the smart grid

1540-7977/10/$26.00©2010 IEEE66 IEEE power & energy magazine may/june 2010

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may/june 2010 IEEE power & energy magazine 67

Using Demand Response with Appliances to Cut Peak Energy Use, Drive Energy Conservation, Enable Renewable Energy Sources, and Reduce Greenhouse-Gas Emissions

By T. Joseph Lui, Warwick Stirling, and Henry O. Marcy

EENERGY GENERATION, CONSUMPTION, AND CONSERVATION ARE AT

the root of many of the most pressing issues facing society today. Demand contin-

ues to rise steadily while the ability to generate and deliver energy is increasing at

a much slower rate. In addition, as stated by the secretary of the U.S. Department

of Energy (DOE), Steven Chu, in his Grid Week 2009 presentation, 25% of U.S.

power generation and 10% of its distribution assets are associated with electricity

generation required during the roughly 400 hours of annual peak-energy-use peri-

ods, which represent hundreds of billions of dollars in investments. Furthermore, in

the United States, more than half of the electricity produced is wasted due to power

generation and distribution ineffi ciencies, according to 2002 Energy Flow Trends

data from the DOE. Very simply, using less energy in our daily lives, making more

effi cient use of the energy we do produce, and reducing global greenhouse-gas emis-

sions associated with energy generation are fundamental to our continued collective

prosperity and quality of life.

It is the thesis of this article that

the achievement of energy con-

servation and, hence, global emis-

sion reductions can be signifi cantly

accelerated by integrating smart,

energy-effi cient appliances into a

“smart” electricity grid—the so-

called “smart grid.” Smart applianc-

es shift the paradigm for appliances:

appliances are no longer merely

passive devices that drive emis-

sions but active participants in the

electricity infrastructure that can be

drawn upon for energy reduction,

energy storage, and the optimiza-

tion of the electrical grid for greater compatibility with its greenest energy- generation

sources. To amplify this latter point: by providing a variable load, smart appliances

connected to the smart grid are ideal complements to renewable sources of energy

such as wind and solar power, which are inherently variable in supply. We further

believe that given proper incentives and control over their smart products, consum-

ers will play a key role in reducing peak demand while lowering costs for consumers

and businesses and creating more environmentally friendly power generation.

A key feature of the smart grid is demand response (DR). As defi ned by the

Association of Home Appliance Manufacturers (AHAM) in a December 2009

smart grid white paper, DR refers to a set of scenarios whereby the consumer,

utility, or designated third party can reduce energy consumption during peak

usage or other critical energy use periods: “The North American Energy Stan-

dards Board (NAESB) has defi ned demand response as ‘changes in electric use

by demand-side resources from their normal consumption patterns in response

to changes in the price of electricity or to incentives designed to induce lower

electricity use at times of potential peak load, high cost periods, or when systems

reliability is jeopardized.’ ”

Digital Object Identifi er 10.1109/MPE.2010.936353

68 IEEE power & energy magazine may/june 2010

What this says is that when it is necessary to reduce peak

demand to avoid the use of high-cost and high-emission

power-generating resources or when the utility encounters

some other issue on the electrical grid that requires the

reduction of electricity demand, it can send a signal to the

home so that the system will reduce its electrical load during

this critical time period. This article describes the develop-

ment of a system that will reliably and securely accomplish

DR as part of the overarching smart grid.

It makes sense to focus on residential electricity use as a

primary means for enabling DR since, according to a 2009

Electric Power Research Institute (EPRI) study, residential

energy use accounts for a full 38% of the total energy con-

sumed in the United States. Home appliances; water heaters;

and heating, ventilation, and air-conditioning (HVAC)

systems together represent more than half of this consump-

tion, or 21%, of the total energy used in the United States.

Developing the smart grid and linking it to smart appliances

and other products having DR capabilities will reliably and

predictably reduce appliance electricity consumption in real

time. This will create the opportunity for signifi cant increases

in energy effi ciency and conservation and meaningful reduc-

tions in greenhouse-gas emissions.

Requirements for the Smart GridAHAM has outlined three primary requirements for the suc-

cess of the smart grid:

Consumer choice and privacy must be respected; the ✔

consumer is the decision maker.

Smart grid communications standards must be open, ✔

fl exible, secure, and limited in number.

Pricing must provide incentives to manage energy use ✔

more effi ciently and enable consumers to save money.

The way consumers engage with the smart grid is critical.

Consumers must be able to choose when and how they want

their smart appliances to participate in the smart grid. The

offer of fi nancial incentives—through time-of-use pricing or

other incentive plans—will be the single biggest driver for

consumers to change their energy consumption habits. The

beauty of the smart appliances currently being developed is

that they will empower consumers to obtain direct economic

benefi ts while also providing signifi cant benefi ts to utilities

and society at large (i.e., via lower investments and emissions

reductions) without compromising the core performance of

the products. Finally, the success of the smart grid depends

on public-private partnerships and the adoption of an open,

global standard for transmitting and receiving signals from

a home appliance.

