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Abstract

An often stated objective of the Smart Grid is to enable building energy demands to be more responsive to utility and grid system loads. By potentially providing utility capability for direct load control, measurement in support for dynamic pricing, and as well the granular data needed for energy use to be more precisely targeted to consumer needs, the Smart Grid may enable significant electric energy savings as well as peak demand savings. However, it is evident that choices made in smart grid deployment strategy and network architecture by utilities, guided by the policies of state and federal regulatory authorities, may significantly impact the outcome of the Smart Grid initiatives. As utilities begin their planning and implementation for Smart Grid, it remains ambiguous as to whether the elements needed for efficiency and demand response will be included. Will utilities offer dynamic pricing, and/or control customer systems directly? And will utilities provide customers with a more frequent and granular measurement of energy use? This paper considers these questions, and proposes architectural directions for the Smart Grid that compare utility-controlled and consumer-controlled energy networks. With utility control, the intelligence of devices is derived from a central control point via a private utility network. With consumer control, these devices use a control system that is located in the home or business, or on the Internet but ultimately managed by the needs of the consumer. For both of these extremes, as well as intermediate possibilities, we consider how choices impact the aggregate efficiency and demand response, as well as support/limit innovation in supporting a responsive energy future.
Architecting the Smart Grid for Energy Efficiency
Harvey Michaels and Kat Donnelly, Massachusetts Institute of Technology
ABSTRACT
An often stated objective of the Smart Grid is to enable building energy demands to be
more responsive to utility and grid system loads. By potentially providing utility capability for
direct load control, measurement in support for dynamic pricing, and as well the granular data
needed for energy use to be more precisely targeted to consumer needs, the Smart Grid may
enable significant electric energy savings as well as peak demand savings. However, it is
evident that choices made in smart grid deployment strategy and network architecture by
utilities, guided by the policies of state and federal regulatory authorities, may significantly
impact the outcome of the Smart Grid initiatives.
As utilities begin their planning and implementation for Smart Grid, it remains
ambiguous as to whether the elements needed for efficiency and demand response will be
included. Will utilities offer dynamic pricing, and/or control customer systems directly? And
will utilities provide customers with a more frequent and granular measurement of energy use?
This paper considers these questions, and proposes architectural directions for the Smart
Grid that compare utility-controlled and consumer-controlled energy networks. With utility
control, the intelligence of devices is derived from a central control point via a private utility
network. With consumer control, these devices use a control system that is located in the home
or business, or on the Internet but ultimately managed by the needs of the consumer. For both of
these extremes, as well as intermediate possibilities, we consider how choices impact the
aggregate efficiency and demand response, as well as support/limit innovation in supporting a
responsive energy future.
Introduction
The potential for information to help us increase the energy efficiency of buildings is
certainly large: examinations of building energy systems show that, in today’s practice, we
frequently fail to align our delivered end-use (especially air conditioning, heat, and lighting) with
the time and place that we require them. 1 In homes as well as large facilities, buildings use
energy for light and comfort unnecessarily when unoccupied, or to inappropriate levels where
occupied. While local controls such as clock thermostats, occupancy sensors, and photocell
dimmers exist, they are far from ubiquitous, and at times inoperative or ineffective at reducing
energy use waste. For example, Grid-enabled communications and transparency results in
mechanisms that uncover faults in buildings often saving 20-30% as compared with the systems
we now have. 2 It is therefore critical to consider the potential of systems for optimizing
consumers’ end-use needs based on information, consumer preferences, weather, schedules, and
time differentiated energy costs.
1 MacKinsey , July 2009.
2 Jim Butler, Cimetrics; Stephan Samouhos, MIT, case study presentations at MIT October 2009
11-163©2010 ACEEE Summer Study on Energy Efficiency in Buildings
One important objective of the Smart Grid is to enable energy demands in residential and
commercial buildings to be more responsive to utility and grid system loads. As experience is
gained from early deployments, we will determine the extent to which the Smart Grid could
increase the responsiveness of building energy use and displace the need for other energy
resources. 3 However, it is evident that choices made in smart grid deployment strategy and
network architecture by utilities, guided by the policies of state and federal regulatory
authorities, may significantly impact the outcome of the Smart Grid initiatives.
