U.S. patent application number 12/852690 was filed with the patent office on 2011-02-24 for context-aware smart home energy manager.
This patent application is currently assigned to HONEYWELL INTERNATIONAL INC.. Invention is credited to Saad J. Bedros, Thirumaran Ekambaram, Tom Markham, Nasir Mohammed, Tom Plocher, Pradeep Shetty.
Application Number | 20110046805 12/852690 |
Document ID | / |
Family ID | 43605996 |
Filed Date | 2011-02-24 |
United States Patent
Application |
20110046805 |
Kind Code |
A1 |
Bedros; Saad J. ; et
al. |
February 24, 2011 |
CONTEXT-AWARE SMART HOME ENERGY MANAGER
Abstract
A context-aware smart home energy management (CASHEM) system and
method is disclosed. CASHEM dynamically schedules household energy
use to reduce energy consumption by identifying contextual
information within said household, selecting a comfort of service
preference, wherein said comfort of service preference is based on
different said contextual information, and extracting an appliance
use schedule for maximum energy savings based on said contextual
information in light of said comfort of service preferences, by
executing a program instruction in a data processing apparatus.
CASHEM correlates said contextual information with energy
consumption levels to dynamically schedule said appliance based on
an energy-saving condition and a user's comfort. Comfort of service
preferences are gathered by CASHEM by monitoring occupant activity
levels and use of said appliance. CASHEM can also recommend
potential energy savings for a user to modify comfort of service
preferences.
Inventors: |
Bedros; Saad J.; (West St.
Paul, MN) ; Markham; Tom; (Fridley, MN) ;
Plocher; Tom; (Hugo, MN) ; Shetty; Pradeep;
(Bangalore, IN) ; Ekambaram; Thirumaran;
(Bangalore, IN) ; Mohammed; Nasir; (Woodbury,
MN) |
Correspondence
Address: |
HONEYWELL/ORTIZ & LOPEZ;PATENT SERVICES
101 Columbia Road
Morristown
NJ
07962-2245
US
|
Assignee: |
HONEYWELL INTERNATIONAL
INC.
Morristown
NJ
|
Family ID: |
43605996 |
Appl. No.: |
12/852690 |
Filed: |
August 9, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61234947 |
Aug 18, 2009 |
|
|
|
Current U.S.
Class: |
700/291 |
Current CPC
Class: |
H04L 12/2809 20130101;
H04L 12/282 20130101; G05B 2219/2642 20130101; H04L 12/2829
20130101; G05B 15/02 20130101; H04L 2012/285 20130101; G05B
2219/2639 20130101; G05B 19/0421 20130101 |
Class at
Publication: |
700/291 |
International
Class: |
G06F 1/32 20060101
G06F001/32 |
Claims
1. A method for dynamically scheduling household energy use that
reduces wasteful energy consumption, reduces peak electricity
demand, integrates renewable energy and storage technology, and
changes a user's behavior to manage and consume less energy, said
method comprising: identifying contextual information within said
household, by executing a program instruction in a data processing
apparatus; identifying a user preference for comfort and service
within said household, by executing a program that allows said user
to indicate said user preference; selecting a comfort of service
preference, wherein said comfort of service preference is based on
different said contextual information and said user preference, by
executing a program instruction in a data processing apparatus; and
extracting an appliance use schedule for maximum energy savings
based on said contextual information, said user preference, and
said comfort of service preference, by executing a program
instruction in a data processing apparatus.
2. The method of claim 1 further comprising extracting a schedule
for using renewable energy sources and storage batteries within
said household, wherein said extracted schedule reflects said
contextual information about demand response, by executing a
program instruction in a data processing apparatus.
3. The method of claim 1 further comprising: monitoring ongoing
appliance use to infer compliance with said appliance use schedule,
by executing a program instruction in a data processing apparatus;
and dynamically modifying said appliance use schedule according to
monitored contextual information and said user's evolving energy
use behavior, by executing a program instruction in a data
processing apparatus.
4. The method of claim 1 further comprising correlating said
contextual information with energy consumption levels to
dynamically schedule said appliance based on an energy-saving
condition and a user's comfort, by executing a program instruction
in a data processing apparatus.
5. The method of claim 1 further comprising coordinating an energy
manager to perform at least one of the following operations:
gathering contextual information related to environmental
conditions; gathering energy supply type conditions; gathering cost
conditions; selecting a comfort of service preference; and
configuring an appliance use schedule.
6. The method of claim 5 wherein said energy manager comprises a
graphical user interface and data processing apparatus, wherein
said graphical user interface is configured for at least one of the
following operations: gathering said contextual information related
to user activity and a daily schedule; gathering information about
user comfort and service preferences; displaying energy use
feedback to said user; displaying energy saving opportunities in
compliance with said user's evolving behavior; recommending use of
renewable energy source and stored energy within said household;
and displaying incentive or motivational information to said user
based on observed energy use behavior and adaptive to said user's
energy use pattern.
7. The method of claim 1 further comprising monitoring said
household's occupant activity levels and use of said appliance for
configuring said appliance use schedule, by executing a program
instruction in a data processing apparatus.
8. The method of claim 1 wherein said contextual information either
entered by said user or via a networked device includes at least
one of the following: current weather information; forecast weather
information; security system information; utility information;
renewable energy-use information; energy storage information;
energy supply type; and utility signals including at least one of
the following types of signals: demand response (DR),
real-time-pricing (RTP) information, time-of-use (TOU) tariff.
