Lighting the Way

Persistent climate change concerns, volatile energy prices and a growing awareness of technological advancement in energy are leading consumers across the globe to reconsider their role in the electric power value chain. Likewise, substantial increases in utility infrastructure investment are likely due to global demands for climate change mitigation; the need to support aging networks and generation plants; and proliferation of government stimulus plans for weakened economies.

For energy and utility companies, this presents an historic opportunity to encourage new, mutually beneficial behaviors and create business models to meet new consumer demands.

Our last report, "Plugging in the Consumer: Innovating Utility Business Models for the Future," explored the radically changing relationship between energy providers and consumers who took part in a survey conducted in late 2007. Even during the global economic downturn, progress has continued along the two dimensions shaping these changes: technology advancement and consumers’ desire for more control. Ultimately, this will result in movement of the basis of the industry to a participatory network – an interconnected environment characterized by a wide variety of grid and network technologies that enable shared responsibility and benefits. It will drive the creation of entirely new markets and products.

To continue our research about consumer expectations, we launched a followup survey in the fall of 2008. We surveyed over 5,000 customers from an expanded group of countries. This included the "core group" from our prior survey – the U.S., the U.K., Germany, the Netherlands, Australia and Japan – plus Canada, Denmark, Belgium, France, Ireland and New Zealand. Our survey findings strongly suggest the historical view of customers as "like-minded" is already outdated in most places.

Encouraging New Behaviors

In our surveys over the past two years, many consumers demonstrated at least one goal associated with asserting more control over their energy usage. The features of a participatory network appeal tremendously to them, because it would offer abundant service options and information to manage energy usage according to specific goals, such as cost reduction or environmental impact.

There is not much evidence that consumers think lower rates are coming. Over half see the cost increasing at roughly the same pace as usage. Forty percent see their bills increasing more rapidly than their usage (or not decreasing as much as any reduction in usage). Six percent think their bills will increase more slowly (or decrease more rapidly) than their usage. Overall, this year’s respondents have a slightly more pessimistic view of the next five years than those last year.

Cost remains the powerful motivator behind a desire for control over energy usage and a willingness to change behavior. Four in five consumers are willing to change the time-of-day in which they perform energy-consuming housework in exchange for cost savings of 50 percent or more. With the prevalent feeling that prices will move inexorably upward and awareness of smart meters growing, over 90 percent of respondents indicated that they would like a smart meter or other tools to manage their usage, with 55 percent to 60 percent of these respondents willing to pay a one-time or monthly fee for that capability.

Consumers’ emphasis on climate change and the availability of renewable energy programs in response to this demand for more carbon-neutral products remained about the same year to year. Across the core group countries, the percentage reporting that they did not have renewable power programs available dropped to 16 percent from 21 percent in the new survey (see Figure 1). Rather than changing their answers to the affirmative, however, most of the movement was to "don’t know" (up to 50 percent from 46 percent).

According to industry experts in some of the countries surveyed, the high level of "don’t know" responses, in part, reflects doubts in some countries about the veracity of green power claims. Still, if to a larger extent many customers truly cannot answer that question, this could indicate a valuable opportunity lost to ineffective communication with customers in countries with significant renewable resources and high participation levels.

In addition to environmental concerns, the global economic downturn of 2008 is clearly having severe impact on consumers. Across the core group countries, the number of consumers paying a premium for green products and services is down 20 percent to 30 percent (see Figure 2).

This change in spending patterns also seems to influence perceptions of green power options among consumers from core group countries that do not have (or are unsure if they have) green power options. The percentage of people who say they want green power options is down slightly, falling to 78 percent in 2008 from 85 percent in 2007. But, during that one-year period, the percentage of those willing to pay an additional 20 percent or more monthly dropped by nearly two-thirds, to just 6 percent from 16 percent.

The percentage of those who have green power options and actually buy them remained about the same, however. This is not surprising given contractual commitments, significantly higher prices for nonrenewable fuels in the past year (which eliminated some of the cost differential between standard and green power), and the overall commitment to the environment expected of "green" consumers.

