Case Studies – UtilitesDB

The New Corporate Web Site

A security software development start-up had an innovative software product but a limited budget for launching and promoting the offering. The company used a combination of an event marketing strategy and social media to take its first product to market. Over the course of several weeks, the company not only launched its product but also won an industry-recognized award. The firm engaged R2integrated (R2i) to develop a series of product-centric microsites based on social media campaigns.

TAKING A NEW PRODUCT TO THE MARKET

Since the firm was a start-up, its executives were watchful of the budget given the costs of launching a company. For this reason, the company used open-source software and lightweight social media tools to support its marketing efforts. An open-source content management system supported the company’s marketing initiatives, while the popular blogging software WordPress allowed the firm to post relevant content quickly.

As part of the company’s event-driven marketing strategy, it used a series of industry conferences to launch its first product, a software tool designed to recognize network intrusions before they happened. The firm employed a variety of social media to not only document its product-related events but also to interact and engage with potential prospects online.

The firm decided to launch its fledgling product at the industry’s leading conference and trade show. For several weeks leading up to the event, it accelerated its use of social media tools. Executives wrote several blog posts per day, posted multiple “tweats” and even published product demonstrations to Flickr.

THE PROBLEM WITH SOCIAL MEDIA CAMPAIGNS

The firm realized that its Web-based marketing efforts existed both on and off the corporate website. The website, however, included little mention of the company’s activities on Blip.TV, Flickr or Twitter. The first problem with this approach to social media was that off-site activities had low visibility for visitors on the corporate website. How would a website visitor know, for example, that the firm’s team was hanging out on Twitter or had interesting interviews on Blip.TV? The second problem the company faced was that its corporate website was becoming less relevant because its marketing content was formal and static rather than social and dynamic.

THE SOLUTION

A combination of RSS feeds and widgets solved both of the above-described problems. R2i was able to “widgetize” the content from its blogs, Twitter and Flickr, and as a result, this content was aggregated into one place on the corporate website. These pages, known as “learning centers,” gave prospective customers a unique look at the company and featured a range of content that included white papers, analyst reports, “webinars” and social media.

For example, when the firm gave a product demonstration at an industry conference, the event sponsor provided all attendees with a video of the performance. Immediately after the video became available, R2i was able to embed the video via a widget directly into its website. When the team arrived back home, it used the same widget to post the video on its blogs.

Widgets also solved website relevancy issues in that the learning centers were able to feature a variety of new content. For example, visitors to the website were able to scan Twitter messages posted from the conference room floor. Other content included blog posts that were “live blogged” and Flickr photos of the firm’s employees socializing with various groups from their booth. For visitors to the corporate website, the learning centers provided an immersive experience.

SOCIAL MEDIA RESULTS

After attending several trade shows and creating three purpose-built learning centers, several benefits have emerged for the firm. The website became more relevant at the same time that it directed visitors to a variety of off-site content items and experiences.

Since many content items were posted live from industry events, the learning centers provided website visitors with a unique vantage point, giving them a direct line of sight into the process of launching an award-winning product as well as an opportunity to learn about the product itself through a range of content types and file formats. Visitors to the learning centers were able to consume formal content items like analyst reports that shared the page with more conversational items like Twitter “tweats.” Even a low-tech video (described as “gorilla cool”) joined the company’s arsenal of marketing collateral.

An Australian Approach to Energy Innovation and Collaboration

Just as global demand for energy is
steadily increasing, so too, are the
recognized costs of power generation.
A recent report about the possibility
of creating a low-emissions future by Australia’s
Treasury noted that electricity production
currently accounts for 34 percent
of the nation’s net greenhouse gas emissions,
and that it was the fastest-growing
contributor to greenhouse gas emissions
over the period from 1990 to 2006 [1].

This growing realization of the true
cost of energy production will be brought
into stark relief, with the likely implementation
of a national emissions trading
scheme in 2010.

Australia’s energy producers are entering
an era of great change, with increasing
pressure to drive efficiencies in both the
supply and demand sides of their businesses.
These pressures manifest themselves
in the operation of energy and utilities
organizations in three basic needs:

To tighten the focus on delivering value,
within the paradigm of achieving more
with less, and while concentrating on
their core business;
To exploit the opportunities of an industry
in transformation, and to build new
capabilities; and
To act with speed in terms of driving
leadership, setting the agenda, managing
change and leveraging experience
– all while managing risk.

The net effect of the various government
initiatives and mandates around energy
production is to drive energy and utility
companies to deliver power more responsibly
and efficiently. The most obvious
evidence of this reaction is the development
of advanced metering infrastructure
(AMI) and intelligent network (IN) programs
across Australia. Yet a more fundamental
change is also starting to emerge – a
change that is leading companies to work
more openly and collaboratively toward a
smarter energy value chain.