9. The method of claim 1 further comprising operating said
appliance according to said appliance use schedule at a recommended
level equal to a comfort of service preference for maximum energy
savings, by executing a program instruction in a data processing
apparatus.
10. A system for dynamically scheduling household energy use that
reduces wasteful energy consumption, reduces peak electricity
demand, integrates renewable energy and storage technology, and
changes a user's behavior to manage and consume less energy, said
system comprising: a data-processing apparatus; a module executed
by said data-processing apparatus, said module and said
data-processing apparatus being operable in combination with one
another to: identifying contextual information within said
household, by executing a program instruction in a data processing
apparatus; identifying a user preference for comfort and service
within said household, by executing a program that allows said user
to indicate said user preference; selecting a comfort of service
preference, wherein said comfort of service preference is based on
different said contextual information and said user preference, by
executing a program instruction in a data processing apparatus; and
extracting an appliance use schedule for maximum energy savings
based on said contextual information, said user preference, and
said comfort of service preference, by executing a program
instruction in a data processing apparatus.
11. The system of claim 10 wherein said module and said
data-processing apparatus are further operable in combination with
one another to extract a schedule for using renewable energy
sources and storage batteries in said household, wherein said
extracted schedule reflects said contextual information about
demand response, by executing a program instruction in a data
processing apparatus.
12. The system of claim 10 wherein said module and said
data-processing apparatus are further operable in combination with
one another to: monitor ongoing appliance use to infer compliance
with said appliance use schedule, by executing a program
instruction in a data processing apparatus; and dynamically modify
said appliance use schedule according to monitored contextual
information and said user's evolving energy use behavior, by
executing a program instruction in a data processing apparatus.
13. The system of claim 10 wherein said module and said
data-processing apparatus are further operable in combination with
one another to correlate said contextual information with energy
consumption levels to dynamically schedule said appliance based on
an energy-saving condition and a user's comfort, by executing a
program instruction in a data processing apparatus.
14. The system of claim 10 wherein said module and said
data-processing apparatus are further operable in combination with
one another to coordinate an energy manager to perform at least one
of the following operations: gather contextual information related
to environmental conditions; gather energy supply type conditions;
gather cost conditions; select a comfort of service preference; and
configure an appliance use schedule.
15. The system of claim 14 wherein said energy manager comprises a
graphical user interface and data processing apparatus, wherein
said module, said data-processing apparatus, and said graphical
user interface are further operable in combination with one another
to: collect said contextual information related to user activity
and a daily schedule; collect information about user comfort and
service preferences; display energy use feedback to said user;
display energy saving opportunities in compliance with said user's
evolving behavior; recommend use of renewable energy source and
stored energy within said household; and display incentive or
motivational information to said user based on observed energy use
behavior and adaptive to said user's energy use pattern.
16. The system of claim 12 wherein said module and said
data-processing apparatus are further operable in combination with
one another to monitor said household's occupant activity levels
and use of said appliance to configure said appliance use schedule,
by executing a program instruction in a data processing
apparatus.
17. The system of claim 12 wherein said contextual information
either entered by said user or via a networked device includes at
least one of the following: current weather information; forecast
weather information; security system information; utility
information; renewable energy-use information; energy storage
information; energy supply type; and utility signals including at
least one of the following types of signals: demand response (DR),
real-time-pricing (RTP) information, time-of-use (TOU) tariff.
18. The system of claim 12 wherein said module and said
data-processing apparatus are further operable in combination with
one another to operate said appliance according to said appliance
use schedule at a recommended level equal to a comfort of service
preference for maximum energy savings, by executing a program
instruction in a data processing apparatus.
19. An apparatus comprising one or more processor readable storage
devices having processor readable code on said processor readable
storage devices, said processor readable code for programming one
or more processor to perform a method for dynamically scheduling
household energy use that reduces wasteful energy consumption,
reduces peak electricity demand, integrates renewable energy and
storage technology, and changes homeowner behavior to manage and
consume less energy, comprising: identifying contextual information
within said household, by executing a program instruction in a data
processing apparatus; identifying a user preference for comfort and
service within said household, by executing a program that allows
said user to indicate said user preference; selecting a comfort of
service preference, wherein said comfort of service preference is
based on different said contextual information and said user
preference, by executing a program instruction in a data processing
apparatus; and extracting an appliance use schedule for maximum
energy savings based on said contextual information, said user
preference, and said comfort of service preference, by executing a
program instruction in a data processing apparatus.
20. The apparatus of claim 19 further comprising: a sensor to
detect contextual information; a network; and an energy manager
coupled to said network comprising said sensor for detecting
context information, a display, said data processing apparatus, and
a set of instructions for dynamically scheduling household energy
use that reduces wasteful energy consumption, reduces peak
electricity demand, integrates renewable energy and storage
technology, and changes homeowner behavior to manage and consume
less energy.
Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] This patent application claims the priority and benefit of
U.S. Provisional Patent Application 61/234,947 filed Aug. 18, 2009
entitled "Context-Aware Smart Home Energy Manager" that is herein
incorporated by reference.
TECHNICAL FIELD
[0002] Embodiments are generally related to energy management.
Embodiments are additionally related to energy management of
household consumer appliances. Embodiments are further related to a
control interface for energy management of household consumer
appliances.
BACKGROUND OF THE INVENTION
[0003] Net zero energy (NZE) homes are structures that combine
state-of-the-art, energy-efficient construction techniques and
equipment, with renewable energy systems to return as much energy
as it uses on an annual basis. To achieve NZE use in a home, a
comprehensive energy reduction strategy is required, including the
use of efficient appliances, renewable energy resources, and
efficient home energy management capable of adapting to the
occupant's lifestyle. Energy management concepts and technologies
reduce wasteful energy consumption, reduce peak electricity demand,
integrate renewable energy and storage technology, and change the
occupant's behavior for the occupant to learn how to manage and
consume less energy.
