Sioshansi F.P. Smart Grid: Integrating Renewable, Distributed & Efficient Energy
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[9] Newell, S.; Hajos, A., The Brattle Group. Presentation to
the Northeast Energy and Commerce Association's
Energy Efficiency and Demand Response Conference.
Key Issues for Demand Response (October 21, 2010).
[10] AWEA, Wind Energy Facts: Texas. American Wind
Energy Association. http://www.awea.org/learnabout/
publications/upload/1Q-11-Texas.pdf (accessed
24.05.11).
[11] ERCOT, ERCOT Operations Report on the EECP Event
of Electricity Reliability Council of Texas (February 26,
2008).
[12] BPA, 2009 BPA Facts. http://www.bpa.gov/corporate/
about_BPA/Facts/FactDocs/BPA_Facts_2009.pdf
(accessed 25.05.11).
[13] BPA, BPA's Interim Environmental Redispatch and
Negative Pricing Policies: Administrator's Final Record
of Decision. Bonneville Power Authority, May 2011.
[14] Oren, S.S.; Smith, S.A., Design and management of
curtailable electricity service to reduce annual peaks, OR
Practice 40 (2) (1992) 213–228.
[15] California Public Utilities Commission. Appendix A of
Rulemaking 07-01-041 Straw Proposals for Load Impact
Estimation and Cost Effectiveness Evaluation of
Southern California Edison Company, San Diego Gas &
Electric Company, and Pacific Gas and Electric
Company filed on July 16, 2007. CA CPUC,
R.07-01-041, http://docs.cpuc.ca.gov/efile/REPORT/
72728.pdf (accessed 30.03.11).
[16] Katzenstein, W.; Apt, J., Air emissions due to wind and
solar power, Environ. Sci. and Technology 43 (2009)
253–258.
531
[17] Denny, E.; O’Malley, M., Wind generation, power
system operation, and emissions reduction, IEEE Trans.
Power Syst. 21 (2006) 341–347.
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Chapter 11. Software Infrastructure and the
Smart Grid
Chris King and James Strapp
Chapter Outline
Introduction 259
Smart Grid IT Challenges 262
Smart Grid Data Reliability 264
Data Accuracy 267
Data Systems of Record 269
Communications Management 273
Integration of Software Applications 276
Essential Smart Grid Software Platform 277
Smart Application Integration Platform 277
Issues Associated with Other IT Architectures 278
Multiple Operating Companies/Multiple Utilities 279
System Interfaces and Interoperability 279
Smart Grid Applications 280
Meter Data Management 281
Dynamic Pricing Rates 282
Net Metering 283
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Case Studies 284
Ontario MDM/R 285
Smart Meter Texas 286
Conclusions 287
At first glance, implementing a smart grid seems an exercise in acquiring and installing equipment in
homes, businesses, distribution circuits, and substations However, the information technology
(IT)—data centers, communications networks, software platforms, and applications—is equally
essential to achieving smart grid benefits The authors focus on two universal requirements for success:
managing large imperfect data streams and integrating multitudinous communicating smart grid
devices with legacy and new software applications Success requires overcoming IT silos built around
individual applications and supporting diverse devices from smart meters to smart appliances The
authors describe case studies that illustrate best practices, including flexibility to handle new
technologies, new applications, and new standards
Smart grid, smart software, smart grid IT
Introduction
The smart grid promises many benefits to utilities, consumers,
and society—as much as $131 billion per year for the United
States.
1
As described in other chapters of this book, these
benefits include utility operating efficiencies, better use of
existing grid assets, enhanced energy efficiency, greater
reliability, reduced peak demand, and integration of
distributed renewable energy resources. Achieving these
benefits requires investing in hardware such as smart meters,
communication networks, line sensors and controllers,
automated switchgear, capacitor bank controllers, in-home
devices, and other equipment. The amount is significant, with
estimates from ranging from a “bare bones” approach costing
$50 billion to as high as $476 billion for 150 million electric
customers in the United States
2
—and an order of magnitude
higher to implement smart grid for all 1.7 billion electric
meters globally.
3
By way of progress, U.S. installations
surpassed 20 million meters in May 2011, with nearly 50
million committed by 2015
4
; global spending on smart grids
is expected to reach $46 billion by 2015.
5
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1
McKinsey & Co., McKinsey on Smart Grid, Summer 2010, at 6.
2
EPRI, Estimating the Costs and Benefits of the Smart Grid, March 2011.
3
ABS Energy Research, Electricity Meter Report, June 2009.
4
Chris King, U.S.: 20 million smart meters Now Installed, May 17, 2011.
Available at http://www.emeter.com/smart-grid-watch/2011/
us-20-million-smart-meters-now-installed/.
5
ABI Research, Smart Grid Applications: Smart Meters, Demand
Response, and Distributed Generation, Research Report, July 2010.
Nowhere are \ the potential benefits greater and the profile
higher than with those smart grid applications that have a
direct impact on the energy customer. The smart grid
technologies associated with the home or business include
smart meters, home energy devices connected through a
so-called home area network or HAN, and smart appliances.
Delivering smart grid application functionality requires a
complex integration of these millions of devices in
environments that challenge communications technologies.
