Sioshansi F.P. Smart Grid: Integrating Renewable, Distributed & Efficient Energy
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Monitoring-based commissioning refers to the combination of
electronic data collection, sophisticated data filtering, and
analysis with a comprehensive facility audit. The MBCx
Program helps a facility quantify the energy savings from
such measures as:
• Detecting faults
• Optimizing schedules
• Adjusting temperature set-points
• Reducing overcooling
• Participating in demand response programs
The MBCx program was designed for large commercial
customers with greater than 100,000 square feet of
conditioned space or an electric demand of greater than 500
kW. To participate effectively customers must have a
BacNET/IP-enabled building management system (BMS),
BMS (building management system) metering for utility
service point of entry, BMS control and monitoring points for
environmental comfort and operating systems, and sufficient
IT capacity to support export of energy usage data to
third-party firms. Typical program services include:
• Integration of BMS to third-party analysis application
• Comprehensive facility audit and report
• 12 monthly reports that track performance and contain EE
• EE measurement implementation assistance
• Online access to detailed, real-time facility energy usage.
Customers can receive incentive payments for up to 50% of
project costs at $0.09/kWh, $1.00/therm, and $100/peak kW.
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What is interesting for the purposes of this chapter is that this
program reads like a smart grid designer's dream: AMI-based,
sophisticated interaction with customers' building automation
systems, which allows diagnosis, efficiency improvement,
and demand response down to the device level. And yet there
was virtually no controversy at the regulatory level on the
approval or rollout of this program. It is also interesting that
one of the implementing firms, EnerNOC, is better known as
a curtailment service provider (CSP), whose business model
typically focuses more on wholesale-market demand response
programs. But because of the sophistication of its data
analytics and other capabilities, EnerNOC is able to
seamlessly provide a range of energy efficiency and demand
response assistance within a single program design. It is also
important to note that PG&E laid a critical foundation for
MBCx and other smart grid applications through its early
work on automated electronic data exchange. As a leader in
the ENERGY STAR Buildings program, PG&E was one of
the first utilities to implement the Automated Benchmarking
System (ABS) software solution, which is connected to the
EPA Portfolio Manager software platform. By providing
energy use data electronically, rapidly, and for free, ABS can
enable a whole host of customer information-based program
solutions.
This case points to the enormous potential for smart grid
deployment, and the combined realization of energy
efficiency and demand response goals in a single integrated
program framework. While most of the literature focuses on
the challenges and opportunities in deploying smart grid
technology to a fundamentally low-tech, mass-market
audience, programs like MBCx (and there are still very few
like it) are quietly showing the way forward, working with
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larger customers who are more tech-savvy and have the
digital metering and building automation systems needed to
implement sophisticated approaches like this. This suggests
that smart grid deployment should start with larger customers
first, with mass-market deployment to residential and small
commercial customer classes phased in later.
These three case studies imply a number of potential lessons
for smart grid deployment:
• Customer benefits can be demonstrated without AMI.
While this may sound threatening to utilities seeking to
deploy AMI as a core part of their smart grid strategy, it
also suggests that demonstrating customer benefits in
feedback and behavior change, as the Cape Light pilot
does, can be achieved relatively quickly and at lower cost
than full AMI deployment. Done strategically, as part of a
concerted set of pilots, studies, and other activities, such
customer-side initiatives can help make the case for wide
AMI and other smart grid deployments.
• Customers prefer to be in charge. The Cape Light
project demonstrates the advantages of giving customers
more control of the process—letting them choose their
energy savings goals, the energy efficiency measures they
want to take on, etc.
• Use pilots to build the cost-effectiveness case. A
limitation of the Cape Light evaluation was that it was not
designed to assess overall benefits and costs. That was not
its core design, but other utilities pursuing such pilots
would be well advised to try to capture and quantify
energy, demand, and other benefits, and to document costs.
While some smart grid deployments will only be fully cost
effective at scale when all customers are involved,
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collecting and documenting such data in pilots are
necessary parts of the process of building the case.
• Engage stakeholders proactively. The PowerCentsDC
™
program showed how to gain support from potential
opponents by engaging consumer advocates, regulators,
and labor interests in the program's design and deployment.
While this has not yet translated into final approval for
systemwide AMI and dynamic pricing deployment, it can
only help with customer acceptance as well as regulatory
approval.