[0004] A home typically uses unmanaged appliances with minimal
planning and inefficient scheduling. It is impossible to formulate
a home energy plan without a holistic view of home occupancy, usage
patterns, demand peaks, or weather effects on home energy usage.
Further, without dynamic energy pricing, current NZE strategies
fall short as technology focuses on user awareness of energy
consumption, basic demand response (DR), and fixed programmable
schedules with minimal ability to control and schedule energy
consumption. Current DR solutions for energy usage range from
simple pager-based solutions to sophisticated appliances, with
little homeowner participation or input. Homeowners may try to
reduce household energy use by turning off the air conditioning
during certain parts of the day or heating the pool to lower
temperatures. This approach, however, does not take into account
reducing the energy use of all the appliances and consumer
electronics, as a collective system, within a home. Other
apparatuses and techniques exist to facilitate the efficient
operation of the energy consuming devices, including programmable
electronic thermostats and various timers for lighting, water
heaters, and pool heaters. But these apparatuses, do not
communicate with each other through a centralized system to
efficiently manage energy use within a home. Such solutions simply
shift energy consumption and do not help achieve NZE goals.
[0005] A comprehensive home energy use management system is needed
to coordinate efficient and smart appliances, other
energy-consuming devices, and renewable energy resources. This home
energy use management system also needs to recognize and adjust
energy use to varying occupancy levels and conditions within the
home. By accommodating to the lifestyle of the occupants, and
properly scheduling use of appliances, a large percentage of energy
can be saved. Therefore, a need exists for a context-aware smart
home energy manager (CASHEM) to coordinate and conserve energy use
in the home, as will be discussed in greater detail herein.
BRIEF SUMMARY
[0006] The following summary is provided to facilitate an
understanding of some of the innovative features unique to the
disclosed embodiment and is not intended to be a full description.
A full appreciation of the various aspects of the embodiments
disclosed herein can be gained by taking into consideration the
entire specification, claims, drawings, and abstract as a
whole.
[0007] It is, therefore one aspect of the disclosed embodiment to
provide for an improved energy management system and method.
[0008] It is another aspect of the disclosed embodiment to provide
for an improved energy management system and method for household
consumer appliances.
[0009] It is a further aspect of the disclosed embodiment to
provide for a control interface for energy management of household
consumer appliances.
[0010] The aforementioned aspects and other objectives and
advantages can now be achieved as described herein. A context-aware
smart home energy management (CASHEM) system and method is
disclosed. "Context-awareness" describes the conditions of energy
consumption in the house. CASHEM identifies contextual information
within said household, selects a comfort of service preference
based on previously expressed homeowner preferences, and generates
an appliance use schedule for maximum energy savings based on said
contextual information in light of said comfort of service
preferences. It does this by executing a program instruction in a
data processing apparatus. Once running, CASHEM continues to
monitor actual appliance use and identifies additional
opportunities for energy savings that match up with the homeowner's
evolving energy use behavior. Part and parcel to this is the use
various incentives to motivate energy use behavior change in the
desired direction. An energy manager display coordinates and
gathers said user preferences to formulate a dynamic energy-savings
plan for a household.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] The accompanying figures, in which like reference numerals
refer to identical or functionally-similar elements throughout the
separate views and which are incorporated in and form a part of the
specification, further illustrate the invention and, together with
the detailed description of the invention, serve to explain the
principles of the disclosed embodiments.
[0012] FIG. 1 illustrates a schematic view of a software system
including an operating system, application software, and a user
interface, in accordance with the disclosed embodiments;
[0013] FIG. 2 illustrates a schematic view of a data-processing
system, in accordance with the disclosed embodiments;
[0014] FIG. 3 illustrates a graphical representation of a
computer-implemented context-aware smart home energy management
system (CASHEM), in accordance with the disclosed embodiments;
[0015] FIG. 4 illustrates a flow chart illustrating the logical
operation steps of CASHEM's operation, in accordance with the
disclosed embodiments;
[0016] FIGS. 5A-5B illustrates graphical representations model of
energy savings using CASHEM's dynamic scheduling based on various
activities, in accordance with the disclosed embodiments;
[0017] FIGS. 5C-5D illustrates graphical representations model of
energy savings when using CASHEM's dynamic scheduling techniques to
provide a user with a recommended energy savings usage plan, in
accordance with the disclosed embodiments; and
[0018] FIGS. 6A-6E illustrate a graphical user interface (GUI) for
interaction with the context-aware smart home energy management
system (CASHEM), in accordance with the disclosed embodiments.
DETAILED DESCRIPTION
[0019] The particular values and configurations discussed in these
non-limiting examples can be varied and are cited merely to
illustrate at least one embodiment and are not intended to limit
the scope thereof.
[0020] FIGS. 1-2 are provided as exemplary diagrams of
data-processing environments in which embodiments of the present
invention may be implemented. It should be appreciated that FIGS.
1-2 are only exemplary and are not intended to assert or imply any
limitation with regard to the environments in which aspects of
embodiments of the disclosed embodiments may be implemented. Many
modifications to the depicted environments may be made without
departing from the spirit and scope of the disclosed
embodiments.