This paper presents findings from the ongoing MIT Energy Innovations Research
Project. 4 Through analysis of literature, consideration of the results of early trials, advisory
team interviews, and discussions at a project forum held in July 2009, our research explored the
roles for utilities, consumers, third-party providers of services and technology, and policymakers
in the build-out of consumer-side smart grid infrastructure.
Information-Driven Efficiency and Demand Response Mechanisms
Distributed information and intelligence-driven energy management have the potential to
create disruptive change in society’s use of energy. Potentially, the customer side of Smart Grid
architecture may address this opportunity with three strategies:
utility control of peak building energy use,
time-differentiated dynamic electricity pricing, and
more frequent and granular energy consumption data to support operational
improvements and behavior change.
Load control/demand response: Using utility network communications, the Smart Grid
may curtail consumer loads during critical system hours. It is estimated that 5.8% of our peak
loads are currently controllable and up to 20% could be controlled.5 This approach, historically
called load management, is now often called Demand Response (DR) - connecting system
requirements directly to consumer endpoints. For small consumers, utility load management
programs have for many years successfully shed loads on utility peaks. With radio and
powerline signals, these programs cycle air conditioners, raise thermostat set points, or shut off
water heaters as examples. AMI systems provide a lower cost and more ubiquitous system,
potentially aiding expansion.
Dynamic pricing: AMI deployments are increasingly focusing on the ability of AMI to
support time-differentiated (dynamic) prices, such as critical peak pricing (CPP) rates, which
charge their highest rate for a few hours on a handful of days per year when loads are highest. A
study comparing 15 recent dynamic pricing experiments found that critical-peak pricing tariffs,
under a variety of price structures, induce a drop in peak demand that ranges between 13 to 20
percent. 6
3 Leeds, David, GTM Research, 2009.
4 This research was carried out as part of the Energy Innovation Project, based at the MIT Industrial Performance
Center and led by Prof. Richard Lester. We are grateful for the support for this work provided by the Doris Duke
Charitable Foundation.
5 FERC, DR Assessment 2008 and DR Potential 2009
6 Faruqui and Sergici, 2009.
11-164©2010 ACEEE Summer Study on Energy Efficiency in Buildings
Granular energy use information: With the availability of hourly electric reads, early
research shows that, in addition to pricing, the information of AMI may by itself be a valuable
source of behavior change. With feedback about energy consumption, an interested energy
consumer can better manage their energy and money. There have been over 40 studies that have
identified how direct and indirect feedback on energy use can reduce energy consumption.
Direct, real-time, feedback through in-home energy displays and other enabling-technology can
have positive effects on consumer electricity efficiency, reducing average participant usage by
up to 15%. 7 Inferential analysis supported by granular data continues to advance; for example:
End use disaggregation analytics separate energy use into meaningful components. A
recent California study indicated that disaggregated end use information was, in fact,
more impactful than real-time feedback. 8
Benchmarks: New companies such as O-Power (formerly Positive Energy) focus on
providing consumers with benchmarks to understand their relative energy use, and are
comparing these consumers with a similar social or demographic group. Early
indications are that 5 – 10% energy savings may result from these benchmarks.9
Collective Action: With ubiquitous metering, there is the potential opportunity to leverage
the benefits of shared information resulting in greater individual behavior change.
Anecdotal trials suggest that group dynamics hold a tremendous potential, with several
models under consideration, including competitions and group rewards or recognition. 10
Smart Grid Architecture and Energy Efficiency
Smart Grid is a broad objective, addressing opportunities for enhanced communications
and control in transmission and distribution of electricity. Within distribution, a key component
under consideration is Advanced Meter Infrastructure (AMI), which is usually defined as
measuring energy use at the meter at hour intervals or less and communicating these reads at
least daily to the utility. However, it remains ambiguous as to whether the deployments will
include the elements needed for efficiency and demand response. For example, will utilities
offer dynamic pricing, and/or control customer systems directly? And will utilities provide
customers with a more frequent and granular measurement of energy use? The paper reports
findings on three architectural dimensions of AMI:
1. In-facility Local area networks: thermostats, appliances, controls.
2. Utility-facility Communication.
3. Content Provisioning.
1. Controlling Appliances with Utility vs. Consumer-Controlled Architectures
AMI provides operating benefits including reduced meter reading costs, outage
management, and granular visibility on distribution components including transformers.