Smart Grid DR System Architecture

OverviewThis section describes the smart grid DR system that Whirl-

pool Corporation and its partners will develop and demonstrate

as part of a smart grid investment grant under the American

Recovery and Reinvestment Act. The description will start at

a high level and then discuss in more detail each system com-

ponent. We conclude by describing selected use cases.

Figure 1 is a high-level representation of the smart grid

DR system architecture that Whirlpool will demonstrate;

it is referred to as the Whirlpool Smart Device Network

(WSDN). Consumer feedback and control is highlighted at

Smart Meter Domain

Smart Grid

Control

System

Smart Meter/AMI

Home Internet

Router

Smart Device

Controller

Computer or

In-Home Display

Open Communication

Protocol (OCP)

Electronic

Communication

Module

Home Area Network

Internet Domain

Consumer Energy Control

WISE

Whirlpool-

Integrated

Service

Environment

SEP 1.0 / 2.0

Smart Energy

Profile

figure 1. The WSDN architecture.


the top of the fi gure and represents an overarching WSDN

design element. The consumer must always be in control of

how appliances respond to signals from the smart grid.

Figure 1 further depicts three data communications

domains, including the smart meter domain, the Internet

domain, and the home area network (HAN). In an April

2009 paper, the Edison Foundation notes that the smart meter

domain represents the tens of millions of networked smart

meters that are being deployed by utilities as part of building

a so-called “advanced metering infrastructure” (AMI). The

Internet domain is the public Internet that consumers typi-

cally access through a variety of broadband service provid-

ers. The HAN represents the connection of appliances and

other smart devices in the home to one another and to both

the Internet and the smart meter domains. In the case of the

architecture being demonstrated by Whirlpool, the HAN

will be controlled by a smart device controller (SDC) that

hosts applications for monitoring, controlling, and coordi-

nating the activities of appliances and other smart devices

on the HAN. It also acts as a central gateway to both the

Internet and the smart meter domains.

The Three Levels of DR on the Smart GridIt is important to recognize and keep in mind the three levels

of smart grid DR that must be developed and coordinated on

a large scale in order to realize benefi ts from the smart grid.

At the lowest level is the response of an individual smart

appliance to a smart grid control or pricing signal. This

encompasses how an individual water heater, refrigerator,

clothes dryer, or dishwasher responds to the smart grid.

The second level of smart grid DR involves understand-

ing the present usage of and coordinating the responses

from all the smart appliances and other smart DR products

(e.g., solar panels, electric vehicle supply equipment, and so

on) in a given home. This is the role of the HAN. While it

may always be acceptable to a consumer to stop running the

smart water heater for some period of time, it may not be

acceptable to also adjust the operation of the clothes washer,

clothes dryer, and dishwasher at the same time. The SDC

operates the HAN and hosts an in-home energy management

system that manages DR coordination for all of the smart

appliances in the home based on a personal energy savings

profi le defi ned by the consumer. The SDC connects to the

Internet via the consumer’s broadband Internet connection.

The SDC also connects to the home’s smart meter via the

ZigBee Smart Energy Public Application Profi le and com-

munications protocol.

The third level of smart grid DR involves knowing the

potential, and coordinating the response from, hundreds to

millions of homes. Ideally, the smart grid DR profi le will

look just like an inverse power generator to a utility or grid

operator. That is, it will be a nearly square wave in nature,

having a predictable amplitude and reliable performance

over time. Whirlpool Corporation envisions this level of

smart grid DR will take place primarily via messaging on

the Internet, as the networks making up the smart meter

domain generally do not have the bandwidth or refresh

rates necessary to either cause or coordinate large-scale DR

actions in meaningful time frames. For example, in a 2009

Silver Springs Network white paper, it is stated that state-of-

the-art smart meter networks currently being deployed have

refresh rates for pricing and energy use information on the

order of one data set per hour per meter.

Using the WSDN architecture, Whirlpool and its partners

will be developing and demonstrating these three levels of

smart grid DR for a selected set of smart appliances through-

out 2010 and 2011.

Putting the Consumer in Control of DRThe requirement for consumers to control how their appli-

ances respond to control and pricing signals from the

smart grid has been discussed in numerous forums and is

a primary fi nding in recent consumer research related to

the smart grid, such as that undertaken by Litos Strategic

Communication and the Continental Automated Building

Association. In these reports, it has also been noted that

very few people want to spend time each day understanding

and coordinating how their appliances respond to control

and pricing signals from the smart grid. Whirlpool’s smart

grid demonstration system will use an in-home display and

controller to combine real-time energy use feedback with

simple smart grid energy savings response profi les. Many

have cited real-time energy use feedback as a key element

in helping consumers reduce energy use, and this was also

a key fi nding in the time-of-use pricing simulation studies

Whirlpool has conducted with consumers. The smart grid

energy savings profi les are provided as a straightforward

means for consumers to control to what degree they par-

ticipate in the smart grid, based on their personal priorities,

family schedules, and the energy saving incentive options

offered by local utilities or demand aggregators. Essentially,

these energy savings profi les defi ne several levels of par-

ticipation, from “full participation” to “opt out” and with

several gradations in between. These determine the degree

It makes sense to focus on residential electricity use as a primary means for enabling DR since residential energy use accounts for a full 38% of the total energy consumed in the United States.


of coordination and the absolute energy savings that will

be triggered when control and pricing signals are received

from the smart grid. The objective is to provide consumers

with simple smart grid participation options that produce

maximum benefi ts with little or no compromise in appli-

ance performance and with no need for regular consumer

interaction. The result for consumers will be a reduction in

their electricity bill with virtually no effort.