[0021] FIG. 1 illustrates a computer software system 100 for
directing the operation of the data-processing system 200 depicted
in FIG. 2. Software application 104, stored in main memory 202 and
on mass storage 207 (as described in FIG. 2), generally includes a
kernel or operating system 101 and a shell or interface 103. One or
more application programs, such as software application 104, may be
"loaded" (i.e., transferred from mass storage 207 into the main
memory 202) for execution by the data-processing system 200. The
data-processing system 200 receives user commands and data through
user interface 103; these inputs may then be acted upon by the
data-processing system 100 in accordance with instructions from
operating system module 101 and/or software application 104.
[0022] As illustrated in FIG. 2, the disclosed embodiments may be
implemented in the context of a data-processing system 200 that
includes, for example, a central processor 201, a main memory 202,
an input/output controller 203, a keyboard 204, an input device 205
(e.g., a pointing device, such as a mouse, track ball, pen device,
etc), a display device 206, a mass storage 207 (e.g., a hard disk),
and a USB (Universal Serial Bus) peripheral connection 211.
Additional input/output devices, such as a rendering device 208
(e.g., printer, scanner, fax machine, etc), for example, may be
associated with the data-processing system 200 as desired. As
illustrated, the various components of data-processing system 200
can communicate electronically through a system bus 210 or similar
architecture. The system bus 210 may be, for example, a subsystem
that transfers data between, for example, computer components
within data-processing system 200 or to and from other
data-processing devices, components, computers, etc.
[0023] The following discussion is intended to provide a brief,
general description of suitable computing environments in which the
system and method may be implemented. Although not required, the
disclosed embodiments will be described in the general context of
computer-executable instructions, such as program modules, being
executed by a single computer. In most instances, a "module"
constitutes a software application.
[0024] Generally, program modules include, but are not limited to
routines, subroutines, software applications, programs, objects,
components, data structures, etc., that perform particular tasks or
implement particular abstract data types and instructions.
Moreover, those skilled in the art will appreciate that the
disclosed method and system may be practiced with other computer
system configurations, such as, for example, hand-held devices,
multi-processor systems, data networks, microprocessor-based or
programmable consumer electronics, networked PCs, minicomputers,
mainframe computers, servers, and the like.
[0025] Note that the term module as utilized herein may refer to a
collection of routines and data structures that perform a
particular task or implements a particular abstract data type.
Modules may be composed of two parts: an interface, which lists the
constants, data types, variable, and routines that can be accessed
by other modules or routines, and an implementation, which is
typically private (accessible only to that module) and which
includes source code that actually implements the routines in the
module. The term module may also simply refer to an application,
such as a computer program designed to assist in the performance of
a specific task, such as word processing, accounting, inventory
management, etc.
[0026] The interface 103 can include, for example, a graphical user
interface (GUI) or an interactive speech interface. The interface
103 can serve to display results, whereupon a user may supply
additional inputs or terminate a particular session. In some
embodiments, operating system 101 and interface 103 can be
implemented in the context of a "Windows" system. It can be
appreciated, of course, that other types of systems are possible.
For example, rather than a traditional "Windows" system, other
operation systems, such as, for example, Linux may also be employed
with respect to operating system 101 and interface 103. The
software application 104 can include, for example, an energy use
detection and management module 102 for providing a CASHEM. The
energy use detection and management module 102 can include
instructions, such as those of method 300 and 400 discussed herein
with respect to FIGS. 3-4.
[0027] FIGS. 1-2 are thus intended as an example, and not as an
architectural limitation with respect to particular embodiments.
Such embodiments, however, are not limited to any particular
application or any particular computing or data-processing
environment. Instead, those skilled in the art will appreciate that
the disclosed system and method may be advantageously applied to a
variety of system and application software. Moreover, the present
invention may be embodied on a variety of different computing
platforms, including Macintosh, UNIX, LINUX, a real time OS/kernel
and the like.
[0028] FIG. 3 illustrates a graphical representation of a
computer-implemented context-aware smart home energy manager
(CASHEM) 310, in accordance with the disclosed embodiments. CASHEM
recognizes and adjusts to different conditions around, and within,
a house 320, 340, 350, 360 to minimize total energy consumption.
Note that in FIGS. 1-9 identical parts or elements are generally
indicated by identical reference numerals. The disclosed
embodiments take advantage of dynamically planning, scheduling and
programming the different appliances of the house based on these
different conditions and the expressed user preferences within the
different conditions. The term "appliance" refers to any device in
the home that consumes, stores or produces energy. Depending on the
varying conditions 320, a home's appliances 350, 360 can operate at
lower or higher energy consumption levels based on the comfort or
convenience level demanded by the occupant. Adaptation of the
appliance coordination system can be supported based on monitoring
and analysis of occupant's activity and the use of the appliances.
The appliance tasks can also be shifted at some time in the future
to consume less energy based on the forecasted weather condition
321. CASHEM 310 is designed to work with existing homes and
appliances, and grow its capabilities as smart appliances and other
components are added to the home. CASHEM 310 can be the hub for
communicating with appliances 350, 360 and use information from
different operational, environmental, and energy supply type
parameters. As context sensors become available, CASHEM 310 can use
the sensors for enhanced energy management.
[0029] CASHEM 310 integrates renewable energy sources into the home
and reduces overall energy consumption. By increasing the focus on
systems design, integration, and control, CASHEM 310 serves as a
central point to collect information from all available sources and
build the big picture necessary to manage energy consumption. To
build the big picture of a home's energy usage 300, the
computer-implemented home network 330 connects a home's energy-use
contexts 320, a home's energy manager displays 340, and a home's
appliances, including both 24/7-type appliances 350 and on-demand
appliances 360. The home energy manager 310 connects to a home's
energy meter 329 to collect electricity use information.