However, in many cases, energy efficiency, including but not limited to peak demand reduction,
7 Summarized by Darby,2006 and EPRI, 2009
8 Herter, K., 2010
9 OPOWER. (2009). The Home Energy Reporting System Fact Sheet.
10 EPRI, 2009.
11-165©2010 ACEEE Summer Study on Energy Efficiency in Buildings
is important to the business case to proceed with Smart Grid. Automated control of appliances
and thermostats is one approach to creating a sustainable energy impact. In fact, Home Area
Network (HAN) enabling technologies are now viewed as an important element of achieving the
highest peak demand savings. In the summer of 2003 the California Statewide Pricing Pilot
found that average peak savings were 34.5% on households with enabling technology such as
communicating thermostats, appliance cycling devices, and in-home displays. 11 This is
substantially higher than the 12.5% achieved by pricing-induced behavior alone, and as a result
some utilities and regulators have reworked AMI plans to include control strategies to capture
these potential benefits.12
At the ends of the spectrum, two disparate approaches are under consideration to more
intelligently manage devices in the home; utility and consumer controlled architectures.
Utility-controlled architectures create resource benefits, particularly lowering system
peak demand, with controls operated by the utility on their customers’ air conditioning, water
heaters, pool pumps, and other equipment. The infrastructure of AMI/Smart Grid however
provides a lower cost, and more ubiquitous capability to achieve utility-controlled demand
response as compared with the systems used historically.
The benefits of the utility-controlled approach include:
A deterministic demand impact, since these are implemented by switching capabilities
controlled by the utility, as compared to the potential uncertainties of a consumer
decision in response to price.
Typically, the in-home control equipment in this paradigm is provided by the utility to
the consumer at no cost, increasing near-term penetration rates, and does not require the
consumer to have any form of Internet access. 13
Since the system is utility managed, attribution of the demand impact to the utility
infrastructure investment of such control is very clear, simplifying the evaluation of
benefits for incentive ratemaking.
Issue with the utility-controlled approach: Speculating forward on the Smart Grid
option, the utility controlled approach anticipates in the years ahead that generation,
transmission, distribution, and end use equipment will, in effect, collaborate directly as part of a
single system, without any direct consumer involvement. Consumers express concerns regarding
consumer choice and privacy, with detractors envisioning a scary Big Brother-like network as a
natural extension of this approach. As a result, in 2008, the California Energy Commission
needed to scrap a plan to require programmable communicating thermostats (PCTs) in new
construction, following a public outrage at a perceived trend towards utility access to home
controls and information.14 The PCTs were to have radio capabilities to respond to utility signals
to increase home temperatures during system peaks, and report home temperatures and
compliance back to the utility. To this point, it is unclear as to whether these fears will subside,
as society’s concerns for other information-related technological changes have over time, or
force an end to this paradigm.
11 Statewide Pricing Pilot Summer 2003 Impact Analysis, Charles River Associates, Table 1-3, 1-4, August 9, 2004.
12 Pacific Gas and Electric announced reconsideration of its AMI plan with this objective in June 2007.
13 While the consumer is not charged, the costs are embedded in rates paid by all consumers.
14 Barringer, F. (2008). California Seeks Thermostat Control. New York Times Retrieved from
http://www.nytimes.com/2008/01/11/us/11control.html
11-166©2010 ACEEE Summer Study on Energy Efficiency in Buildings
By comparison, consumer-controlled architectures are composed of consumer
purchased and configured building (LAN) or home (HAN) network devices that optimize
appliances to meet the consumer’s objectives for comfort or function, while minimizing energy
costs and/or carbon footprint. Often, these devices connect to public networks, and interface
with the consumer through Internet applications (often called control panels or dashboards)
provided with the devices, or offered by third parties such as Google, Microsoft, or even the
utility (but under consumer control). Utility AMI systems that support time-based pricing are
beneficial, as they can add value to these systems if properly implemented. Direct interface with
the meter network is not absolutely required, as price information can be made available over the
Internet or intercepted by an in-home display.