Smart Device Networking to Enable Smart Grid DRAs shown in Figure 1, the WSDN consists of three distinct

networking domains—the HAN, the Internet, and the smart

meter network. The system is designed to provide seam-

less connectivity and security across each of these network

domains. The HAN and Internet are described in terms of

the ubiquitous TCP/IP architecture protocol layers depicted

on the far left side of Figure 2. From left to right in the rest

of Figure 2 is the protocol stack for each individual appli-

ance (i.e., both the proprietary protocol within the appliance

and the translation of this protocol to the Internet and smart

meter networks via the communications module, or CM);

the architecture protocol for the SDC; and the architecture

protocol for a variety of Internet-based services, including

smart grid DR, referred to as the Whirlpool Integrated Ser-

vices Environment (WISE). Whirlpool is defi ning an open

communication protocol (OCP) across the CM, SDC, and

WISE to provide open standards–based, secure commu-

nication links that connect smart appliances to the WISE

using open and proven IP-based technologies. The OCP will

be supported and made available to any smart device manu-

facturer to allow seamless connection of its smart devices to

the WISE. This architecture provides secure, seamless fl ow

and scaling of smart grid DR application messages and data

across all levels of the system. The interface to the smart

meter network, which is not depicted in Figure 2, is expected

to be based on the ZigBee Smart Energy Public Application

Profi le, versions 1.0 and 2.0, which many utilities and smart

meter manufacturers have adopted. Apart from communica-

tions within each individual appliance, the WSDN is built

TCP/IP Architecture

Protocol Layers

WSDN Architecture

Protocol Layers

Application

Layer

Host-to-Host

Transport Layer

Internet Layer

Network

Interface

Layer

Appliance CM

XMPP

TCP

IP

Wi-Fi

TCP

IP

TCP

IP

Broadband

Connection

to Internet

Bro

adband

Inte

rnet

Zig

bee

Wi-F

i

XMPP

XML

Turn

Stunt

SASL XML SASL

TLS Turn

Stunt TLS

XML

Turn

Stunt

SASL

TLS

XMPP

SDC WISE

OCP Object Model – Common Profile, Plus Custom Profile

Applia

nce-C

ontr

olli

ng P

roto

col

Applia

nce-C

ontr

olli

ng P

roto

col

OC

P S

tack

OC

P S

tack

OC

P S

tack

figure 2. Protocol architectures for each of the networks in the WSDN.

Consumers must be able to choose when and how they want their smart appliances to participate in the smart grid.


on open networking standards,

protocols, and applications.

Figure 2 provokes several obser-

vations. Starting at the left with indi-

vidual appliances, the operation and

interface to these appliances will

continue to be handled with propri-

etary protocols and algorithms. This

is essentially where each manufac-

turer differentiates the performance

and user experience associated with

each appliance. Whirlpool expects

the interface from the HAN to each

of the individual appliance DR

actions will become standard at the

CM, so that appliances from mul-

tiple manufacturers will seamlessly interoperate and perform

as part of the smart grid. For interfacing each appliance to the

SDC so that communications can be established with both the

smart meter and the Internet, Wi-Fi (IEEE Standard 802.11)

is used (for demonstration purposes) as the physical layer of

the CM. But CMs may ultimately come in multiple varieties

or with multiple physical layer capabilities embedded in them

(e.g., power line carrier, ZigBee, cellular, and so on).

The WSDN SDC will support Wi-Fi, ZigBee, power

line carrier (PLC), and broadband Internet network inter-

face layers. The Wi-Fi will form the HAN with the smart

appliances; the ZigBee and PLC will connect with the smart

meter and the broadband Internet to the consumer’s Internet

connection. The SDC will be responsible for managing the

consumer’s smart grid energy savings profi les, for coordinat-

ing the smart grid DR of all the smart appliances and other

DR products in the home, for communicating the current

price of energy as loaded into the smart meter by the utility,

and for communicating via the Internet with the WISE in

order to provide real-time energy use and DR energy-saving

potential information to the utility or demand aggregator.

Individual Appliances as Part of a Smart Grid DR SystemA key aspect of creating a DR capability is developing

consumer- relevant DR algorithms for each of the major home

appliances that regularly consumes signifi cant amounts of

energy. How these DR algorithms modify the operation of

the machine is critical to achieving consumer acceptance and

delivering DR energy savings and societal benefi ts. Creating

consumer-relevant DR algorithms depends on detailed knowl-

edge of machine performance. Figure 3 shows energy use

during a typical operating cycle for a household dishwasher.