This renewed sense of purpose gives
energy and utilities organizations an opportunity
to think and act in dynamic new ways
as they re-engineer their operations to:

Transform the grid from a rigid, analog
system to a responsive and automated
energy delivery system by driving operational
excellence;
Empower consumers and improve their
satisfaction by providing them with near
real-time, detailed information about
their energy usage; and
Reduce greenhouse gas emissions to
meet or exceed environmental regulatory
requirements while maintaining a
sufficient, cost-effective power supply.

A Global Issue

In Australia, Country Energy, a leading
essential services corporation owned by
the New South Wales Government, is leading
the move to change not just its own
organization, but the entire electricity
supply industry.

With the strength of around 4,000
employees, and Australia’s largest power
supply network covering 95 percent of
New South Wales’ landmass, Country
Energy recognized the scale and scope of
this industry challenge meant no single
player could find all the answers by himself.

A Powerful Alliance

Formed by IBM, the Global Intelligent
Utilities Network (IUN) Coalition represents
a focused and collaborative effort
to address the many economic, social and
environmental pressures facing these
organizations as they shape, accelerate
and share in the development of the
smart grid. Counting just one representative
organization from each major urban
electricity market, the coalition will collaborate
to enable the rapid development of solutions, adoption of open industry-based
standards, and creation of informed
policy and regulation.

Not only does the coalition believe
these three streams of collaboration will
help drive the adoption of the IUN, or
smart grid, in markets across the planet,
but the sharing of best practice information
and creation of a unified direction for
the industry will help reduce regulatory,
financial, market and implementation
risks. And, like all productive collaborative
relationships, the rewards for individual
members are likely to become amplified as
the group grows, learns and shares.

Global Coalition, Local Results

As Australia’s only member of the coalition,
Country Energy has been quick to
capitalize on – and contribute to – the
benefits of the global knowledge base,
adapting the learnings from overseas
operators in both developed and emerging
markets, and applying them to the unique
challenges of a huge landmass with a
decentralized population.

From its base in a nation rich in natural
resources, the Australian energy and utilities
industry is quickly moving to adapt to
the emergence of a carbon economy.

One of Country Energy’s key projects in
this realm is the development of its own
Intelligent Network (IN), providing the
platform for developing its future network
strategy, incorporating distributed generation
and storage, as well as enabling consumer
interaction through the provision of
real-time information on energy consumption,
cost and greenhouse footprint.

Community Collaboration

Keen to understand how the IN will work
for customers and its own employees,
Country Energy is moving the smart grid
off the page and into real life.

Designed to demonstrate, measure and
evaluate the technical and commercial
viability of IN initiatives, two communities
have been identified by Country Energy,
with the primary goal of learning from
both the suitability of the solutions implemented
and the operational partnership
models by which they will be delivered.

These two IN communities are intended
to provide a live research environment
to evaluate current understandings and
technologies, and will include functionality
across nine areas, including smart meters,
electrical network monitoring and control,
and consumer interaction and response.

Demonstrating the Future

In preparing to put the digital age to
work, and to practically demonstrate to
stakeholders what an IN will deliver, Country
Energy has developed Australia’s first
comprehensive IN Research and Demonstration
Centre near Canberra.

This interactive centre shows what the power network of the not-too-distant
future will look like and how it will
change the way power is delivered, managed
and used.

The centre includes a residential setting
to demonstrate the “smart home of
the future,” while giving visitors a preview
of an energy network that automatically
detects where a power interruption
occurs, providing up-to-date information
to network operators and field crews.

An initiative as far-reaching as the IN will
rely on human understanding as much as it
does on technology and infrastructure.

Regional Delivery Model

In addition to the coalition, IBM and
Country Energy developed and implemented
an innovative new business model
to transform Country Energy’s application
development and support capability. In
2008, Country Energy signed a four-year
agreement with IBM to establish a regional development centre, located in
the city of Bathurst.

The centre is designed to help maximize
cost efficiencies, accelerate the pace of
skills transfer through close links with the
local higher-education facility, Charles
Sturt University, and support Country
Energy’s application needs as it moves
forward on its IN journey. The centre is also
providing services to other IBM clients.

Through the centre, Country Energy
aims to improve service levels and innovations
delivered to its business via skills
transfer to Country Energy. The outcome
also allows Country Energy to meet its
commitment to support regional areas
and offers a viable alternative to global
delivery models.