[0030] "Context-awareness" describes the conditions of energy
consumption in the house. CASHEM's 310 objective is to identify the
current contextual state 320, 340 350, 360, note the user
preference associated with that current state, and then configure a
context-driven, appliance-use, convenience, or comfort, of service
(CoS) model. The CoS model correlates the different contexts with
energy consumption levels, and dynamically schedules the appliances
350, 360 under the stated conditions, based on efficient energy
consumption and occupancy comfort. The type and amount of CoS
deviation can vary between different homeowners with homeowners
submitting CoS preferences at system configuration time. CASHEM 310
reduces energy consumption while keeping the user comfortable by
adapting its recommendations to the occupant's expressed CoS
preferences. The system 310 can also monitor and analyze energy
consumption, recommend further energy saving actions, and
engage/motivate the homeowner to adopt those recommendations.
[0031] Contexts 320 that the system 300 gathers to formulate CoS
preferences include, but are not limited to: weather conditions
321, both current and forecasted; occupancy and occupancy activity
information 322; security system information 323; utility
information 324; renewable energy-use information 325; energy
storage information 326; and plug-in hybrid electric vehicle (PHEV)
information 327. CASHEM 310 integrates on-site energy generation
and renewable energy sources 325. With context-aware
characteristics, CASHEM 310 can coordinate use of wind and solar
energy with charging a hybrid electric vehicle to minimize energy
consumption and reduce carbon footprints. Combined heat and power
is becoming practical in some northern climates, while photovoltaic
panels are becoming cost-effective in the southwest. Energy
storage, particularly in the form of plug in hybrid electric
vehicles, is also making its way into homes.
[0032] CASHEM 310 coordinates energy manager displays 340 when
gathering a home's context information 320 to appropriately adjust
energy consumption. Energy manager displays include, but are not
limited to: In Home Displays 341; computing device 342, mobile
communications devices, such as a Smartphone 343, a computing
device 345B connected to the Internet 345A, HVAC controls 346 for
cooling 351 and heating devices 352.
[0033] An energy efficient home can have smart appliances capable
of one or two-way communication with CASHEM 310. The central
communications and data integration allows the home to be treated
as a system 300 as opposed to a collection of independent,
non-communicating appliances. CASHEM 310 can coordinate different
types of appliances, including both 24/7-type appliances 350 and
on-demand appliances. 24/7-type appliances include those appliances
used nearly twenty-four hours of a day, for seven days a week.
These include cooling 351 and heating 352 units, water heaters 353,
pool pumps and heaters 354, refrigerators and freezers 361.
On-demand appliances 360 include those appliances used less
frequently than 24/7-type appliances 350. On-demand appliances
include, but are not limited to: dishwashers 362, lighting 363,
consumer electronics, such as entertainment devices 364, appliances
that run off of wireless controlled outlets 365, including stereos
365A, computing devices 365B, and televisions 365C. CASHEM can
integrate other similar sensors and systems when additional
appliances are used in the home, such as security systems, smoke
detectors, HVAC, structured wiring, energy management, and video,
to provide one integrated system.
[0034] CASHEM 310 alerts users to pending problems through the
home's IP network 330. Condition-based monitoring (CBM) techniques
can be scaled down and integrated in CASHEM 310. Alerts to the
homeowner through various energy manager displays 340 can be as
simple as, for example, "The furnace has run 265 hours since the
filter was changed." CASHEM can use abnormal vibration detection to
identify potential problems in HVAC systems. CASHEM enables two-way
communication with the electrical grid 324 to obtain real-time
pricing and demand response events via an open automated demand
response (OpenADR) server or other mechanism that complies with
National Institute of Standards and Technology standards.
[0035] By adjusting to the occupant's preferences and behaviors
under different activity or occupancy conditions of the house,
appliance energy consumption is reduced while keeping the occupants
satisfied with a desirable CoS for each appliance under the
different conditions. The capabilities of the system 300 shown in
FIG. 3 are best described through a series of non-limiting CASHEM
310 use cases, as follows:
Example 1
[0036] Sleep mode activation: The homeowner goes to bed early 322.
CASHEM 310 is notified by the security system 323, which triggers
the HVAC system 346 to go into "Sleep" mode. CASHEM 310 also
enables the dishwasher 362 and dryer to complete their pending
cycles. The water heater's 353 settings are changed to reflect
reduced energy consumption 329. The entertainment devices 364 and
lighting 363 are scheduled turn off to reduce or eliminate energy
consumption 329.
Example 2
[0037] Vacation scheduling: Before leaving on vacation 322, the
homeowner notifies CASHEM 310. The online calendar indicates that
the homeowner can be away for a week 322. CASHEM 310 transmits
requests to all appliances 350, 360 to either shutdown or switch to
vacation mode. Other appliances 350, 360 may be shut down or
switched to vacation mode including: managing the HVAC system 346,
setting the water heater 353 and refrigerator 361 to power saving
modes, turning the entertainment system 364 off, lowering the set
point on the pool heater and pump 354 and turning off lighting 363,
as appropriate. Later in the week, CASHEM 310 is notified of the
Homeowner's impending return 322 through an SMS text message on a
Smartphone 343, or an e-mail or Tweet.TM. on a computer device
connected to the internet 345b. In response, CASHEM 310 prepares
the home for a homeowner's arrival.