Table 1 provides a summary of a number of relevant energy

use statistics, and Figure 4 provides data from a 2008 National

table 1. Summary of DR opportunities related to shifting peak electricity use during the operation of major home appliances.

Appliance Type

Total Energy Consumed in Cycle(kWh)

Cycle Time(hour)

Peak Energy in Cycle(W)

Minimum Energy in Cycle (W)

Average Power During Cycle (W)

Percent of Peak Energy Use Shift Moving from Max to Min Consumption (%)

Load-Shedding Period Without Adverse Consumer Impact (min)

Electric clothes dryer 3.0 0.75 6,000 200 3,000 97 20–60

Dishwasher 1.4 1.75 1,180 240 800 80 60–90

Refrigerator 2.1 24 574 20 89 97 40–60

1,4001,200

1,000

800

600400

20000:00 0:08 0:16 0:25 0:33 0:41 0:49 0:58 1:06 1:14 1:23 1:31 1:39 1:48 1:56

Heater On Heater

On

Heater On

Heated Dry.

Heater Is On

Main Wash. Heater Ison for Approx. 5 min

Final Rinse. Heateron Approx. 15–20 min

Watts

Time (hh:mm)

Dishwasher Energy Consumption Profile

Heater On Heater

On

Heater On

Heated Dry.

Heater Is On

on o for Approx. 5 min on Approx. 15–20 min

figure 3. Energy use profile during the operation of a typical U.S. residential dishwasher.

0.12

0.1

0.08

0.06

0.04

0.02

01 4 7 10 13

Hour of Day

16 19 22

Perc

enta

ge

figure 4. Time of use and percent of total U.S. power consumption profile for U.S. dishwashers (source: NREL).


Renewable Energy Laboratory (NREL) technical report on

typical usage curves for the U.S. market.

From these data it can be seen that the residential dish-

washer is an ideal DR appliance because its energy consump-

tion can be totally deferred by delaying the operation of the

machine to a later time in the evening without causing signifi -

cant inconvenience to the consumer. Dishwasher usage in the

United States spikes in the early evening soon after dinner

and often coincides with peak electricity demand. Making

consumers aware of this and incentivizing them to delay their

dishwasher use will dramatically

reduce peak energy consumption.

From a DR algorithm perspec-

tive, in addition to the opportu-

nity for complete deferral of the

entire operating cycle, there are

also signifi cant power reduction

opportunities available during the

cycle by delaying the fi nal rinse

and/or delaying—or perhaps even

eliminating—the heated drying

portion of the cycle. Eliminating

the heated drying cycle results in a

reduction of the absolute amount of energy consumed as well

as a time-shifted consumption—a double win.

Figures 5 and 6, along with Figures 7 and 8 and Table 1,

provide similar energy and time of use data for residential

clothes dryers and refrigerators. As shown in Figures 5 and

6, electric clothes dryers offer very signifi cant opportunities

for shifting peak electricity use, because the difference in

electricity use between heating the air the clothes are tum-

bling in and just running the motor to tumble the clothes is

well over 5 kW. The typical time of use for clothes dryers in

the United States is spread more evenly throughout the day

than is the case for dishwashers, with the peak occurring

at about 10 a.m., thereby providing more opportunities for

DR participation. From a consumer performance perspec-

tive, clothes dryer cycle times and energy consumption are

nearly linearly related, indicating that some amount of heater

on-off cycling upon receiving a DR signal will not dramati-

cally affect drying performance but will lengthen the total

operating cycle by an amount slightly less than the total time

the heater is shut off. Periodically turning the dryer heater

on and off and thereby lengthening the operating time has

an additional benefi t: it reduces total clothes dryer energy

consumption by making better use of residual heat.

With respect to refrigerators, Figures 7 and 8 and Table 1

show that there are some opportunities to shift peak electricity

use by moving the defrost and ice-making cycles to off-peak

times. In general, however, the overall DR opportunity for

refrigerators is much less than for other household appliances.

Energy Management and the WISEThis section provides an overview

of how the network will be used to

provide energy management ser-

vices to consumers and utilities. In

applying the WSDN to the smart

grid and energy management, there

will be a variety of functional ser-

vices available. These will include

a number of historical energy use

and real-time databases; a variety

of generic customer interaction

7.06.05.04.03.02.01.00.0

Heater On

0:00 0:05 0:10 0:15 0:20 0:25 0:30 0:35

Time (hh:mm)

Heater Off,Tumble On

Wa

tta

ge

(kW

)

Dryer Energy Consumption Profile

figure 5. Energy use profile for a typical U.S. electric clothes dryer.

0.1

0.08

0.06

0.04

0.02

0

1 3 5 7 9 11 13 15 17 19 21 23

Hour of Day

Perc

enta

ge

figure 6. Time of use and percent of total energy used by U.S. clothes dryers (source: NREL).