Looking to the Future

In many ways, the energy and utilities
industry has come to symbolize the crossroads
that many of the planet’s systems find themselves at this moment in time:
legacy systems are operating in an economic
and environmental ecosystem that
is simply unable to sustain current levels –
let alone, the projected demands of global
growth.

Yet help is at hand, infusing these systems
with the instrumentation to extract
real-time data from every point in the
value chain, interconnecting these points
to allow the constant, back-and-forward
fl ow of information, and finally, employing
the power of analytics to give these systems
the gift of intelligence.

In real terms, IBM and Country Energy
are harnessing the depth of knowledge
and expertise of the Global IUN Coalition,
collaborating to help change the way the
industry operates at a fundamental level
in order to create an IN. This new smart
grid will operate as an automated energy
delivery system, empowering consumers
and improving their satisfaction by providing
them with near real-time, detailed
information about their energy usage.

And for the planet that these consumers
– and billions of others – rely upon,
Country Energy’s efforts will help reduce
greenhouse gas emissions while maintaining
that most basic building block of
human development: safe, dependable,
available and cost-effective power.

Reference

1 Commonwealth of Australia. Commonwealth
Treasury. Australia’s Low Pollution
Future: The Economics of Climate
Change Mitigation. 30 October 2008.

Author’s Note: This customer story is based
on information provided by Country Energy
and illustrates how one organization uses IBM
products. Many factors have contributed to
the results and benefits described. IBM does
not guarantee comparable results elsewhere.

The GridWise Olympic Peninsula Project

The Olympic Peninsula Project consisted of a field demonstration and test of advanced price signal-based control of distributed energy resources (DERs). Sponsored by the U.S. Department of Energy (DOE) and led by the Pacific Northwest National Laboratory, the project was part of the Pacific Northwest Grid- Wise Testbed Demonstration.

Other participating organizations included the Bonneville Power Administration, Public Utility District (PUD) #1 of Clallam County, the City of Port Angeles, Portland General Electric, IBM’s T.J. Watson Research Center, Whirlpool and Invensys Controls. The main objective of the project was to convert normally passive loads and idle distributed generation into actively participating resources optimally coordinated in near real time to reduce stress on the local distribution system.

Planning began in late 2004, and the bulk of the development work took place in 2005. By late 2005, equipment installations had begun, and by spring 2006, the experiment was fully operational, remaining so for one full year.

The motivating theme of the project was based on the GridWise concept that inserting intelligence into electric grid components at every point in the supply chain – from generation through end-use – will significantly improve both the electrical and economic efficiency of the power system. In this case, information technology and communications were used to create a real-time energy market system that could control demand response automation and distributed generation dispatch. Optimal use of the DER assets was achieved through the market, which was designed to manage the flow of power through a constrained distribution feeder circuit.

The project also illustrated the value of interoperability in several ways, as defined by the DOE’s GridWise Architecture Council (GWAC). First, a highly heterogeneous set of energy assets, associated automation controls and business processes was composed into a single solution integrating a purely economic or business function (the market-clearing system) with purely physical or operational functions (thermostatic control of space heating and water heating). This demonstrated interoperability at the technical and informational levels of the GWAC Interoperability Framework (www.gridwiseac.org/about/publications.aspx), providing an ideal example of a cyber-physical-business system. In addition, it represents an important class of solutions that will emerge as part of the transition to smart grids.

Second, the objectives of the various asset owners participating in the market were continuously balanced to maintain the optimal solution at any point in time. This included the residential demand response customers; the commercial and municipal entities with both demand response and distributed generation; and the utilities, which demonstrated interoperability at the organizational level of the framework.

PROJECT RESOURCES

The following energy assets were configured to respond to market price signals:

Residential demand response for electric space and water heating in 112 single-family homes using gateways connected by DSL or cable modem to provide two-way communication. The residential demand response system allowed the current market price of electricity to be presented to customers. Consumers could also configure their demand response automation preferences. The residential consumers were evenly divided among three contract types (fixed, time of use and real time) and a fourth control group. All electricity consumption was metered, but only the loads in price-responsive homes were controlled by the project (approximately 75 KW).
Two distributed generation units (175 KW and 600 KW) at a commercial site served the facility’s load when the feeder supply was not sufficient. These units were not connected in parallel to the grid, so they were bid into the market as a demand response asset equal to the total load of the facility (approximately 170 KW). When the bid was satisfied, the facility disconnected from the grid and shifted its load to the distributed generation units.
One distributed microturbine (30 KW) that was connected in parallel to the grid. This unit was bid into the market as a generation asset based on the actual fixed and variable expenses of running the unit.
Five 40-horsepower (HP) water pumps distributed between two municipal water-pumping stations (approximately 150 KW of total nameplate load). The demand response load from these pumps was incrementally bid into the market based on the water level in the pumped storage reservoir, effectively converting the top few feet of the reservoir capacity into a demand response asset on the electrical grid.

