Sioshansi F.P. Smart Grid: Integrating Renewable, Distributed & Efficient Energy
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energy usage, but as we've discussed, timing of energy usage
is more important than total consumption from an economic
perspective, and from an environmental perspective in some
circumstances.
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The Illinois Smart Buildings Initiative is
working to connect these piece parts in large buildings in
Illinois.
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In the U.S. Midwest, where the wind is strongest at night, it is possible to
shift load to nighttime hours, reducing both the total energy bill and the
total carbon footprint of a building, while keeping the total consumption
the same.
Currently, ISBI partners from Illinois and Korea are
beginning a feasibility study of opportunities in a set of
candidate buildings and believe that the dynamic efficient
operation of building systems is technically and economically
possible. The biggest questions that the ISBI seeks to answer
relate not to the technological solutions, but to the business
process and interaction questions surrounding the
sustainability of potential business models.
The advanced metering systems being deployed by utilities
are increasing both the granularity of telemetry and control.
As noted in this chapter, increasing telemetry and control
opens a host of new opportunities for demand response.
System operators will have more comfort that changes in
demand will be available when they need them; in effect they
will understand the reliability implications of demand-side
programs, and with this understanding, the system can be
planned in a more efficient manner. This is demonstrated in
Figure 16.4.
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Figure 16.4
Linking demand response opportunities to the granularity of telemetry and
control.
Source: Demand Response Research Center at Lawrence Berkeley National Laboratories, M.A.
Piette, S. Kiliccote, G. Ghatikar, Linking Continuous Energy Management and Open Automated
Demand, November 2008, Presented at the Grid Interop Forum, Atlanta, GA, November 11–13,
2008.
As shown in Figure 16.4 the increasing speed of telemetry
and control opens new and diverse markets for demand
response participation. The deployment of AMI, and the
increasing telemetry and control that it brings, is stimulating a
wave of new emerging technologies, as we have discussed in
this chapter. The current pace of technological advance has
been huge, and the technology that will emerge over the next
few years will be radically different from what's available
today.
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How different? The concept of dynamic efficiency introduced
above is an operational solution that optimizes multiple,
unrelated inputs in real time. As an example, large
commercial and residential buildings today have advanced
control and building automation systems.
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These systems
are typically referred to as building energy management
systems (BEMS). Today, these systems are optimized for
tenant comfort, total energy usage, and in some circumstances
to limit exposure to high prices and participate in demand
response programs offered by utilities and CSPs. But this
optimization is constrained. The constraints come primarily
from a lack of real-time information about the energy usage
of equipment in a building. It's impossible to optimize
real-time energy costs without such information.
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Although many have only limited functionality or have been value
engineered in one way or another, limiting their functionality.
In many circumstances, building operators have established
fixed setpoints for chilled water temperatures, air handling
capacity, and other large building system operational
parameters. These setpoints are based upon the historic
performance of the building and are designed to maintain
tenant comfort. This system functions very well and has
allowed operators to maintain tenant comfort for many years.
However, new predictive methodologies, relying on the
thermal mass of a building are emerging.
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These
methodologies create opportunities to maintain comfort using
dynamic system setpoints.
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Building IQ and Clean Urban Energy are two examples operating as of
the publication date of this book.
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Dynamic efficient operation of building systems has benefits
for building owners/operators in the form of reduced
operating costs, for tenants in the form of reduced energy
costs, and for system operators in terms of more effective
system planning and real-time operation, not to mention
potential ancillary service opportunities that might be
available from taking advantage of the momentum inherent in
building air handling and chilled water circulation in real
time.
More granular communication and control technologies in
large buildings offer a host of potential benefits. We expect
that these potential benefits offer the clearest path for new
business models, and ongoing collaborative efforts like the
ISBI offer the best opportunities to realize these models.
There are several opportunities, for sustainable models, but in
order to realize their true value, suppliers and other actors will
have to find solutions that maximize the available telemetry
and control.
Can We Relate the Model for Big Customers to Small
Customers?
At this point, it's reasonable to ask: how do business models
for commercial buildings relate to business models for
residential customers? In fact, there are direct correlations; the
only difference is the size of the potential load at each site.
The models used to operate large loads are equally applicable
for small loads, as predictive technologies, similar to those
mentioned above, exist for residential air conditioning
systems.
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The only questions are the economics of the
systems and the value of corresponding loads involved.
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See Ecofactor, for example.