700

600500

400

300200

100

0

0:00

1:20

2:41

3:56

5:19

6:40

8:01

9:22

10:4

1

12:0

5

13:2

1

14:4

3

16:0

4

17:2

5

18:4

8

20:0

7

21:2

8

22:4

8

Time (hh:mm)

574.7PulseDefrostCycle 386.7

Ice-Making

274.8

149.411

8.2

Compressor on Cycle(Door Openings = LongerCycles)

Possible Energy Consumption Pattern over a 24-h Period

Wa

tta

ge

(W

att

s)

figure 7. Electricity use profile for a typical U.S. refrigerator.


services, such as subscriber management and authentication,

authorization, and accounting (AAA); business application

modules such as an energy management server (EMS); an

interface to third-party applications; and infrastructure (e.g.,

an interface to the utility back-end systems and interfaces

to the consumer). Some of these will be off-the-shelf, Web-

based functional blocks; others will be developed as part of

the smart grid demonstration program. Figure 9 provides a

visual depiction of these functional blocks and some of the

instances that may be found within them for the smart grid

energy management application.

Specific Smart Grid Energy Management Use Cases for the WISEWith the system functional blocks defi ned, we can now look

at specifi c examples of using the WISE for performing aspects

0.06

0.05

0.04

0.03

0.02

0.01

01 4 7 10

Hour of Day

13 16 19 22

Perc

enta

ge

figure 8. Time of use and percent of total energy used by U.S. refrigerators (source: NREL).

figure 9. The functional blocks for the WISE that will be used to provide energy management services for the smart grid.

Databases

DBMS for Data-Warehouse DBMS for Transactions

ContentSource

Interface

AAA

AccountManagement

NetworkManagement

Server

Web Server

Business ApplicationModules

End User Interface Modules

Part

ner

and T

hird-P

art

y Inte

rface M

odule

s

UtilityBackendInterface

UtilityAccounting,

Billing,ClearingInterface

HistoricalConsumption

Data

HistoricalDevice Status

Data

Device

Profiles

Billing andAccountingDatabase

CertificatesSubscriber

ProfilesApplication Related Data

SubscriberManagement Server

Billing andAccounting

Server

CCP Device Management Server

DeviceManagement

Service

Network-LevelEnergy-Management

Server

Demand-ResponseApplication

The smart grid DR system described here will deliver significant benefits for consumers, utilities, and society at large.


of residential energy management with the smart grid. We

will examine how a consumer will interact with the WISE to

defi ne a smart energy profi le and thereby control how the home

responds to signals from the smart grid. We will also discuss

how a utility will interact with the smart grid in order to reduce

the amount of power required by the grid in real time.

Consumer Interaction with the Smart Grid Using a Smart PhoneConsider the actions that occur when a consumer wants to

alter his or her smart energy profi le to control how appli-

ances respond to energy management and pricing signals

from the smart grid. In this case, the consumer will perform

this task using a Web-enabled cellular telephone or smart

phone. The process will be as follows:

The consumer downloads the WSDN user applica-1)

tion and installs it on a smart phone.

The consumer launches the WSDN management 2)

app on the smart phone. The app automatically con-

nects to the WISE’s Web server (an end-user inter-

face module, shown in Figure 9).

The consumer enters an ID and password to log on. 3)

Data are passed from the smart phone to the subscriber

management server (SMS) through the Web server.

The SMS authenticates the user-entered data (ID and 4)

password) against a subscriber profi le database.

If authentication is successful, the SMS retrieves 5)

the consumer’s authorization data (i.e., a smart en-

ergy profi le).

The SMS builds a front-page smart energy profi le 6)

based on the consumer’s authorized services.

The SMS forwards the front-page content to the 7)

Web server.

The Web server formats the page and forwards it to 8)

the consumer’s smart phone.

The consumer modifi es fi elds in the smart energy 9)

profi le and submits the modifi cation.

The data updates are forwarded to the SMS via the 10)

Web server.

The SMS validates the received data and modifi es 11)

the consumer’s profi le in the subscriber profi le data-

base accordingly.

By the end of 2011, Whirlpool will be on track to deliver at least 1 million smart appliances to the U.S. market capable of responding to DR signals.

Device

S-MIME – Encrypts the Actual Data Sent by the Application over Encrypted Connection

SASL – Authenticates the Connection and Authorize Users over the Encrypted Connection

TLS – Provides a Secured, Encrypted Connection at the Transport Layer

SASL

TLS

TCP

Turn/Stunt

XMPP

IP

SASLXML

TLS

TCP

Turn/Stunt

XMPP

IP

Internet

Energy Management

OCP Messagingand Media Interface

Bus

OC

P T

ransport

Wi-F

I

Zig

bee

Bro

adband

Inte

rnet

OC

P T

ransport

Bus

OCP Messagingand Media Interface

Energy Management

WISE

figure 10. The three layers of security provided within the WSDN architecture.


The SMS builds a notifi cation message targeted to the 12)

consumer’s SDC and sends it to the open communica-

tions protocol (OCP) device management server.

The OCP device management server keeps a map-13)

ping table of its registered devices and subscriber

IDs. It fi nds the target SDC, encapsulates the noti-

fi cation message in the OCP protocol, and forwards

the notifi cation message to the SDC.