Monitoring was performed for all of these resources, and in cases of price-responsive contracts, automated control of demand response was also provided. All consumers who employed automated control were able to temporarily disable or override project control of their loads or generation units. In the residential realtime price demand response homes, consumers were given a simple configuration choice for their space heating and water heating that involved selecting an ideal set point and a degree of trade-off between comfort and price responsiveness.

For real-time price contracts, the space heater demand response involved automated bidding into the market by the space heating system. Since the programmable thermostats deployed in the project didn’t support real-time market bidding, IBM Research implemented virtual thermostats in software using an event-based distributed programming prototype called Internet- Scale Control Systems (iCS). The iCS prototype is designed to support distributed control applications that span virtually any underlying device or business process through the definition of software sensor, actuator and control objects connected by an asynchronous event programming model that can be deployed on a wide range of underlying communication and runtime environments. For this project, virtual thermostats were defined that conceptually wrapped the real thermostats and incorporated all of their functionality while at the same time providing the additional functionality needed to implement the real-time bidding. These virtual thermostats received
the actual temperature of the house as well as information about the real-time market average price and price distribution and the consumer’s preferences for set point and comfort/economy trade-off setting. This allowed the virtual thermostats to calculate the appropriate bid every five minutes based on the changing temperature and market price of energy.

The real-time market in the project was implemented as a shadow market – that is, rather than change the actual utility billing structure, the project implemented a parallel billing system and a real-time market. Consumers still received their normal utility bill each month, but in addition they received an online bill from the shadow market. This additional bill was paid from a debit account that used funds seeded by the project based on historical energy consumption information for the consumer.

The objective was to provide an economic incentive to consumers to be more price responsive. This was accomplished by allowing the consumers to keep the remaining balance in the debit account at the end of each quarter. Those consumers who were most responsive were estimated to receive about $150 at the end of the quarter.

The market in the project cleared every five minutes, having received demand response bids, distributed generation bids and a base supply bid based on the supply capacity and wholesale price of energy in the Mid-Columbia system operated by Bonneville Power Administration. (This was accomplished through a Dow Jones feed of the Mid-Columbia price and other information sources for capacity.) The market operation required project assets to submit bids every five minutes into the market, and then respond to the cleared price at the end of the five-minute market cycle. In the case of residential space heating in real-time price contract homes, the virtual thermostats adjusted the temperature set point every five minutes; however, in most cases the adjustment was negligible (for example, one-tenth of a degree) if the price was stable.

KEY FINDINGS

Distribution constraint management. As one of the primary objectives of the experiment, distribution constraint management was successfully accomplished. The distribution feeder-imported capacity was managed through demand response automation to a cap of 750 KW for all but one five-minute market cycle during the project year. In addition, distributed generation was dispatched as needed during the project, up to a peak of about 350 KW.

During one period of about 40 hours that took place from Oct. 30, 2006, to Nov. 1, 2006, the system successfully constrained the feeder import capacity at its limit and dispatched distributed generation several times, as shown in Figure 1. In this figure, actual demand under real-time price control is shown in red, while the blue line depicts what demand would have been without real-time price control. It should be noted that the red demand line steps up and down above the feeder capacity line several times during the event – this is the result of distributed generation units being dispatched and removed as their bid prices are met or not.

Market-based control demonstrated. The project controlled both heating and cooling loads, which showed a surprisingly significant shift in energy consumption. Space conditioning loads in real-time price contract homes demonstrated a significant shift to early morning hours – a shift that occurred during both constrained and unconstrained feeder conditions but was more pronounced during constrained periods. This is similar to what one would expect in preheating or precooling systems, but neither the real nor the virtual thermostats in the project had any explicit prediction capability. The analysis showed that the diurnal shape of the price curve itself caused the effect.

Peak load reduced. The project’s realtime price control system both deferred and shifted peak load very effectively. Unlike the time-of-use system, the realtime price control system operated at a fine level of precision, responding only when constraints were present and resulting in a precise and proportionally appropriate level of response. The time-of-use system, on the other hand, was much coarser in its response and responded regardless of conditions on the grid, since it was only responding to preconfiured time schedules or manually initiated critical peak price signals.

Internet-based control demonstrated. Bids and control of the distributed energy resources in the project were implemented over Internet connections. As an example, the residential thermostats modified their operation through a combination of local and central control communicated as asynchronous events over the Internet. Even in situations of intermittent communication failure, resources typically performed well in default mode until communications could be re-established. This example of the resilience of a well-designed, loosely coupled distributed control application schema is an important aspect of what the project demonstrated.