Consumer-controlled benefits: Supporters argue that the consumer-controlled approach
has the following benefits as compared with utility-controlled demand:
Compared with utility control, consumer control has a similar theoretical potential to
create demand impacts, but with price as the arbiter there is a boundary providing greater
privacy to the consumer.
Consumer control is more likely to generate energy savings as well as peak demand
savings. Since total dollar savings is a common consumer goal, the system is more likely
to save significant energy throughout the day, week, and seasons, while utility controlled
systems are typically focused on the peak hours of the year.
With time-based (dynamic) pricing, there is a more obvious connection to hourly meter
read capability of AMI than with demand response, justifying the utility’s investment.
It is argued that time-based rates are inherently more fair and inevitable: without them,
some consumers, such as those without peak-contributing central air conditioning, are
paying too much and are subsidizing AC consumers. 15
Home area network (HAN) devices leverage existing networks already in the home such
as Internet, mobile, cable, and in-home power lines for communication and control are
more likely paid for directly by the consumer, rather than the utility (although all utility
costs are indirectly borne by consumers through rate-setting). As a result, the utility total
cost of the system may be less.
Issue with the consumer-controlled approach: The consumer approach is more reliant on
the market to develop options, and the consumer to both purchase and use them, to get the
desired energy and demand impacts. As a result, it is necessary with this approach that the utility
provide a system to accelerate adoption, similar to the objective of other efficiency programs.
Several, including Commonwealth Edison and Duke Energy have announced significant
customer and market partnership programs.16
Potential 5-10 year innovations in consumer-control architecture: Just as the
capabilities of Internet and electronics have continued to progress for a variety of consumer
applications, one would anticipate that a decentralized ecosystem of competitive applications
will continue to adapt to the improving understanding of consumer preferences. Some directions
that have been already considered or are under development include:
15 Faruqui, The Ethics of Dynamic Pricing, 2010
16 Vardell, 2008.
11-167©2010 ACEEE Summer Study on Energy Efficiency in Buildings
Improved control precision: In time we can anticipate improvements in sophistication
of control. For example, in addition to the control of heating, air conditioning, hot water, and
pool pumps, we can anticipate that in time refrigerator/freezers could modify their use pattern by
linking their internal control logic to a home network signal of high cost, a scenario already
being beta-tested in select households. In addition, comfort settings are increasingly more
automatic, and mitigation is possible by pre-overcooling of the home, for example, prior to
anticipate high cost periods to allow the system to coast.17
Thematic control: A trend to establishing default settings in complex electronics is to
offer the consumer a few high-level thematic choices. Browser Internet security settings set
many parameters based on a consumer’s selection of low, medium, or high security. Some
automobiles have tunable transmissions that allow power vs. economy settings. Similarly, we
can see the trend towards thematic options in home controls, allowing consumers to select their
preference for maximum economy, low carbon footprint, or full-but-not wasteful comfort.
Adaptive control: Many software systems improve their functionality for the consumer
through automatic response to user experience. For example, voice recognition systems adapt
based on the history of corrections, as do many other functions on websites, word processing,
and mobile phones. In time the response of household and business energy systems to dynamic
pricing can be designed to adapt to user corrections, reflecting preferences more accurately
through learning, and over time requiring fewer corrections. As an example, if a more general
thematic setting such as “super green” had been selected, but the consumer at regular times
adjusted the heating or cooling for increased comfort, the software system can learn and tune the
controls to more accurately reflect these preferences in the future.
2. Communications - Utility Meter network vs. Public Network Approaches
Somewhat independent of the question of utility vs. consumer-controlled load is whether
utilities should provide proprietary meter network connectivity, or alternatively communicate via
Public Internet.
With the meter network approach, the utility provides the meter-to-display and meter-to-
control devices, and in most models subsidize them substantially for provision to consumers,
with the costs recovered through rates. In early trials of Smart Grid-enabled controls, most
systems offered a paradigm of utility-controlled smart thermostats, with on-device displays,
firmware, and utility-network connectivity. In-home display pilots have been typically deployed
in the kitchen or dining room, providing basic information on metered electricity use and prices
in real time.