Example 3
[0038] Convenience of Service: CASHEM 310 is aware of the
homeowner's CoS requirements. The homeowner prioritized on the side
of energy conservation. During the cooling season 321, CASHEM 310
looks for opportunities to bring in outside air 325 whenever
feasible instead of running the air conditioner 351 even though
this can affect humidity levels in the home.
Example 4
[0039] Adaptation of Schedule for 24/7 Appliances 350: CASHEM 310
noted that the homeowner's schedule has changed 322 due to seasonal
factors. CASHEM 310 determines a new energy-usage schedule that
better reflects the energy usage of the home 322 and presents it to
the homeowner. With the homeowner's concurrence, the new schedule
is put into trial service. Later the new schedule is accepted as a
permanent energy usage schedule.
Example 5
[0040] Adaptation for On-Demand Appliances 360: CASHEM 310 has
identified that the dishwasher 362 is generally run after dinner
322 with high CoS settings. Given time-of-use pricing and the
desire of the Homeowner to conserve energy 329, CASHEM 310
recommends using the dishwasher's 362 delay feature to start
washing after the lower prices set in. It also suggests using air
drying mode, since the clean dishes are not needed until the
morning.
Example 6
[0041] Predictive Load Management: It is Friday and the weather 321
is expected to be unusually hot. The utilities 324 issued a peak
pricing alert for the afternoon, but the homeowner generally works
from home 322 on Fridays. CASHEM 310 anticipates cooling needs and
pre-cools 351 the house during the morning hours on Friday to
reduce the load during peak hours, and raises the set point of the
HVAC system 346.
Example 7
[0042] Demand response and dynamic pricing: CASHEM 310 is notified
that peak pricing can be in effect and responds by taking actions
pre-approved by the homeowner to reduce demand on the utilities
324. Typical responses might include reducing set points of HVAC
346, water heater 353, pool pump and heater 354, and delaying the
start of energy consuming appliances 350, 360 such as dishwashers
362 and dryers. Depending on the criticality of the pricing request
and the CoS settings, more conservative actions can be taken.
Example 8
[0043] Renewable energy management: The home is equipped with a
small wind turbine 325 and battery storage 326. During the cooling
season, the wind forecast 321 indicates significant generation
potential overnight. Knowing the off-peak utility pricing and the
health and capacity of the battery 326, CASHEM 310 decides to first
charge the battery 326 then uses the excess energy to pre-cool in
anticipation of a hot summer day.
[0044] Illustrated in FIG. 4 is a flow chart illustrating the
logical operation steps of CASHEM's 310 operation, in accordance
with the disclosed embodiments. As illustrated in block 401, the
CASHEM process is initiated. CASHEM 310 first identifies contextual
information that affects the CoS of home appliances, as illustrated
in block 402. As illustrated in block 403, the user selects CoS
preferences on the computer-human graphical user interface 103
(GUI), as shown in FIG. 1. The GUI is provided to display and
capture the occupant's appliance operation preferences and
convenience constraints. Next, the appliances are configured for
the different home conditions using a selected CoS preference, as
illustrated in block 404. CASHEM 310 then extracts an appliance use
schedule to run the appliances at an efficient rate to guide the
occupant to either test or comply with further energy saving
opportunities, as illustrated in block 405. Through data
monitoring, the system can analyze energy consumption under
different conditions and recommend to the user further energy
saving opportunities, as illustrated in block 406. The CASHEM
controller continues to process and identify contextual information
and configure appliances, even when the user has not provided new
CoS preferences, as illustrated in block 407.
[0045] CASHEM 310 first identifies contextual information that
affects the CoS of home appliances, as illustrated in block 402.
Context describes a setting or a situation that impacts the energy
consumption of an appliance. Awareness of the context with respect
to the occupant or the home environment is used to significantly
reduce energy consumption without compromising the occupant's
comfort and convenience. Recognizing different types of contexts
can dictate development of efficient modes of operations for home
appliances. Three main types of context information exist as a
function of time that potentially affect energy consumption, as
follows:
[0046] Operational conditions: These are mainly driven by the
user's occupancy and can be summarized by short and long term
schedule. According to the user schedule, different user modes can
be identified as a function of time. For example, these user modes
include In, Vacation, At the Office, Sleeping, Party, etc.
[0047] Environmental conditions: This context type is typically
related to the current and predicted weather conditions around the
house. If the current and forecasted weather are known, some
appliance systems, such as HVAC, can potentially utilize efficient
operational strategies. Also, weather information such as sunny or
windy conditions can affect the renewable energy supply use in the
home.
[0048] Energy supply type and/or cost conditions: This information
is important for the integration and management of renewable
sources. It is related to the reliability of the current and
predicted energy supply from the available sources of energy. It
also includes the different utility signals including at least one
of the following signals: demand response (DR), real-time-pricing
(RTP) information, time-of-use (TOU) tariff.
[0049] As illustrated in block 403, the user selects CoS
preferences. The primary objective of CASHEM is to reduce the total
energy consumption around the house by providing an integrated and
optimal schedule that reflects the CoS for each appliance at
different times of the day. The gathered context information helps
develop a specific CoS level for a particular home. The CoS
settings are driven by the variations in context types. Based on
the homeowner preferences and convenience constraints under
different conditions or context information of the house, CASHEM
knows and recommends the best way of operating the home appliances
and renewable resources while meeting the requested convenience
constraint.