• Give customers enabling technologies.
PowerCentsDC
™
included smart thermostats as a customer
option for supporting their response to price signals. Not
only does this dramatically increase peak demand
reductions, and likely energy savings (though energy
savings were not measured), it also gives customers
concrete tools to deal with dynamic pricing, which was one
of the objections Maryland OPC raised in the BGE case.
Such technologies thus provide a two-pronged
benefit—increased impacts and greater regulatory approval
chances.
• Segment customers strategically. If one were to read
some of the negative press about residential AMI
deployment in places like Illinois or Colorado, one could
get the impression that smart grid deployment faces big
challenges. But the PG&E MBCx program tells a different
story, demonstrating most if not all of what smart grid
designers dream of, by focusing on the customer segment
that is most amenable to the technology and information
solutions that smart grid enables. Large commercial and
institutional customers are ripe for smart grid solutions, and
in many areas comprise a large fraction of electricity load.
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Even within residential and small business customer
classes, there are numerous ways to segment customers
from program design and marketing standpoints. For
example:
• The “set and forget” strategies described in other
chapters will be most appealing to a certain segment of
customers, who want to save money but have little
interest or skill for ongoing engagement. They might
agree to a simple thermostat/CPP program that they sign
up for once and hopefully never notice.
• Another segment, perhaps that targeted by the Cape
Light project, would be receptive to an “continuous
improvement” approach, involving more choices and
more ongoing, active involvement in learning how to
manage home energy use.
• It's also important to recognize that some customers
may never want to engage in smart grid matters. They
may be suspicious of utility motives, resistant to
technology, or otherwise disinterested. It may be
strategic to allow for some fraction of customers to be
“left alone,” other than perhaps AMI installation as part
of a rollout that the majority of customers come to
support.
Filling the Gaps: What Smart Grid Designers
Should Focus on to Better Document Customer
Benefits
Drawing on the field experience with customer acceptance
and regulatory approval with smart grid customer offerings
across the United States, this section describes the data
collection and the program features that should be part of
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smart grid customer offerings in order to better document and
deliver the full range of customer benefits. Filling these gaps
will be important in gaining the customer acceptance and
regulatory approval that have been lagging in many service
areas. These gaps are summarized as follows:
• Measure annual energy savings. Far too few smart grid
demonstrations and pilots have been able to generate robust
data on customer energy savings over annual cycles and
longer. Most of these efforts have focused on demand
response, dynamic pricing, and related topics.
Appropriately, the focus of such programs is on short-term
demand impacts, measured as kilowatts of power capacity
coincident with the utility system peak. Energy savings
measured over a year's period, while not the primary
concern of DR and dynamic pricing, are paramount as
metrics for the success of energy efficiency programs.
There is thus a need for more robust data on the energy
AND demand impacts of smart-grid-based customer
offerings. This would help utilities, regulators, and other
parties develop fuller estimates of the benefits that smart
grid technologies can offer.
• Give customers feedback they can use. Customer
feedback has been shown in many of the programs
described above to be effective in producing both peak
reductions and longer-term energy savings. But the
information has to be designed and delivered to fit the
specific needs of customer segments. For a large
commercial customer participating in the PG&E MBCx
program, data need to be very granular and specific to
isolate efficiency and peak demand options. For a typical
residential customer, an IHD combined with a user-friendly
web portal and bill disaggregation software can point to
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energy and peak reduction options in a much simpler
fashion.
• Give customers control options they will use.
Residential programs can suffer from overkill, promising
too many whiz-bang control features. Many customers will
only use a one-time “set and forget” option, while others
may be interested in managing home electronics and major
appliances as well as heating, cooling, and hot water.
Customer segmentation and program design should
accommodate these differences. It may require only two to
three differentiated offerings to capture these differences
and gain wider customer acceptance and program impacts.
However, even if the next generation of customer offerings is
developed and perfected to the point of being ready for mass
market deployment, utilities and other parties will need to
develop program logic models that are persuasive to
regulators. This is a critical step: to date, program logic
models have had to be relatively simple, with hard-and-fast
logic that is easily understood. Such program models
typically follow the physical-technological-economic-model
(PTEM) structure, in which the program is designed to install
or replace a physical device containing a specific technology,
offers an economic incentive to the customer for purchasing/
installing the device, on the basis that so doing is cost
effective under defined economic tests, and that in so doing
customers are reliably following a rational pattern of
economic behavior.