However, if the meter network is going to manage the devices, it needs to have greater
bandwidth, two-way capability, and more upgradeability than systems installed to date to service
these needs over the next 20 years, a typical meter network system life. As a result, a meter
network gateway system may have $50-$200 per home additional costs for these system
capabilities, excluding the costs for any utility-provided HAN devices.
With public network approach, the home network components communicate through a
market-provided home network wireless router to connect with the home computer or other
market-provided processor, which in turn connects with the public Internet, as do other devices
like printers and computers on a home network today. Alternatively, home powerline and/or
wireless broadband may support the home area network.
17 Galvin Electricity Initiative, 2007.
11-168©2010 ACEEE Summer Study on Energy Efficiency in Buildings
Consideration of AMI high bandwidth and two-way communication capability: With the
consumer-controlled approach focused on dynamic pricing with Internet-provided
communications and information presentment, one-way hourly meters may be sufficient for this
purpose, as there is no need for control capabilities to be built into the AMI network itself.
Further, bandwidth needs are less, potentially reducing the AMI cost and increasing the number
of options available. Also, since the consumer buys the display and control equipment, these
costs are less for the utility. As a result, if AMI system costs are substantially higher for high
bandwidth two-way capabilities (considering the cost of communication devices and upstream
software and control systems), these may not be justifiable costs based on efficiency and DR
considerations.
Benefit of containing the requirements for AMI: Certainly, the higher the stakes in terms
of initial cost, and the greater the technology expectations placed on the system, the more
difficult it will be for AMI to move forward. Not only will the higher costs produce near-term
rate impacts that might be politically unacceptable, the breadth of current and near-term future
solutions will slow the purchasing process. In addition, the higher requirements expand concerns
for upgradability, obsolescence, and standards. Therefore, to achieve the necessary
opportunities for AMI-enhanced energy use, minimizing the technology requirements is an
important focus of policy and regulation.
3. Content: Meter Information and Analysis
A third related architectural issue is provision of information; again the main question is
whether the utility is the provider or the market: who will design and deliver information that
consumers need to better manage their homes and buildings?
Meter-to-Home Network Communications: In the last section, we discussed Internet
options that reduce the necessity of utility-to-meter communication. Nonetheless, it is valuable
for the meter systems to provide at a minimum hourly reads directly to the home for use by
consumers with their web workspaces. Several AMI systems offer technology in the meter that
broadcast short-interval reads directly to the home. These short-interval reads on demand (when
the consumer can use them) are a key ingredient in measuring differential energy use, supporting
the measurement of load, and cost, of any device in the home.
At the low marginal cost of $10 or less often cited, it should be justifiable for AMI
systems to have functionality to support high frequency reads on demand to home networks.
With short-interval meter data available to the home router, and then routed to a Web-based
application, diagnostics and inferential analyses can be performed for a variety of functions. For
example, applications using this data may be able to determine appliance energy use, determine
when heating or air conditioning systems are in need of service, and evaluate options to reduce
costs or improve device performance. For interested consumers, a Web audit on a cell phone
could support the consumer walking around the home, switching loads on and off, and seeing
what the impact of the switched load – costs per hour during peak or off peak periods, carbon
footprint, etc.
The biggest challenge will be to assure that the electric company meter
hanging on the outside wall of buildings will be linked real-time with the consumer-
owned building management system inside the wall. The ubiquitous IP-based
commonality now becoming standard will make that easy to achieve at the right
time. The immediate challenge is to make sure that the utility industry moves away
11-169©2010 ACEEE Summer Study on Energy Efficiency in Buildings
from small-scale proprietary systems and embraces broader, interoperable IP-
based protocols and approaches. 18
Should consumers receive their content from the Public Internet, or the utility private
network? Many pilots have examined the benefits of in-home displays as part of the AMI
network, but it may be more beneficial to tie displays to public networks. With IP connection,
the consumer’s display of choice can be a home computer, or a log-in from a computer at work,
or web-enabled cell phone (i.e. iPhone). Web systems are low cost, flexible, and easily
upgraded, promoting open, non-obsolescent consumer connectivity. Compared with the static
content and quality of meter network-tied in-home displays, utilities or third parties such as
Google or Microsoft can offer a richer, more interesting interface for working with consumers on
the public Internet.
Should Utility content architectures support data exchange with other public Websites?