Distributed generation served as a valuable resource. The project was highly effective in using the distributed generation units, dispatching them many times over the duration of the experiment. Since the diesel generators were restricted by environmental licensing regulations to operate no more than 100 hours per year, the bid calculation factored in a sliding scale price premium such that bids would become higher as the cumulative runtime for the generators increased toward 100 hours.

CONCLUSION

The Olympic Peninsula Project was unique in many ways. It clearly demonstrated the value of the GridWise concepts of leveraging information technology and incorporating market constructs to manage distributed energy resources. Local marginal price signals as implemented through the market clearing process, and the overall event-based software integration framework successfully managed the bidding and dispatch of loads and balanced the issues of wholesale costs, distribution congestion and customer needs in a very natural fashion.

The final report (as well as background material) on the project is available at www.gridwise.pnl.gov. The report expands on the remarks in this article and provides detailed coverage of a number of important assertions supported by the project, including:

Market-based control was shown to be a viable and effective tool for managing price-based responses from single-family premises.
Peak load reduction was successfully accomplished.
Automation was extremely important in obtaining consistent responses from both supply and demand resources.
The project demonstrated that demand response programs could be designed by establishing debit account incentives without changing the actual energy prices offered by energy providers.

Although technological challenges were identified and noted, the project found no fundamental obstacles to implementing similar systems at a much larger scale. Thus, it’s hoped that an opportunity to do so will present itself at some point in the near future.

Ontario Pilot

Smart metering technologies are making it possible to provide residential utility customers with the sophisticated “smart pricing” options once available only to larger commercial and industrial customers. When integrated with appropriate data manipulation and billing systems, smart metering systems can enable a number of innovative pricing and service regimes that shift or reduce energy consumption.

In addition, by giving customers ready access to up-to-date information about their energy demand and usage through a more informative bill, an in-home display monitor or an enhanced website, utilities can supplement smart pricing options and promote further energy conservation.

SMART PRICES

Examples of smart pricing options include:

Time-of-use (TOU) is a tiered system where price varies consistently by day or time of day, typically with two or three price levels.
Critical peak pricing (CPP) imposes dramatically higher prices during specific days or hours in the year to reflect the actual or deemed price of electricity at that time.
Critical peak rebate (CPR) programs enable customers to receive rebates for using less power during specific periods.
Hourly pricing allows energy prices to change on an hourly basis in conformance with market prices.
Price adjustments reflect customer participation in load control, distributed generation or other programs.

SMART INFORMATION

Although time-sensitive pricing is designed primarily to reduce peak demand, these programs also typically result in a small reduction in overall energy consumption. This reduction is caused by factors independent of the primary objective of TOU pricing. These factors include the following:

Higher peak pricing causes consumers to eliminate, rather than merely delay, activities or habits that consume energy. Some of the load reductions that higher peak or critical peak prices produce are merely shifted to other time periods. For example, consumers do not stop doing laundry; they simply switch to doing it at non-peak times. In these cases the usage is “recovered.” Other load reductions, such as those resulting from consumers turning off lights or lowering heat, are not recovered, thus reducing the household’s total electricity consumption.
Dynamic pricing programs give participants a more detailed awareness of how they use electricity, which in turn results in lower consumption.
These programs usually increase the amount of usage information or feedback received by the customer, which also encourages lower consumption.

The key challenge for utilities and policy makers comes in deciding which pricing and communications structures will most actively engage their customers and drive the desired conservation behaviors. Studies show that good customer feedback on energy usage can reduce total consumption by 5 to 10 percent. Smart meters let customers readily access more up-to-date information about their hourly, daily and monthly energy usage via in-home displays, websites and even monthly bill inserts.

The smart metering program undertaken by the province of Ontario, Canada, presents one approach and serves as a useful example for utility companies contemplating similar deployments.

ONTARIO’S PROGRAM

In 2004, anticipating a serious energy generation shortfall in coming years, the government of Ontario announced plans to have smart electricity meters installed in 800,000 homes and small businesses by the end of 2007, and throughout Ontario by 2010. The initiative will affect approximately 4.5 million customers.

As the regulator of Ontario’s electricity industry, the Ontario Energy Board (OEB) was responsible for designing the smart prices that would go with these smart meters. The plan was to introduce flexible, time-of-use electricity pricing to encourage conservation and peak demand shifting. In June 2006, the OEB commissioned IBM to manage a pilot program that would help determine the best structure for prices and the best ways to communicate these prices.

By Aug. 1, 2006, 375 residential customers in the Ottawa area of Ontario had been recruited into a seven-month pilot program. Customers were promised $50 as an incentive for remaining on the pilot for the full period and $25 for completing the pilot survey.