[0050] A CoS for renewable resources can also be defined according
to the estimated supply and related uncertainty level of the
supplied energy. A CoS metric is then applied to the different
appliances. The CoS level is related to the time it takes to finish
a job, or the thermal comfort in an environment. The CoS is
typically correlated to the amount of energy consumed. Based on the
condition driven by the context, the user can configure the CoS of
an appliance for that particular condition. The CoS can also
provide a range base control versus set point control to provide
the occupant with a choice between comfort vs. energy conservation.
For example, when the occupant is "IN", the CoS is 76+/-2 degrees
F.; when the occupant is "ON VACATION", the CoS is 62+/-4 degrees
F.; and, when the occupant is in the office, the CoS is 70+/-4
degrees F. The temperature range points are mapped to a CoS metric.
The user can change these CoS values under different supply type
modes, such as DR mode from utilities, solar supply, or wind
supply.
[0051] Once a CoS level is developed, a home's appliances are
configured, as illustrated in block 404. The initial operational
context extraction related to homeowner activity or schedule can be
implemented using programmable thermostats. Two approaches are
typically used to assess context information: direct sensing
measurements and indirect, inferred by integrating information from
multiple sensors. The static schedule can be enhanced by making use
of more accurate context extraction that is related to the user's
activity. Home appliances are first categorized under two distinct
categories, either as on-demand or 24/7 appliances, before
developing a CoS level, as follows:
[0052] On demand (OD) appliances are activated randomly, or
scheduled by external trigger. OD appliances include clothes
washers and dryers, dishwashers, televisions, lighting, etc. These
systems generally have discrete modes of operation. For on-demand
appliances, the task is to correlate the convenience constraints,
typically time range of use, to the energy consumption for the
discrete modes of operation. In general, the goal for the OD
appliances is to move to a lower CoS for the given condition, or
move the task to a different time of the day. For example, CASHEM
can recommend washing dishes in three hours instead of two when the
user is IN, or move the task to "SLEEP" time and wash the dishes in
5 hours.
[0053] For 24/7 appliances, the energy savings can be achieved by
recommending a lower CoS for a given condition or reducing the time
of the highest quality conditions. For example, a user could either
lower the heating set point from 72 to 68 deg F. for "IN" or shrink
the "IN" time to 7 hours instead of 8 hours based on occupancy
data. 24/7 appliances generally have continuous modes of operation,
such as controlling to a set point. These appliances also have
transitional modes of operations that move from one set point to
another, such as pre-heating or pre-cooling modes. 24/7 appliances
include equipments such as HVAC systems, water heaters, pool
heaters and pool pumps. The task for the 24/7 appliances can be
similar to the on-demand appliances. Weather conditions, however,
can affect the relationship and need to be included in the
assignment of a CoS analysis. For example, to maintain 76 degrees
F. for cooling conditions, ventilation can be provided if the
outdoor temperature is low. An example of CoS for heating and
cooling is a comfort index that can be calculated based on
temperature or more broadly based on a predicted mean vote (PMV)
(**) index that is based on actual temperature, humidity, wind
velocity, user activity and clothing. Some of these parameters can
be configured or estimated seasonally. The user can indicate his or
her tolerance of comfort range based on activity, weather, and
energy supply type.
[0054] As illustrated in block 405, CASHEM then extracts an
appliance use schedule. Under a given CoS, CASHEM can then select
the best mode for a particular appliance in each category and
estimate the energy consumed under a given CoS. A static schedule
is developed first. Typically, the static schedule during the
initial setup results in adherence to CoS preferences and lower
energy savings. CASHEM can also evaluate the cost of energy and
recommend a more efficient schedule based on energy cost while
maintaining homeowner satisfaction. In other cases, the schedule
can deviate enough that the unhappy user can turn off the
scheduling mode. CASHEM can reduce peaks using a combination of
range base control and load shifting via predicted scheduling. When
a demand peak is signaled, CASHEM can automatically shed loads
based on information from the homeowner. CASHEM can supervise and
properly schedule all the appliances during demand response by
multiple set point strategy for example, delaying running the
dehumidifier until well after the peak load. For additional energy
savings, CASHEM can respond to non-scheduled events requested by
the user.
[0055] As illustrated in block 406, CASHEM provides the user with
recommended energy-saving opportunities based on the data collected
and user-inputted CoS preferences. CASHEM provides recommendation
to the user to educate the user on current energy savings and
future modifications to CoS preferences to further increase energy
savings. The process ends, as illustrated in block 407.
[0056] FIGS. 5A-5B illustrate graphical representations of energy
savings using CASHEM's dynamic scheduling based on various
activities 511. For example, FIG. 5A illustrates energy savings
when using CASHEM 510 based on user's activity levels 511. CoS
preferences for different activity levels 511 are used to program
501 the energy-use levels of various appliances over a twenty-four
hour period. A user programs 501 energy use levels for "Sleep"
modes 512, "In" modes 513, an "Away" mode 514, and a "Swim" mode
515, for example. CASHEM dynamically schedules actual energy use
502 based on these CoS preferences for particular activities 511,
but also incorporates energy saving techniques discussed herein.
Therefore, CASHEM lowers actual energy use 502 for all scheduled
modes 512-515, as illustrated in FIG. 5B. During sleep modes 512,
energy use is lower than energy use during "In" 513 and "Swim" 515
modes. CASHEM's dynamical scheduling for lower energy use results
in energy savings 522 especially during modes of higher energy
use.
[0057] FIGS. 5C-5D illustrate graphical representations of energy
savings when using CASHEM's dynamic scheduling techniques to
provide a user with a recommended 503 energy savings usage plan.