It is important to keep an eye on the continued development,
testing, and consumer acceptance of emerging technologies,
but it's equally important to keep an eye on the development
of new business models. Devices create new opportunities for
demand response automation, and as the penetration of AMI
increases and the available economies of scale for automated
response increase, the cost should go down. When combined
with appropriate rate designs, such as time-of-use rates, the
impact of these distributed energy resources on peak loads
could be significant. However, it will take significant
evolution of existing business models to create new
opportunities to deploy new technology and significantly
affect system operation.
Conclusions
In conclusion, the electric grids of the future will likely look
dramatically different from those that exist today. As
technology improves and the granularity of communications
and control increases, more opportunities for true
demand-participation will arise. A truly dynamic demand side
is possible with today's technology. However, for this to
happen, both customers and system operators will need to
perceive and be comfortable with the benefits of these
technologies.
Admittedly, this will not occur overnight, and the scale and
scope of such a change are not lost on the authors. It will take
many years for the industry to be truly transformed by
emerging smart technologies on the customer side of the
meter. Until that time, traditional demand response and
energy efficiency program models will continue to exist and
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become profitable distribution mechanisms for emerging
smart technologies. However, in the long term, customer
engagement models for energy efficiency and demand
response will look more like smart phone apps and less like
the cumbersome regulated models that exist today.
There are a multitude of new ideas emerging that will allow
customers to better manage consumption both actively and
passively. In the future, a combination of direct feedback and
prices-to-devices technologies will likely meet varying
customer preferences and needs. Although it's not yet clear
how these technologies will find their way to customers, the
potential of these technologies is expected to be unlocked in
the coming years. As customers become more aware of new
electricity usage management capabilities and as technology
costs decline, markets will grow and benefits will materialize.
Although it's difficult to predict that pace at which these
markets will develop, one thing is abundantly clear: to
maximize the potential created by utility smart meter
investments, we have to go beyond the meter.
References
[1] S. Darby, Making it Obvious: Designing Feedback into
Energy Consumption, Environmental Change Institute,
University of Oxford, 2000.
[2] A. Faruqui, S. Sergici, A. Sharif, The Impact of
Informational Feedback on Energy Consumption—A
Survey of the Experimental Evidence, 2010.
http://www.brattle.com/_documents/uploadlibrary/
upload772.pdf (accessed 23.05.11).
[3] A. Faruqui, S. Sergici, Household Response to Dynamic
Pricing: A Survey of Seventeen Pricing Experiments,
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Social Science Research Network Working Paper,
November 13, 2008.
807
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Chapter 17. Demand Response Participation
in Organized Electricity Markets
A PJM Case Study
Susan Covino, Peter Langbein and Paul Sotkiewicz
Chapter Outline
Introduction 422
Entities That Participate as DR in PJM's Markets 425
Demand Response Participation in the Capacity Market
426
Resource Adequacy and the Role of DR 426
Brief History Before RPM 427
RPM Capacity Market 428
Market Results 430
Expansion of DR Products to Ensure Reliability 431
DR Participation in the Energy Market (Day-Ahead
and Real-Time) 433
Energy Market Benefits of Integrating Economic Load
Response 434
History 434
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Market Mechanics 436
Measuring Load Reductions 438
Settlements in the Energy Market 438
Market Results 439
Emergency DR Participation in the Energy Market 442
Order 745, Demand Response Compensation in
Organized Wholesale Energy Markets, Issued 3/15/11
443
Resolving Early Issues with CBL Estimation 443
DR Participation in Ancillary Service Markets 444
Synchronized Reserve Market 444
Regulation Market 446
Potential Financial Benefits and Market Results 446
Administration of DR in PJM's Markets 448
DR Participation Going Forward: Current Issues
Related to Demand Response 449
Price-Responsive Demand 449
Customer Baseline Calculation Revisited 450
Dispatch of DR with a Scalpel Rather than a
Sledgehammer 451
Demand response participation in PJM's markets has been enabled by early vintage smart grid
technologies such as interval metering, which facilitates the necessary measurement and verification of
demand reductions in conjunction with market design enhancements that monetize the value demand
response provided Demand response may participate in PJM's Energy Markets, the PJM RPM
Capacity Market, PJM's Synchronized Reserve Market, or the PJM Regulation Market The interval
meter requirement has tended to be less of a challenge for very large consumers in states with
“restructured” retail markets than for consumers located in states with traditional fully integrated and
fully regulated retail markets * Since 2002 demand response participation has grown significantly such
that its participation in the RPM Capacity Market accounts for about 7% of PJM's all-time system peak
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