by block 604. The forecast weather information may be used to
predict future weather conditions for input into analysis and
prediction models. Current weather conditions are also collected by
block 606. Current outdoor conditions may be obtained from outdoor
sensors and/or weather service information. Indoor sensor data may
be collected by block 608. Such indoor sensor data may include
indoor environmental conditions and/or occupancy information.
Energy meter data may be collected by block 610. Energy meters may
measure energy consumption or production for the whole building
and/or for individual components of HVAC equipment.
[0073] Once data and information has been collected, an update in
the prediction of building conditions may occur by block 612. A
model of building performance may be used to update the predicted
building conditions as described above. In some embodiments, an
occupancy prediction model may be used to in forming the an update
of building conditions.
[0074] Predicted building conditions may then be used to select
rules for HVAC management by block 614. In some embodiments, the
predicted building conditions may inform a target indoor state
based on building performance and/or occupancy predictions. Any
suitable set of rules may be used to select controls for operating
components of HVAC equipment and for providing advice to users.
Additional exemplary rules, with terminology definitions, that may
be used to select control signals for HVAC equipment and/or
notifications using techniques described in the present invention
are presented in Tables 1-3. Analysis, prediction, and rule
selection programs and computation may occur in a base station
configured to transmit control signals.
[0075] The selected rules may then be used to determine output
control signals to HVAC equipment. Output ventilation control
signals may be sent to ventilation equipment by block 616. Output
heating, cooling, or off control signals may be sent to heating
and/or cooling equipment by block 618. The control signals may be
discrete and/or continuous signals to instruct HVAC equipment to
operate at particular settings as discussed previously. In some
embodiments, a control module may be used to receive control
signals and interface with one or more components of HVAC
equipment. Additionally, the rules selected may include actions to
notify a user with advice on how to optimize performance by block
620. Such notifications may be sent to a user electronic
device.
[0076] Process 600 may repeat continuously, at specific times, or
at certain time interval. When such a process repeats may be
defined by a user, service provider, and/or a default setting.
[0077] Having thus described several aspects of at least one
embodiment of this invention, it is to be appreciated that various
alterations, modifications, and improvements will readily occur to
those skilled in the art.
[0078] Such alterations, modifications, and improvements are
intended to be part of this disclosure, and are intended to be
within the spirit and scope of the invention. Further, though
advantages of the present invention are indicated, it should be
appreciated that not every embodiment of the invention will include
every described advantage. Some embodiments may not implement any
features described as advantageous herein and in some instances.
Accordingly, the foregoing description and drawings are by way of
example only.
[0079] Various aspects of the present invention may be used alone,
in combination, or in a variety of arrangements not specifically
discussed in the embodiments described in the foregoing and is
therefore not limited in its application to the details and
arrangement of components set forth in the foregoing description or
illustrated in the drawings. For example, aspects described in one
embodiment may be combined in any manner with aspects described in
other embodiments.
[0080] Also, the invention may be embodied as a method, of which an
example has been provided. The acts performed as part of the method
may be ordered in any suitable way. Accordingly, embodiments may be
constructed in which acts are performed in an order different than
illustrated, which may include performing some acts simultaneously,
even though shown as sequential acts in illustrative
embodiments.
[0081] Use of ordinal terms such as "first," "second," "third,"
etc., in the claims to modify a claim element does not by itself
connote any priority, precedence, or order of one claim element
over another or the temporal order in which acts of a method are
performed, but are used merely as labels to distinguish one claim
element having a certain name from another element having a same
name (but for use of the ordinal term) to distinguish the claim
elements.
[0082] Also, the phraseology and terminology used herein is for the
purpose of description and should not be regarded as limiting. The
use of "including," "comprising," or "having," "containing,"
"involving," and variations thereof herein, is meant to encompass
the items listed thereafter and equivalents thereof as well as
additional items.
TABLE-US-00001 TABLE 1 Key for HVAC Management Rules Temperature
T.sub.indoor "Temperature indoors": Represents the set of all
indoor temperature sensors. T.sub.outdoor "Temperature outdoors":
The outdoor temperature as measured by a sensor or from a weather
service. avg(T.sub.indoor) Average of all indoor temperature
sensors range(T.sub.indoor) Range of all indoor temperature
sensors, i.e. max(T.sub.indoor)-min(T.sub.indoor) TT.sub.high
Target indoor temperature (high) also called the cooling setpoint.
The control algorithm endeavors to ensure that avg(T.sub.indoor)
< TT.sub.high TT.sub.low Target indoor temperature (low) also
called the heating setpoint. Goal is to ensure that
avg(T.sub.indoor) > TT.sub.low TT.sub.range Target indoor
temperature range. The maximum desired value for
range(T.sub.indoor) Relative Humidity Rh.sub.indoor "Humidity
indoors": Represents the set of all indoor humidity sensors.
Rh.sub.outdoor "Humidity outdoors": The outdoor humidity as
measured by a sensor or from a weather service. avg(Rh.sub.indoor)
Average of all indoor humidity sensors range(Rh.sub.indoor) Range
of all indoor humidity sensors, i.e.
max(Rh.sub.indoor)-Min(Rh.sub.indoor) RhT.sub.high Target indoor
humidity (high). Goal is to ensure that avg(Rh.sub.indoor) <
RhT.sub.high RhT.sub.low Target indoor humidity (low). Goal is to
ensure that avg(Rh.sub.indoor) > RhT.sub.low RhT.sub.range
Target indoor humidity range. The maximum desired value for
range(Rh.sub.indoor) Heating/Cooling Control States Heating
Equipment is in heating mode and managed to an average temperature
avg(T.sub.indoor) above TT.sub.low with control such as a
traditional PID control loop. Cooling Equipment is in cooling mode
and managed to an average temperature avg(T.sub.indoor) below
TT.sub.high with control such as a traditional PID control loop.