Pilot participants continued to receive and pay their “normal” bimonthly utility bills. Separately, participants received monthly electricity usage statements that showed their electricity supply charges on their respective pilot price plan, as illustrated in Figure 1. Customers were not provided with any other new channels for information, such as a website or in-home display.

A control group that continued being billed at standard rates was also included in the study. Three pricing structures were tested in the pilot, with 125 customers in each group:

Time-of-use (TOU). Ontario’s TOU pricing includes off-peak, mid-peak and peak prices that changed by winter and summer season.
TOU with CPP. Customers were notified a day in advance that the price of the electricity commodity (not delivery) for three or four hours the next day would increase to 30 cents per kilowatt hour (kWh) – nearly six times the average TOU price. Seven critical peak events were declared during the pilot period – four in summer and three in winter. Figure 2 shows the different pricing levels.
TOU with CPR. During the same critical peak hours as CPP, participants were provided a rebate for reductions below their “baseline” usage. The base was calculated as the average usage for the same hours of the five previous nonevent, non-holiday weekdays, multiplied by 125 percent.

The results from the Ontario pilot clearly demonstrate that customers want to be engaged and involved in their energy service and use. Consider the following:

Within the first week, and before enrollment was suspended, more than 450 customers responded to the invitation letter and submitted requests to be part of the pilot – a remarkable 25 percent response rate. In subsequent focus groups, participants emphasized a desire to better monitor their own electricity usage and give the OEB feedback on the design of the pricing. These were in fact the primary reasons cited for enrolling in the pilot.
In comparison to the control group, total load shifting during the four summertime critical peak periods ranged from 5.7 percent for TOU-only participants to 25.4 percent for CPP participants.
By comparing the usage of the treatment and control groups before and during the pilot, a substantial average conservation effect of 6 percent was recorded across all customers.
Over the course of the entire pilot period, on average, participants shifted consumption and paid 3 percent, or $1.44, less on monthly bills with the TOU pilot prices, compared with what they would have paid using the regular electricity prices charged by their utility. Of all participants, 75 percent saved money on TOU prices. Figure 3 illustrates the distribution of savings.
When this shift in consumption was combined with the reduction in customers’ overall consumption, a total average monthly savings of more than $4 resulted. From this perspective, 93 percent of customers would pay less on the TOU prices over the course of the pilot program than they would have with the regular electricity prices charged by their utility.
Citing greater control of their energy costs and benefits to the environment, 7 percent of participants surveyed said they would recommend TOU pricing to their friends.

There were also some unexpected results. For instance, there was no pattern of customers shifting demand away from the dinnertime peak period in winter. In addition, TOU-only pricing alone did not result in a statistically significant shifting of power away from peak periods.

CONCLUSION

In summary, participants in the Ontario Energy Board’s pilot program approved of these smarter pricing structures, used less energy overall, shifted consumption from peak periods in the summertime and, as a result, most paid less on their utility bills.

Over the next decade, as the utility industry evolves to the intelligent utility network and smart metering technologies are deployed to all customers, utilities will have many opportunities to implement new electricity pricing structures. This transition will represent a considerable technical challenge, testing the limits of the latest communications, data management, engineering, metering and security technologies.

But the greater challenge may come from customers. Much of the benefit from smart metering is directly tied to real, measurable and predictable changes in how customers use energy and interact with their utility provider. Capturing this benefit requires successful manipulation of the complex interactions of economic incentives, consumer behavior and societal change. Studies such as the OEB Smart Pricing Pilot provide another step in penetrating this complexity, helping the utility industry better understand how customers react and interact with these new approaches.

Con Edison

Consolidated Edison Co. of New York (Con Edison) is a regulated utility serving 3.2 million electric customers in New York City and Westchester County. The company recognized that it could realize significant cost savings if more customers would adopt electronic billing, where bills are delivered electronically without a paper version. Eliminating the printing, postage, labor and equipment costs associated with paper billing can result in significant cost savings.

In addition to operational cost savings, further positive results could be gained from driving e-bill adoption, including improved customer relationships and fewer billing-related service calls. According to a Harris Interactive study conducted for CheckFree Research Services, customers who receive e-bills at a biller organization’s website show higher satisfaction levels, with 25 percent of them reporting an improved relationship with their biller as a result of receiving e-bills.

The challenge was how to attract more customers to the low-cost, high-impact online channel for billing activities and shut off their paper bills. To convince customers to change their behavior, Con Edison had to find a way to cost-effectively generate widespread awareness of electronic billing and explain how benefits, such as saving time, reducing clutter and helping the environment, outweigh concerns customers may have about giving up their paper bills.