Analyzing Consumers

In "Plugging in the Consumer," we described an emerging segmentation comprised of four consumer types: passive ratepayers (PR), frugal goal-seekers (FGs), energy epicures (EE) and energy stalwarts (ES) (see Figure 3). Our latest survey results reinforce these segments as likely outcomes of current trends. Two main attributes are associated with variances in consumers’ behavior profiles:

  • Personal Initiative. A consumer’s willingness to make decisions and take action based on specific goals such as cost control, reliability, convenience and climate change impact.
  • Disposable Income. A consumer’s financial wherewithal to support energy-related goals. In early adoption phases, only those with sufficient resources will be able to implement new technologies and buy more expensive products.

We also found that other demographic characteristics – such as age and country of residence – affect the speed of technology adoption, ability to leverage control "behind the meter," goals embedded in accepting more responsibility for energy choices, among others.

Consumer Profiles

PRs that embody a passive preference for the status quo remain the most prevalent of any of the four consumer archetypes. However, we see a remarkable transition in progress. In the past, these typically uninvolved, acquiescent customers comprised virtually 100 percent of the customer base. They represent just 31 percent of our 2008 survey respondents.

The number of more engaged and goal-oriented customers all along the income spectrum is approaching one-half of the total customer base. Frugal goal-seekers (FGs), about 22 percent of the survey population, have limited resources but strong will to change the way they use energy and manage its consumption. This group desires low-cost control of energy choices. Energy stalwarts (ES) have enough strength in both will and wallet to proactively take measures from making simple efficiency improvements to generating their own electricity. They have a clear willingness to invest in energy choices and represent about one in five consumers surveyed. Both of these groups will strongly influence the other half of consumers as they succeed in meeting their goals.

The remaining respondents (26 percent) are the EEs, who are curious but not committed. While they actually demonstrate more knowledge about their provider and options than any other group, they do not share the cost concerns or clear desire for information and control. This appears to be a matter of choice and not ignorance. While passive in some ways, this group is open to experimentation, particularly when the cost and lifestyle impact of a behavioral change are low.

Generational Change

In the short term, changes in customer needs will occur based on personal initiative and income. In the long run, even more radical changes may emerge as the millennial generation continues to move into adulthood and the energy customer base. By varying definitions, the first wave of these information-hungry, technology-savvy consumers is somewhere in our 25- to 34-year-old demographic grouping and fully encompasses the 18- to 24-year-old age group.

Precisely at this juncture, we see major changes in the survey results related to the ways consumers learn about companies and products, what they value and what they will pay for, as well as how they communicate with each other and the companies with which they do business. This, ultimately, may give way to new customer segments that will influence the shape of the industry in ways unimagined just a decade or two ago. To effectively determine the best strategy for a customer-focused transition to the participatory network of the future, every provider of energy or related services will need to construct an inventory of existing customer interactions with a wide variety of current and future service and product models.

In the following sections, we outline how specific consumer segments view the technology and business advances associated with key interactions.

Learning about Providers

Important messages from providers do not always reach consumers, as evidenced by consumers’ lack of awareness of available green power options (see Figure 1).

Additionally, only one in six consumers foresees a decrease in usage over the next five years, and only about a third say their provider can help them save energy despite strong efforts by the industry and governments to promote efficiency. In particular, provider messages are not reaching the youngest consumers. For example, those aged 18 to 34 are 40 percent more likely to not know if they have a choice in providers versus those 35 and older. The under-34 group also is twice as likely to not even know their provider’s name.

While all age groups will continue to rely heavily on their providers for information about energy (85 percent to 90 percent of respondents indicated this was a likely source), reliance on other sources differed starkly. Those over 55 are more than 10 times more likely to look to government for energy information than to social networks and other Web 2.0 content. Current trends also imply that those under 25 are becoming almost as likely to use the latter, rather than the former. To reach all generations, companies need to understand how different consumers tend to educate themselves about providers and their offerings with the wide variety of media available.