However, smart grid customer offerings typically depend on
customer behavioral responses to price signals and/or usage
feedback. Program designers and regulators alike need to
develop program models that will allow for robust
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measurement and evaluation that will pass regulatory review.
Substantial work is underway in this regard, and smart grid
advocates need to become versed in this emerging area of
inquiry [14] and [15].
Conclusions
This chapter has sought to show that smart grid technologies
can become part of customer offerings that save energy,
reduce peak demand, and gain customer acceptance in the
market as well as regulatory approval. It has also sought to
identify the key challenges that these programs face, in terms
of both program design and regulatory review. Based on the
field experience we have reviewed, we suggest that a
successful smart grid deployment strategy must be
comprehensive and long term, allowing for stakeholder
engagement, careful documentation of benefits, and a staged
deployment approach. We suggest the following principles as
guidance for smart grid developers in designing future
programs for the best chance of success:
• Demonstrate benefits before seeking to recover costs.
Use pilots to demonstrate AMI and other smart grid
benefits, including a variety of customer offerings, such as
dynamic pricing, advanced usage information and
feedback, and device control options. Document results,
and compile results from other smart grid programs, as part
of any proposal for regulatory approval or cost recovery.
• Segment customer markets. Start with the large C/I
customer classes, where resistance to AMI, dynamic
pricing, and active customer-side load control is much
lower than for residential customers, and where consumer
advocate intervenors are less likely to create regulatory
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opposition. In some service areas, large C/I customers can
provide a large share if not a majority of the potential
benefits of smart grid deployment.
• Share risks and costs. The BGE/Maryland PSC example
illustrates that in many states, proposals that ask for
immediate cost recovery from ratepayers are likely to meet
stiff opposition. Deferring cost recovery to after
installation, and including some shareholder risk and cost
sharing, can help improve the chances of regulatory
approval.
• Put the customer in charge. Give customers choices,
including setting their own savings goals, choosing their
own preferred usage management strategies, and setting
their own preferences for receiving information and
feedback. Provide realistic enabling technologies
appropriate to each customer segment to allow them to
respond to price signals and usage feedback.
• Be careful about mandatory dynamic pricing. Many
state regulators have resisted imposing mandatory
critical-peak pricing or other forms of dynamic pricing,
especially on residential and small business customers.
• Consider the alternatives. Consumer advocates have
pointed out, correctly, that some of the benefits of smart
grid technologies do not require AMI or other core
technologies. Deployment proposals must carefully address
how the proposed plan provides sufficient value to
overcome such objections and, depending on the
jurisdiction, may require accommodation to include such
lower-tech, lower-cost options.
Applying these principles thoughtfully in the context of the
specific customer markets and regulatory environment each
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smart grid developer faces can help America realize the
potential for energy efficiency, demand response, and other
benefits that smart grid technology promises.
References
[1] National Action Plan for Energy Efficiency, Coordination
of Energy Efficiency and Demand Response, Prepared by
Charles Goldman (Lawrence Berkeley National
Laboratory), Michael Reid (E Source), Roger Levy, and
Alison Silversteinwww.epa.gov/eeactionplan (2010).
[2] North American Electric Reliability Council, Demand
Response Availability Data System (DADS): Phase I and
II. North American Electric Reliability Corporation,
Washigton, DC (2009).
[3] Maryland Public Service Commission, Case No. 9208: In
the Matter of the Application of Baltimore Gas and
Electric Company for Authorization to Deploy a Smart
Grid Initiative and to Establish a Surcharge for the
Recovery of Cost, Order No. 83410 and Order No.
83531, 2010 (accessed 19.08.11).
[4] Carmody, P., Dumb Policies and Smart Grids: A
Consumer Perspective, Presentation to University of
Florida – Public Utility Research Center, Office of
Maryland People's Counsel, Washington, DC (February
3, 2011).
[5] Hornby, R.; et al., Advanced Metering
Infrastructure—Implications for Residential Customers
in New Jersey, Synapse Energy Economics, Inc.:
Prepared for the New Jersey Department of Ratepayer
Advocate, Division of Rate Counsel, Trenton, NJ. (2008).
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