THE ADVANTAGES OF ELECTRONIC BILLING

Together, Con Edison and CheckFree developed a comprehensive marketing campaign designed to communicate the advantages of electronic billing to as many customers as possible. As a critical first step, Con Edison gained cross-organizational alignment regarding the campaign strategy. Drawing from a longstanding commitment to the environment, the company made a strategic decision to implement an ongoing campaign that conveyed a “Go green with e-bills” message across numerous channels in order to maximize reach within its customer base. Research has shown that when attempting to change consumer behavior, a comprehensive, consistent and widespread marketing campaign is far more effective than “one-off” campaigns utilizing minimal tactics.

In May 2007, Con Edison launched the integrated marketing campaign capitalizing on the wave of consumer awareness on environmental issues. Con Edison promoted paperless billing and electronic payment through a variety of methods and channels, including:

Customer Emails;
Direct-mail postcards;
On-hold messaging;
Radio advertising;
Invoice messaging;
Press releases;
Con Edison website messaging;
My CheckFree website messaging;
Customer newsletters; and
Internal employee newsletters.

Each communication featured the company’s environmental incentive – for every customer choosing the paper-saving option of viewing and paying their bills online, Con Edison would donate $1 to a local, nonprofit tree-planting fund to help the environment in New York.

To aid in driving awareness, Con Edison made a deliberate decision to create an extended campaign designed to consistently reinforce the safety, security, simplicity and environmental benefits of electronic billing. Based on the success of the marketing activities seen thus far, Con Edison plans to include the “Go green with e-bills” theme in every consumer communication going forward.

THE RESULTS

Con Edison showed persistence and enthusiasm in pursuing a multichannel marketing campaign, and it was well worth the effort. In the first seven months after the campaign was launched, Con Edison generated impressive results, including the following:

More than 42,000 e-bills activated;
A 57 percent increase in e-bill activations over the same time period in 2006; and
A 19 percent increase in online e-bill payments over the same time period in 2006.

Con Edison also has benefited from the positive press and goodwill it’s created in the community. By providing its customers with a better, more environmentally friendly choice for paying and receiving their utility bills, Con Edison is minimizing costs, maintaining operational control, optimizing growth for its business and turning customer interactions into profitable relationships.

Pepco Holdings, Inc.

The United States and the world are facing two preeminent energy challenges: the rising cost of energy and the impact of increasing energy use on the environment. As a regulated public utility and one of the largest energy delivery companies in the Mid-Atlantic region, Pepco Holdings Inc. (PHI) recognized that it was uniquely positioned to play a leadership role in helping meet both of these challenges.

PHI calls the plan it developed to meet these challenges the Blueprint for the Future (Blueprint). The plan builds on work already begun through PHI’s Utility of the Future initiative, as well as other programs. The Blueprint focuses on implementing advanced technologies and energy efficiency programs to improve service to its customers and enable them to manage their energy use and costs. By providing tools for nearly 2 million customers across three states and the district of Columbia to better control their electricity use, PHI believes it can make a major contribution to meeting the nation’s energy and environmental challenges, and at the same time help customers keep their electric and natural gas bills as low as possible.

The PHI Blueprint is designed to give customers what they want: reasonable and stable energy costs, responsive customer service, power reliability and environmental stewardship.

PHI is deploying a number of innovative technologies. Some, such as its automated distribution system, help to improve reliability and workforce productivity. Other systems, including an advanced metering infrastructure (AMI), will enable customers to monitor and control their electricity use, reduce their energy costs and gain access to innovative rate options.

PHI’s Blueprint is both ambitious and complex. Over the next five years PHI will be deploying new technologies, modifying and/or creating numerous information systems, redefining customer and operating work processes, restructuring organizations, and managing relationships with customers and regulators in four jurisdictions. PHI intends to do all of this while continuing to provide safe and reliable energy service to its customers.

To assist in developing and executing this plan, PHI reached out to peer utilities and vendors. One significant “partner” group is the Global Intelligent Utility network Coalition (GIUNC), established by IBM, which currently includes CenterPoint Energy (Texas), Country Energy (new South Wales, Australia) and PHI.

Leveraging these resources and others, PHI managers spent much of 2007 compiling detailed plans for realizing the Blueprint. Several aspects of these planning efforts are described below.

VISION AND DESIGN

In 2007, multiple initiatives were launched to flesh out the many aspects of the Blueprint. As Figure 1 illustrates, all of the initiatives were related and designed to generate a deployment plan based on a comprehensive review of the business and technical aspects of the project.