Utility-Scale Energy Management Using the Smart GridThe following is an example of how a utility may interact

with the WISE to cause DR actions across hundreds to mil-

lions of homes located within its smart grid. There are two

preconditions:

The utility’s back-end interface is up for contracted ✔

utilities to connect.

The end user device statuses are up-to-date in WISE. ✔

The process is as follows. Note that each message between

an app server and the SDC in each home will go through the

OCP device management server.

The utility detects a heavy load on its grid and sends 1)

a load-shed request to WISE. The request should

specify the number of watts needed and the time

and duration and provide a list of geographical ar-

eas (e.g., ZIP codes).

The utility back-end interface module forwards the 2)

request to the EMS.

The EMS runs through an algorithm, estimates the 3)

potential load shed for the requested geographic ar-

eas, and generates a list of energy-curtailment com-

mands targeted to particular qualifi ed users. The

algorithm is based on several factors including, for

example, the real-time status of all devices in the

From the perspective of an individual household, time-of-use pricing will enable significant energy bill savings.

table 2. Summary of cyber security risks and mitigation plans.

Scenario Description(Threat or Vulnerability)

Impact to System Mitigation Plan

Back-End Server Threats

The back-end server is compromised through DoS attacks.

High DoS attacks are mitigated by implementing proven approaches, such as restricting concurrent connections and the connection rate from clients, and by using encryption key and certificate control in the end-point devices.

Internet Domain Threats

The network link between the back-end server and user is compromised.

Moderate Since the proposed architecture is based on a distributed-computing model, any single point of failure will not affect the whole environment. The intelligence distributed on the SDCs will continue working by means of the energy management schedule and built-in algorithms. When the lost connections are restored, the whole system will be returned to normal.

HAN Threats

Home appliances are controlled by illegitimate sources.

Low The dual linkage between the consumers and the servers (through the Internet domain and the smart meter domain) gives the smart grid control an opportunity to compare energy usage reports received through the Internet domain with data from the smart energy control. Whenever suspicious patterns are detected, the appliance will be isolated and a report will be sent to the consumer.

Smart Meter Domain Threats

The interface to the utility grid through the smart meter network is compromised.

Moderate Once again, since the proposed architecture is based on a distributed-computing model, any single point of failure will not affect the whole environment.

Consumer Energy Control Threats

The consumer’s interactive device is compromised.

Low Since the consumer’s interactive device does not connect directly to the other two control domains (the smart meter domain and the Internet domain), the threat will be localized and the impact to the system will be minimal.


geographical areas, user consumption preferences,

and historical data.

The EMS sends the estimated load shed to the util-4)

ity. The utility sends back its go-ahead with the esti-

mated load shed.

The EMS initiates the command distribution pro-5)

cess by sending out the energy-curtailment com-

mands to all targeted SDCs, using multicast.

Each SDC receives the energy-curtailment com-6)

mand and executes it with the appliances under

its management (this is determined by the smart

energy profi le that the consumer has set up).

Each appliance, upon completion of the energy-7)

curtailment cycle, reports the energy saved back to

the SDC.

The SDC sends the command completion message 8)

back to the EMS.

The EMS, whenever it receives a completion mes-9)

sage from an end-user device, will update the

subscriber’s database with the energy-saving data,

for verifi cation and accounting purposes.

The EMS, after receiving completion messages from 10)

all targeted devices or after a predefi ned period of

time, summarizes the total energy saved and sends

this information to the utility.

Security Using WISE and the Smart GridCyber security is a critical element in the development and

deployment of a viable smart grid. The proposed architec-

ture employs proven security technology in a multitiered

approach to secure each step in the communication and con-

trol process, from the HAN across the Internet domain and

smart meter domain to the smart grid control. These open

security frameworks and protocols encrypt and transport

data and messages while protecting connections from tam-

pering, theft, and malicious activity. Additionally, this secu-

rity framework allows confi guration of various security lev-

els for different areas of the network, different applications,

and different types of data on a real-time basis. Since these

technologies have already been proven in the public sphere,

they provide unbreakable security today and the fl exibility to

adapt to emerging threats in the future.

The security objectives are to provide:

Confi dentiality: ✔ to ensure that information is not dis-

closed unless authorized

Integrity: ✔ to verify that data sent between the appli-

ance and utility cannot be altered or destroyed

Availability: ✔ to ensure that the smart grid system is al-

ways available and the system data are safe (the smart

grid system is also protected from denial-of-service, or

DoS, attacks and viruses that could potentially bring

the system down or delete fi les)

Privacy: ✔ to ensure that each participating family or

individual maintains control over personal data.

The security design approach has incorporated the fol-

lowing elements:

Openness: ✔ The security protocols and methods are

constantly tested, analyzed, and improved in the real

world by the wider security community. This security

approach can evolve as new threats emerge.

table 3. Expected savings for an individual household, based on the number of loads for which an electric clothes dryer participates in a DR program by shifting use to a time having a lower electricity cost.