The open HAN direction discussed above will support a growing set of energy Web content
choices in time. This will include portal content providers such as Google (Powermeter) and
Microsoft (Hohm), as well as the Web control panels for the thermostat and other devices in the
home. In this model, the utility Website provides meter data and potentially collaborative Web
content site with models and functionality that can be drawn upon by the portal or control panel
sites, ideally with a standard data exchange format. The consumer would need a security
password to allow the public portal or control panel Website to connect to his data. This model
is similar in architecture to the download of consumer-intimate financial data from bank websites
to Intuit’s Quicken and TurboTax applications.
Some question exists about whether the utility can refuse to make the consumer energy
data available to other Websites, or be able to charge for the access. To date, most rulings by
state regulators have determined that billing data availability by utilities is consumer-owned and
within their purview to regulate, although the costs to create and support data access can be
passed on to the consumer with a shared rate-based approach or event-specific charge. This
argument is grounded in the view that the consumer information gathered and managed by
utilities is done as a publicly mandated and ratepayer-funded activity. And further, the public
interest in energy efficiency seems that regulators should encourage easy access to the
consumer’s data for the objective of maximizing energy benefits and market innovation.
Conclusions
This paper examined utility vs. public/consumer approaches to various aspects of
consumer-side Smart Grid architecture. And our conclusion is that utilities, regulators, and
policymakers should focus on the consumer-centric architectures for appliance control, public
architecture for AMI communication, and collaborative architecture for content. Some of the
elements are summarized on the following table19:
18 Galvin. (2007). Galvin Electricity Initiative, The Path to Perfect Power: New Technologies Advance Consumer Control.
19 Terry Vardell and Michelle Davis, Duke Energy, Analysis of Smart Energy Now pilot, July 2008.
Consumer Control Utility Control
11-170©2010 ACEEE Summer Study on Energy Efficiency in Buildings
Regarding innovation, our findings to date are that our objectives are best met by an
ecosystem where the utility creates and seeds an effective ecosystem for innovation, which the
marketplace then fulfills. In this model, the marketplace will be the innovator that will find the
strategies that appeal most to the consumer’s motivation. This is accomplished through leverage
of the utility’s metering infrastructure, with appropriate open access and information sharing.
And clearly, the regulatory standards placed and incentives offered to the utility industry will be
the drivers of effective change and advancement.
We need to focus on consumer-controlled architectures for device control: The market
and consumer-led opportunities for innovation are exciting and substantial. We can see
glimpses of ever-improving diagnostic and control methods that will dramatically reduce
our energy requirements. Achieving our energy and greenhouse gas goals may require
that we focus on market-led innovation in how we manage our homes and buildings.
We need to focus on open and public network approaches to communication: Public
network-connected devices are likely to produce more effective energy management,
while utility-specific standards for communication protocols may reduce choice and
innovation.
We need to encourage a broad ecosystem of content providers, including utilities. The
ability of Web software systems to interact with all of the consumer’s technologies and
information may create an ecosystem that supports the intelligent management of
appliances and systems in our buildings, increasingly effective at saving energy and
demand, and adaptive to consumer preferences. The consumer-managed approach and
IP-based communication options recommended above support this direction. For
example, in-home displays if provided by utilities should receive their content from the
Public Internet, not the utility private network. And in time, one would expect consumers
to rely on their own displays, including computers and phones. However, utility AMI
systems that broadcast short-interval reads directly into the home for use by consumers
Control Consumer decisions/control HAN optimized by utility - Consumer
opt in/out
Pricing Time-based - dynamic pricing. Incentive for participating.
HAN Owned/purchased by consumer.
Possible utility incentives Provided by utility/ recovered as part
of regulated filing.
Gateway HAN via internet, mobile phone,
cable Meter via proprietary system.
Data To consumer via internet
To utility via proprietary system
hourly reads once/day; low
bandwidth.
To consumer and utility via
proprietary system
Two way and high bandwidth –
Large amounts of data.
Utility Cost Less Expensive More Expensive
Impacts Creates efficiency and DR. Primary impact is DR.
11-171©2010 ACEEE Summer Study on Energy Efficiency in Buildings
and their web workspaces will support innovation. These short-interval reads on demand
are a key ingredient in measuring differential energy use, supporting the measurement of
load, and cost, of any switchable device in the home.