More than the other smart grid technologies, these devices
have a direct daily impact on energy consumers’ lives and all
the associated implications. This chapter is focused on the
software platform necessary for successful deployment and
operation of smart grid technologies associated with the
consumer's premises.
Just as a computer is useless without its operating system
software and software applications, smart grid capital
investment can deliver little of the desired benefits without
the necessary accompanying information technology (IT)
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systems. And just as with computers, the IT systems include
both software platforms—analogous to the PC's operating
system—and software applications.
Smart grid software platforms are the underlying elements
that support applications (Figure 11.1). For example, a
software platform is needed within the utility back office to
link individual applications with smart grid communications
networks. This allows multiple applications to use the same
network, such as having the billing system receive usage data
and the outage management system receive outage alarms
from the same smart meters and over the same smart meter
communications network. Another example is in a home or
building, where the software platform underlying the HAN
enables communications between devices, further described
in Chapter 15.
Figure 11.1
Software platform links smart grid devices with utility legacy systems and
provides a platform on which to develop new software applications.
Source: eMeter Strategic Consulting, Smart Meter Best Practices Webinar, April 22, 2010.
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On the applications side, a plethora of product offerings has
emerged. Many of these are in the utility back office, such as
meter data management (MDM) and demand response
management (DRM). Such applications process data provided
by smart meters, sensors, or other devices and produce useful
outputs for utility business processes. For example, the MDM
performs validation, editing, and estimation (VEE) on usage
data received from smart meters, making the results available
to the billing system as needed to generate customer bills.
Many other applications are consumer-oriented, such as
consumer engagement websites where end-users can view
their consumption data online or subscribe to weekly or
monthly emails to have the usage reports “pushed” to them.
Implementing the IT systems that go along with the smart
grid may seem daunting to utilities—and not all of the early
implementations have gone smoothly—but there are many
cases that demonstrate best practices for success. Building on
these successes, exemplary utilities are actively beginning to
achieve the desired benefits of smart meters and smart grids.
Utility projects highlighted here are in Texas and Ontario,
Canada. The authors have worked closely with the project
principals in both cases and have detailed knowledge. These
two case studies illustrate the approaches of a distribution
utility in a deregulated retail market, with a mixture of IT
responsibilities between the utility and centralized systems
serving multiple utilities. The two cases are analogous to, but
more challenging than, cases of integrating systems serving
multiple departments within a single vertically integrated
utility. In other words, the chosen cases illustrate the same
principles and needs of a vertically integrated utility but with
additional complexity. In addition, many regulators require
that utilities interface with third parties to share customer
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usage and other data, in cases where customers have
authorized the sharing of their data.
6
6
California Public Utilities Commission. D.11-07-056. July 28, 2011.
This chapter is organized into four sections. “Introduction”
reviews the goals of the IT infrastructure included in a smart
grid deployment. These include delivering utility operating
benefits, grid efficiencies, and consumer benefits.
Importantly, they also include “future-proofing” to
accommodate new technologies and new regulatory policies,
both of which continue to evolve more and more rapidly.
“Smart Grid IT Challenges” describes the IT challenges faced
by utilities implementing smart grid projects. These
challenges include the handling of imperfect data and
communications—think dropped cell phone calls or corrupt
data files on a computer hard drive, which are not that
common, but do happen regularly—sharing of the data and
communications by multiple applications, and integration of
all of the software and hardware elements. “Essential Smart
Grid Software Platform” describes the essential software
platforms that provide the underlying infrastructure to realize
desired smart grid functionality for the premises. This section
presents a data integration platform and key interfaces, as
well as the standards associated with those interfaces.
Specific examples are smart grid Interoperability Panel
(SGIP) Priority Action Plan (PAP) 10 for the data model for
providing energy information to consumers and Smart Energy
Profile, associated with ZigBee, for sending and receiving
data and control signals between smart meters and smart
appliances, thermostats, and other devices. “Smart Grid
Applications” elucidates some of the major software
applications that provide the smart grid functions for
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customers, such as billing of dynamic pricing rates, meter
data management, net metering, consumer engagement,
outage management, HAN management, and demand
response management.
Throughout the chapter, examples from the sophisticated and
mature smart grid programs in two jurisdictions, Texas and
Ontario, are used to highlight and explain the concepts
discussed. Both of these programs distribute IT
responsibilities between competitive energy retailers,
electricity distributors, and central market players in an
architecture that illustrates the IT complexities involved in
smart grid deployments. Sidebars provide background
information on the history, structure, and scopes of the smart
grid in both jurisdictions. The chapter ends with our findings
and conclusions.
Smart Grid IT Challenges
Investing in the smart grid may be one of the largest capital
investments that a distribution utility makes. The associated
IT infrastructure represents a new breed of enterprise
information system that requires comprehensive integration
and management tools—a smart network application
platform. Such a platform supports basic meter data
management (MDM) functionality but many more
capabilities as well.
7
These additional capabilities are
essential in minimizing the capital and operating costs of the
smart grid, as well as maximizing business benefits
realization.
7
Meter data management refers to processing of smart meter data for use
in billing. This includes receiving the data from the head end of a smart
meter network; performing validation, editing, and estimation (VEE);
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