Price Reduction of Off-Peak Power

Nu

mber

of D

ryer

Cycle

s S

hifte

d

$ 0.09

$ 4.68

$ 9.36

$ 14.04

$ 18.72

$ 23.40

$ 28.08

$ 32.76

$ 37.44

$ 42.12

$ 46.80

$ 51.48

20

40

60

80

100

120

140

160

180

200

220

$ 0.30

$ 15.60

$ 31.20

$ 46.80

$ 62.40

$ 78.00

$ 93.60

$ 109.20

$ 124.80

$ 140.40

$ 156.00

$ 171.60

$ 0.70

$ 36.40

$ 72.80

$ 109.20

$ 145.60

$ 182.00

$ 218.40

$ 254.80

$ 291.20

$ 327.60

$ 364.00

$ 400.40

$ 0.18

$ 9.36

$ 18.72

$ 28.08

$ 37.44

$ 46.80

$ 56.16

$ 65.52

$ 74.88

$ 84.24

$ 93.60

$ 102.96

$ 0.15

$ 7.80

$ 15.60

$ 23.40

$ 31.20

$ 39.00

$ 46.80

$ 54.60

$ 62.40

$ 70.20

$ 78.00

$ 85.80

$ 0.12

$ 6.24

$ 12.48

$ 18.72

$ 24.96

$ 31.20

$ 37.44

$ 43.68

$ 49.92

$ 56.16

$ 62.40

$ 68.64


Real-world security: ✔ The security protocols and

methods are in use every day, proving to consumers

and utilities that their systems, appliances, and private

data are secure.

Modular architecture: ✔ Changes to one feature do

not affect the rest of the system. For example, updates

to the WISE do not affect security processes (such as

authentication and encryption). Improvements to the

security protocols can be implemented without affect-

ing the functionality or performance of the smart grid.

Standards-based architecture: ✔ The security archi-

tecture builds on existing technologies that have been

proven in the real world.

The security architecture is built using the Extensible

Messaging and Presence Protocol (XMPP), a framework

that leverages numerous existing security technologies to

lock, encrypt, and authorize each component and link in

the system. By applying multiple levels of protection, this

solution provides security greater than that used by fi nancial

transactions, e-commerce, and other mission-critical tasks

performed on the Internet today.

Under this security architecture, the security for

the communication between the HAN and the SDC is

achieved through three layers: the Transport Layer Secu-

rity (TLS), the Simple Authentication and Security Layer

(SASL) protocols, and Secure/Multipurpose Internet Mail

Extensions (S/MIME). Figure 10 illustrates this multilay-

ered architecture and the steps involved in each of the

three layers.

These multilevel security measures cover a wide array of

identifi able and potential security vulnerabilities. Our secu-

rity solution not only protects assets in the proposed WSDN

architecture but will also help protect the smart grid itself.

Table 2 summarizes the different cyber

security risks and their associated mitiga-

tion plans.

ConclusionThe smart grid DR system described here

will deliver signifi cant benefi ts for con-

sumers, utilities, and society at large. From

the perspective of an individual household,

time-of-use pricing will enable signifi cant

energy bill savings. Table 3 provides an

example of the savings a consumer can

expect to realize from participating in DR

programs with an electric clothes dryer.

The average U.S. consumer completes

approximately 300 loads of laundry per

year. If a consumer defers 50% of these

loads to times when there are lower elec-

tricity costs, the individual can expect to

save from US$40 to more than US$200

per year, depending on the price of elec-

tricity price from the local utility.

Utilities also can expect signifi cant benefi ts from using

a smart grid–based DR system that systematically controls

energy reduction across millions of homes at a time in a

coordinated fashion. These benefi ts include:

automatic energy reduction without any inconvenience ✔

to consumers

precise control of appliance power usage on a network ✔

level—a powerful facility for sharing the load among

participating consumers

a clear, real-time view of the aggregated demand-side ✔

energy-saving potential on the network that enables:

the prediction of required supply•

the setting of time-of-use and dynamic energy •

pricing

the ability to minimize the need for purchasing spin- ✔

ning reserves, thereby lowering costs and signifi cantly

reducing carbon emissions

the ability to delay the point at which additional gen- ✔

eration capacity must be built.

All of these are signifi cant new capabilities that will give

utilities a level of understanding and control over their oper-

ations that Whirlpool expects will lead to further effi ciencies

and savings.

Finally, having estimates for the range of time that peak

energy use could be delayed without incurring unaccept-

able consequences for the consumer (shown in Table 1)

and also the amount of peak energy use that can poten-

tially be shifted provides insight into the benefi ts that

can be obtained on a macro or societal scale. By simply

converting the numbers in Table 1 to peak energy savings

potential per one million smart appliances of each type,

we can estimate the total peak energy savings potential.

The results for these calculations and their extrapolation to

table 4. Economic benefits associated with 1 million smart appliances of each type participating in a DR program.