Cool/Dehumid Equipment is in dehumidification mode and managed to
an averagehumidity, avg(Rh.sub.indoor) below RhT.sub.high with
control such as a traditional PID control loop. Off The equipment
is off, except for integrated ventilation, if any. Ventilation
volume (e.g. fan speed or runtimes) V.sub.off No ventilation. Used
only when the building is unoccupied. V.sub.min Minimum volume.
Used whenever the building is occupied in order to meet IAQ and
code requirements on fresh air. V.sub.med Medium volume. Used when
"free cooling"or "free heating" is available when the outdoor
temperature and/or humidity are favorable. V.sub.high Maximum
volume. Only used on user demand and when high humidity is detected
in any location in the building. Ventilation Bypass ERV/HRV Bypass
This feature allows fresh air to be supplied without exchange of
heat or humidity with the exhaust air. Not all ERV/HRVs provide
this feature. Other ventilation types (central integrated fan and
exhaust only ventilation) are effectively always in bypass mode
since they have no heat or energy recovery feature.
TABLE-US-00002 TABLE 2 Heating/Cooling/Ventilation Control and
Window Opening Advice (T.sub.indoor < TT.sub.low &
T.sub.outdoor .ltoreq. T.sub.indoor) .fwdarw. Too cold inside,
colder outside (HRV & Rh.sub.indoor < RhT.sub.low &
Rh.sub.outdoor > Rh.sub.indoor) .fwdarw. Also too dry inside: [
Heat, V.sub.med, Bypass/Window=close] Bring in more-humid air (HRV
& Rh.sub.indoor > RhT.sub.high & Rh.sub.outdoor <
Rh.sub.indoor) .fwdarw. Also too humid inside: [ Heat, V.sub.med,
Bypass/Window=close] Bring in dryer air Otherwise .fwdarw. [ Heat,
V.sub.min, Bypass/Window=close] Heat, minimal ventilation
(T.sub.indoor < TT.sub.low & T.sub.outdoor >
T.sub.indoor) .fwdarw. Too cold inside, warmer outside
(Rh.sub.indoor < RhT.sub.low & Rh.sub.outdoor .gtoreq.
Rh.sub.indoor) .fwdarw. Also too dry inside, more humid outside
[Off, V.sub.med, Bypass/Window = Open] Free heating and
humidification (Rh.sub.indoor > RhT.sub.high &
Rh.sub.outdoor < Rh.sub.indoor) .fwdarw. Also too humid inside,
dryer outside [Off, V.sub.med, Bypass/Window = Open] Free heating
and dehumidification Otherwise .fwdarw. Outdoor humidity not
favorable [ Heat, V.sub.min, Bypass/Window=close] Use heat, minimal
ventilation (T.sub.indoor > TT.sub.high & T.sub.outdoor
.gtoreq. T.sub.indoor) .fwdarw. Too hot inside, hotter outside (HRV
& Rh.sub.indoor < RhT.sub.low & Rh.sub.outdoor >
Rh.sub.indoor) .fwdarw. Also too dry inside: [ Cool, V.sub.med,
Bypass/Window=close] Bring in more-humid air (HRV &
Rh.sub.indoor > RhT.sub.high & Rh.sub.outdoor <
Rh.sub.indoor) .fwdarw. Also too humid inside: [ Cool, V.sub.med,
Bypass/Window=close] Bring in dryer air Otherwise .fwdarw. [ Cool,
V.sub.min, Bypass/Window=close] Cool, minimal ventilation
(T.sub.indoor > TT.sub.high & T.sub.outdoor <
T.sub.indoor) .fwdarw. Too hot inside, cooler outside
(Rh.sub.indoor < RhT.sub.low & Rh.sub.outdoor .gtoreq.
Rh.sub.indoor) .fwdarw. Also too dry inside, more humid outside
[Off, V.sub.min, Bypass/Window = Open] Free cooling and
humidification (Rh.sub.indoor > RhT.sub.high &
Rh.sub.outdoor < Rh.sub.indoor) .fwdarw. Also too humid inside,
dryer outside [Off, V.sub.min, Bypass/Window = Open] Free cooling
and dehumidification Otherwise .fwdarw. Outdoor humidity not
favorable [ Cool, V.sub.min, Bypass/Window=close] Use heat
(TT.sub.low .ltoreq. T.sub.indoor .ltoreq. TT.sub.high) &
(RhT.sub.low .ltoreq. Rh.sub.indoor .ltoreq. RhT.sub.high) .fwdarw.
Comfortable temperature and humidity inside (T.sub.indoor ~=
T.sub.outdoor) & (Rh.sub.indoor ~= Rh.sub.outdoor) .fwdarw.
Similar conditions outside [Off, V.sub.min, Bypass/Window = Open]
Can open windows Otherwise .fwdarw. Different conditions outside
[Off, V.sub.min, Bypass/Window = Close] Use ERV/HRV without bypass
In all modes when an ERV or HRV is present: (range(T.sub.indoor)
> TT.sub.range | range(Rh.sub.indoor) > RhT.sub.range)
.fwdarw. Poor temperature or humidity distribution [Ventilation
Rate=V.sub.med] Circulate air around building. Losses to outside
are minimal with an HRV or ERV.
TABLE-US-00003 TABLE 3 Shade Advice/Control In all modes, If
(T.sub.indoor < TT.sub.low & CloudCover <= 20% &
daytime) .fwdarw. Open shades If (T.sub.indoor >= TT.sub.high |
CloudCover > 20% | nighttime) .fwdarw. Close shades
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