For example, in FIG. 5B, CASHEM 520 uses HVAC set points 521 to
dynamically schedule for DR and activity 522. CASHEM's recommended
503 energy use levels are lower than programmed energy use levels
501. Similarly in FIG. 5C, CASHEM 530 uses pool set points 531 to
dynamically schedule for cost and activity 532. CASHEM's
recommended 503 energy use levels are lower than programmed energy
levels 501, as well.
[0058] CoS preferences and CASHEM options are programmed using a
graphical user interface (GUI), as illustrated in FIGS. 6A-6E. FIG.
6A illustrates a GUI 610-650 for display of CASHEM options, in
accordance with the disclosed embodiments. Note that the GUI 610,
620, 630, 640, and/or 650 can be implemented utilizing a GUI such
as, for example, the interface 103 depicted in FIG. 1 herein, and
may be provided by a module, such as, for example, module 102
(i.e., a software application). GUI 610, 620, 630, 640, and/or 650
can be displayed via a display device such as a monitor 206
depicted in FIG. 2. In the illustrated figures herein, the depicted
GUI can be implemented in the context of a GUI "window". Note that
in computing, a GUI window is generally a visual area containing
some type of user interface (e.g., GUI 103). Such a "window"
usually (but not always) possesses a rectangular shape, and
displays the output of and may allow input to one or more
processes. Such windows are primarily associated with graphical
displays, where they can be manipulated with a mouse cursor, such
as, for example, the pointing device 205 depicted in FIG. 2. The
user may use a mouse, joystick, light pen, roller-ball, keyboard,
finger or other peripheral devices for manipulating the pointing
device 205 over the GUI 610. For example, CASHEM options directly
on the GUI 610. A GUI using windows as one of its main "metaphors"
is often referred to as a windowing system.
[0059] The GUI 610-650 may include one or more active windows or
panes. In one implementation, four primary panes may be provided,
including a CASHEM query pane 601, a query response selection pane
602, a "Back" pane 603 to skip back to the previous GUI display
window, and a "Next" pane 604 to move forward to the next GUI
display window. These will be discussed in more detail below. Other
windows and panes may similarly be provided. Various mechanisms for
minimizing, maximizing, moving, and/or changing the dimensions or
the individual panes, may be provided as typically found in a
windows environment.
[0060] The disclosed GUI 610-650 uses a simple question and answer
paradigm to account for wide variations in occupants' perception,
definitions, and tolerance of different comfort levels. Therefore,
one of the keys to acceptance and compliance with CASHEM's
energy-saving recommendations is to tailor the energy tradeoffs to
individual homeowners. CASHEM initially extracts schedules for
every appliance and the related CoS range from the homeowner in a
series of interview questions presented on the GUI 610-650. Thus,
the homeowner does not need to be a programmer to implement an
energy-savings plan. With the success of the system riding on the
computer-human interaction, a homeowner interface to CASHEM engages
individual homeowners to indicate their own personal constraints
for comfort and convenience, provides a simple paradigm for
homeowners to review and understand energy management
recommendations made by the system, and communicates the value of
these recommendations, thereby motivating the homeowner to comply.
Improper use of programmable GUI's can reduce or completely
eliminate energy savings, so occupants need easy to use, innovative
GUI designs for programmable thermostats, for example, to ensure
energy savings.
[0061] CASHEM poses queries 611-651 to users and considers all
query responses 612-652 to formulate energy use schedules and
recommendations for every appliance. For example, in FIG. 6A, GUI
610 displays a query 611 asking the user, "When do you prefer to
run your dishwasher?" The user can select a query response 612
indicating the preferred time, or select the "Back" pane 613 to
skip back to the previous query. When the user makes a selection
from the query response pane 612, or selects the "Next" pane 614 to
skip this pane, the GUI 620 display appears as illustrated in FIG.
6B. The next query 621 displayed in GUI 620 asks the user, "When do
you prefer to use the heat dry feature?" The user can select a
query response 622 indicating the preferred time, or select the
"Back" pane 623 to skip back to the previous query. When the user
makes a selection from the query response pane 622, or selects the
"Next" pane 624, the GUI 630 display appears as illustrated in FIG.
6C. The next query 631 displayed in GUI 630 asks the user, "In
running your dishwasher, how quickly do you prefer to finish the
job?" The user can select a query response 632 indicating the
preferred selection, or select the "Back" pane 633 to skip back to
the previous query. When the user makes a selection from the query
response pane 632, or selects the "Next" pane 634, the GUI 640
display appears as illustrated in FIG. 6D. The next query 641
displayed in GUI 640 asks the user, "When do you like to run it
fast?" The user can select a query response 642 indicating the
preferred selection, or select the "Back" pane 643 to skip back to
the previous query. When the user makes a selection from the query
response pane 642, or selects the "Next" pane 644, the GUI 650
display appears as illustrated in FIG. 6E. The next query 651
displayed in GUI 650 asks the user, "When do you like to run it
slowly?" The user can either select a query response 652 indicating
the preferred selection, select the "Back" pane 653 to skip back to
the previous query, or select the "Next" pane 654, for any further
queries related to this appliance. This question and answer process
continues for CASHEM to gather enough CoS preferences and context
information to formulate a comprehensive energy-savings schedule
for all appliances within a home.
[0062] It will be appreciated that variations of the
above-disclosed and other features and functions, or alternatives
thereof, may be desirably combined into many other different
systems or applications. Also that various presently unforeseen or
unanticipated alternatives, modifications, variations or
improvements therein may be subsequently made by those skilled in
the art which are also intended to be encompassed by the following
claims.
* * * * *