Impact of Moving 1 Million Appliances from On Peak to Off Peak

Appliance

Category

Dishwasher

Refrigerator

Electric

Dryer

© 2009 Whirlpool Corporation. All rights reserved. UPA Smart Energy Conference 2009

1,200 MW

500 MW

5,500 MW

2.4

1.0

11.0

$ 4.20 billion

$ 1.75 billion

$ 19.25 billion

Peak Load

Shifted per Million

Appliances

Equivalents of

500 MW

Coal Plants

Capital Cost Savings

of Constructing

Coal Plant*

*Source: Capital cost of coal power: $3,500/kW–Synapse Energy Economics:

Coal Power Plan Construction Costs, July 2008


capital cost savings based on reduced need for new power

generating capacity are presented in Table 4. Similar stud-

ies for residential electric hot water heaters—such as that

undertaken in 2009 by the Peak Load Association—have

indicated that the consumer-acceptable DR potential for

water heaters can be at least as high as that for electric

clothes dryers.

Further estimating the greenhouse-gas emissions reduc-

tion potential offered by shifting peak electricity use for

the same set of appliances provides the picture presented in

Table 5. These relatively simple analyses indicate that the

electricity economic savings and greenhouse-gas emission

reductions that can be obtained by using the smart grid and

the new capabilities it offers consumers and utilities for

shifting peak energy demand are very signifi cant.

Whirlpool and its partners are committed to making

the smart grid a reality. By the end of 2011, Whirlpool

will be on track to deliver at least 1 million smart appli-

ances to the U.S. market capable of responding to DR sig-

nals. Whirlpool and other companies also are working to

make smart water heaters and smart thermostats available

within a similar time frame. As long as the requirements

for smart grid success put forward by AHAM are adhered

to and implemented, society can expect to start reaping

large-scale benefi ts from the smart grid within the next

several years.

For Further ReadingS. Reedy. (2009, Sept. 21). Grid week: DOE Secretary Chu

on fighting consumer smart-grid resistance [Telephony

Online]. Available: http://telephonyonline.com/business_

services/news/doe-secretary-chu-smart-

grid-20090921

(2009, Mar.). Measurement & verification

for demand response programs. Association

of Edison Illuminating Companies Load

Research Committee White Paper p. 8.

[Online]. Available: http://www.naesb.

org/pdf4/dsmee_group2_040909w5.pdf

Electric Power Research Institute. (2009,

Jan.). Assessment of achievable potential

from energy efficiency and demand response

programs in the US (2010–2030) [Online].

Available: http://mydocs.epri.com/docs/

public/000000000001018363.pdfAssociation of Home Appliance Man-

ufacturers. (2009, Dec.). Smart grid white

paper—The home appliance industry’s

principles & requirements for achieving

a widely accepted smart grid [Online].

Available: http://www.aham.org/ht/a/

GetDocumentAction/i/44191

S. Uckun, “Integrating renewable en-

ergy into the power grid,” in Proc. Sus-tainable Urban Management Workshop,

Mountain View, CA: NASA Ames Research Center, Jan.

9–10, 2009.

R. Vaswani and E. Dresselhuys. (2009). Implementing

the right network for the smart grid: Critical infrastructure

determines long-term strategy. Silver Springs Networks

[Online]. Available: http://www.silverspringnet.com/pdfs/

SSN_whitepaper_UtilityProject.pdf

Litos Strategic Communication. The smart grid: An

introduction [Online]. US Department of Energy, p. 20.

Available: http://www.oe.energy.gov/DocumentsandMedia/

DOE_SG_Book_Single_Pages(1).pdf

Continental Automated Buildings Association State of

the Connected Home Market Survey 2008 [Online]. Avail-

able: http://www.caba.org/Content/Documents/Document.

ashx?DocId=32664

R. Herndon, “Building America research benchmark

definition,” Nat. Renewable Energy Lab., Tech. Rep. NREL/

TP-550-44816, Dec. 2008.

R. F. Troutfetter. (2009). Market potential for water heat-

er demand management. Peak Load Management Associa-

tion [Online]. Available: http://peaklma.com/documents/

WaterHeaterDemandManagement.pdf

BiographiesT. Joseph Lui is the global director of connectivity for

Whirlpool.

Warwick Stirling is the global director of energy and

sustainability for Whrlpool.

Henry O. Marcy is the vice president of global technol-

ogy for Whirlpool. p&e

table 5. Environmental benefits associated with 1 million smart appliances of each type participating in a DR program.

Environmental Impact–Reduction in CO2 Emissions

Appliance

Category

Dishwasher

Refrigerator

Electric

Dryer

© 2009 Whirlpool Corporation. All rights reserved. UPA Smart Energy Conference 2009

80%

95%

80%

49.5 Mil Lb

6.8 Mil Lb

52.1Mil Lb

4,200

560

4,300

Percent of Peak

Demand Move to

Off Peak Hours

Annual

Reduction In

CO2 Emitted1

Equivalent

Number of Car

Years of Emission2

1 Reduction in emissions from off-peak consumption: 209 lb CO2 / MWHr–eGrid

2007 summary, Dec 20082 Annual emissions of a personal car: 5.46 metric tons CO2 / vehicle / yr:

US EPA; Feb 2009