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... The integration of HAN and NAN on a single system constructs AMI [3]. AMI collects and transmits short interval measured consumption rates between smart meter (SM) and utility and relaying utility price information back to the SM [7,9]. The SG has economic and environmental benefits. ...
... The SG has economic and environmental benefits. In [9], it is reported that 34.5% average electrical consumption saving is achieved in California statewide pilot price in households when cycling appliances, communicated thermostats and display technologies are applied. On the other hand, 12.5 % saving only is achieved by pricing induced behavior. ...
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Electrical peak load demand all over the world is always anticipated to grow, which is challenging electrical utility to supply such increasing load demand in a cost effective, reliable and sustainable manner. Thus, there is a need to study some of load management (LM) techniques employed to minimize energy consumption, reduce consumers' electricity bills and decrease the greenhouse gas emissions responsible for global warming. This paper presents a review of several recent LM strategies and optimization algorithms in different domains. The review is complemented by tabulating several demand side management (DSM) techniques with a specific view on the used demand response (DR) programs, key finding and benefits gained. A special focus is directed to the communication protocols and wireless technology, incorporation of renewable energy resources (RERs), battery energy storage (BES), home appliances scheduling and power quality applications. The outcome of this review reveals that the real time pricing (RTP) is the most efficient price-based mechanism program (PBP), whilst time of use (TOU) is the basic PBP and easiest to implement. Energy efficiency programs have proved the highest influential impact on the annual energy saving over the other dynamic pricing mechanism programs. Through a forecasted proposal of future study, DSM proved tremendous potential annual energy savings, peak demand savings, and investment cost rates within different consumption sectors progressively up to year 2030.
... In (22), N(f) is the noise amplitude at the receiver while the bandwidth, the range of f1 to f2 is bandwidth of the channel [37], [38]. The channel information-carrying capacity defined in (22) could be directly linked to channel's signal to noise ratio by considering that (22) could also be written as [39]: ...
... In (22), N(f) is the noise amplitude at the receiver while the bandwidth, the range of f1 to f2 is bandwidth of the channel [37], [38]. The channel information-carrying capacity defined in (22) could be directly linked to channel's signal to noise ratio by considering that (22) could also be written as [39]: ...
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1 The authors are economists with The Brattle Group located respectively in San Francisco, California and Cambridge, Massachusetts. We are grateful to the analysts who worked on the pricing experiments reviewed in this paper for providing us their reports and presentations. Our research was funded in part by the Edison Electric Institute and the Electric Power Research Institute. Questions can be directed to ahmad.faruqui@brattle.com. 2 HOUSEHOLD RESPONSE TO DYNAMIC PRICING OF ELECTRICITY—A SURVEY OF THE EXPERIMENTAL EVIDENCE Since the energy crisis of 2000-2001 in the western United States, much attention has been given to boosting demand response in electricity markets. One of the best ways to let that happen is to pass through wholesale energy costs to retail customers. This can be accomplished by letting retail prices vary dynamically, either entirely or partly. For the overwhelming majority of customers, that requires a changeout of the metering infrastructure, which may cost as much as $40 billion for the US as a whole. While a good portion of this investment can be covered by savings in distribution system costs, about 40 percent may remain uncovered. This investment gap could be covered by reductions in power generation costs that could be brought about through demand response. Thus, state regulators in many states are investigating whether customers will respond to the higher prices by lowering demand and if so, by how much. To help inform this assessment, we survey the evidence from the 15 most recent experiments with dynamic pricing of electricity. We find conclusive evidence that households (residential customers) respond to higher prices by lowering usage. The magnitude of price response depends on several factors, such as the magnitude of the price increase, the presence of central air conditioning and the availability of enabling technologies such as two-way programmable communicating thermostats and always-on gateway systems that allow multiple end-uses to be controlled remotely. Across the range of experiments studied, time-of-use rates induce a drop in peak demand that ranges between three to six percent and critical-peak pricing tariffs induce a drop in peak demand that ranges between 13 to 20 percent. When accompanied with enabling technologies, the latter set of tariffs lead to a drop in peak demand in the 27 to 44 percent range.
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