At this early stage, PHI does not yet have all the answers. Indeed, prematurely committing to specific technologies or designs for work that will not be completed for five years can raise the risk of obsolescence and lost investment. The deployment plan and system map, discussed in more detail below, are intended to serve as a guide. They will be updated and modified as decision points are reached and new information becomes available.

BUSINESS CASE VALIDATION

One of the first tasks was to review and define in detail the business case analyses for the project components. Both benefit assumptions and implementation costs were tested. Reference information (benchmarks) for this review came from a variety of sources: IBM experience in projects of similar scope and type; PHI materials and analysis; experiences reported by other GIUNC members; and other utilities and other publicly available sources. This information was compiled, and a present value analysis was conducted on discounted cash flow and rate of return, as shown in Figure 2.

In addition to an “operational benefits” analysis, PHI and the Brattle Group developed value assessments associated with demand response offerings such as critical peak pricing. With demand response, peak consumption can be reduced and capacity cost avoided. This means lower total energy prices for customers and less new capacity additions in the market. As Figure 2 shows, in even the worst-case scenario for demand response savings, operational and customer benefits will offset the cost of PHI’s AMI investment.

The information from these various cases has since been integrated into a single program management tool. Additional capabilities for optimizing results based on value, cost and schedule were developed. Finally, dynamic relationships between variables were modeled and added to the tool, recognizing that assumptions don’t always remain constant as plans are changed. One example of this would be the likely increase in call center cost per meter when deployment accelerates and customer inquiries increase.

HIGH-LEVEL COMMUNICATIONS ARCHITECTURE DESIGN

To define and develop the communications architecture, PHI deployed a structured approach built around IBM’s proprietary optimal comparative communications architecture methodology (OCCAM). This methodology established the communications requirements for AMI, data architecture and other technologies considered in the Blueprint. Next, an evaluation of existing communications infrastructure and capabilities was conducted, which could be leveraged in support of the new technologies. Then, alternative solutions to “close the gap” were reviewed. Finally, all of this information was incorporated in an analytical tool that matched the most appropriate communication technology within a specified geographic area and business need.

SYSTEM MAP AND INFORMATION MODEL

Defining the data framework and the approach to overall data integration elements across the program areas is essential if companies are to effectively and efficiently implement AMI systems and realize their identified benefits.

To help PHI understand what changes are needed to get from their current state to a shared vision of the future, the project team reviewed and documented the “current state” of the systems impacted by their plans. Then, subject matter experts with expertise in meters, billing, outage, system design, work and workforce management, and business data analysis were engaged to expand on the data architecture information, including information on systems, functions and the process flows that tie them all together. Finally, the information gathered was used to develop a shared vision of how PHI processes, functions, systems and data will fit together in the future.

By comparing the design of as-is systems with the to-be architecture of information management and information flows, PHI identified information gaps and developed a set of next steps. One key step establishes an “enterprise architecture” model for development. The first objective would be to establish and enforce governance policies. With these in place, PHI will define, draft and ratify detailed enterprise architecture and enforce priorities, standards, procedures and processes.

PHASE 2 DEPLOYMENT PLAN

Based on the planning conducted over the last half of the year, a high-level project plan for Phase 2 deployment was compiled. The focus was mainly on Blueprint initiatives, while considering dependencies and constraints reported in other transformation initiatives. PHI subject matter experts, project team leads and experience gathered from other utilities were all leveraged to develop the Blueprint deployment plan.

The deployment plan includes multiple types of tasks; processes; and organization, technical and project management office-related activities, and covers a period of five to six years. Initiatives will be deployed in multiple releases, phased across jurisdictions (Delaware, District of Columbia, Maryland, New Jersey) and coordinated between meter installation and communications infrastructure buildout schedules.

The plan incorporates several initiatives, including process design, system development, communications infrastructure and AMI, and various customer initiatives. Because these initiatives are interrelated and complex, some programmatic initiatives are also called for, including change management, benefits realization and program management. From this deployment plan, more detailed project plans and dependencies are being developed to provide PHI with an end-to-end view of implementation.

As part of the planning effort, key risk areas for the Blueprint program were also defined, as shown in Figure 3. Input from interviews and knowledge leveraged from similar projects were included to ensure a comprehensive understanding of program risks and to begin developing mitigation strategies.

CONCLUSION

As PHI moves forward with implementation of its AMI systems, new issues and challenges are certain to arise, and programmatic elements are being established to respond. A program management office has been established and continues to drive more detail into plans while tracking and reporting progress against active elements. AMI process development is providing the details for business requirements, and system architecture discussions are resolving interface issues.

Deployment is still in its early stages, and much work lies ahead. However, with the effort grounded in a clear vision, the journey ahead looks promising.