Controlling Costs

Not surprisingly, those aged 18 to 34 were most eager for the types of "self-service" and automated energy management that smart metering and smart grids will bring. What may be surprising, however, is that this age group – and particularly those under 25 – is the most willing to pay a stated premium for these services of approximately $100 U.S. as a one-time fee, or a monthly fee of $5 U.S. (see Figure 4).

Having a message sent to a mobile device when power is out at the consumer’s home also garnered significantly higher interest from the under-25 age group. About 30 percent were more likely than the other age groups to pay $1 per month for such a service. This finding may be related to the generally higher willingness we observed of younger age groups to subscribe to these programs, to their higher rate of ownership of mobile data devices and plans, or a combination of the two.

Investing in the Consumer

Substantial new increases in investment in utility infrastructure will come with a great deal of public, regulatory and shareholder scrutiny. All of these stakeholders will want to know how the public as a whole can benefit.

Energy and utility companies will need a strategy for aligning customer wants and needs with technology deployment roadmaps, beginning with rigorous customer segmentation and building an inventory of customer interactions. This must be followed by a program to analyze the interactions that are anticipated with each consumer segment and to assess whether existing capabilities are sufficient to leverage the new infrastructure in ways that support the new customer experience:

  • Identifying customer wants and needs specific to the interactions that will be most important to each particular segment;
  • Identifying the interactions that can be most effectively enhanced through participatory network deployment strategies;
  • Defining new or augmented business capabilities and regulatory models that must be developed to translate technological capabilities into customer benefits;
  • Determining which capabilities, if any, will be ceded to other providers for further development;
  • Integrating the development of specific new business capabilities into the participatory network deployment roadmap; and
  • Communicating these new capabilities clearly and effectively to all stakeholders.

The outcome of this process will lead to critical decisions about the customer-facing business capabilities on which the enterprise will focus.

Existing organizational strengths and new capabilities to be developed – one by one or in combinations – will form the basis for a broad menu of new products and services that the energy provider can offer. Each energy or service provider must be prepared to analyze its customer base to determine specific wants and needs before assessing how customers want to see new products and services emerge. After preferences are evaluated, they need to be applied to the customer interaction inventory in a way that identifies what should to be enhanced through technological improvements, regulatory change or improvements to communication channels.

This needs to be an ongoing process; customer assessment will not cease to be important once the participatory network is in place. The good news is that the data required to perform this continual assessment will be ubiquitous and arrive in real time from multiple sources of value-generating insights. But with this capability comes a challenge: finding new and powerful ways to collect, assimilate and evaluate this torrent of data in a way that will lead to inspiration for new programs and products that appeals to an expanding number of involved consumers.

Alcatel-Lucent Your Smart Grid Partner

Alcatel-Lucent offers comprehensive capabilities that combine Utility industry – specific knowledge and experience with carrier – grade communications technology and expertise. Our IP/MPLS Transformation capabilities and Utility market – specific knowledge are the foundation of turnkey solutions designed to enable Smart Grid and Smart Metering initiatives. In addition, Alcatel-Lucent has specifically developed Smart Grid and Smart Metering applications and solutions that:

  • Improve the availability, reliability and resiliency of critical voice and data communications even during outages
  • Enable optimal use of network and grid devices by setting priorities for communications traffic according to business requirements
  • Meet NERC CIP compliance and cybersecurity requirements
  • Improve the physical security and access control mechanism for substations, generation facilities and other critical sites
  • Offer a flexible and scalable network to grow with the demands and bandwidth requirements of new network service applications
  • Provide secure web access for customers to view account, electricity usage and billing information
  • Improve customer service and experience by integrating billing and account information with IP-based, multi-channel client service platforms
  • Reduce carbon emissions and increase efficiency by lowering communications infrastructure power consumption by as much as 58 percent

Working with Alcatel-Lucent enables Energy and Utility companies to realize the increased reliability and greater efficiency of next-generation communications technology, providing a platform for, and minimizing the risks associated with, moving to Smart Grid solutions. And Alcatel-Lucent helps Energy and Utility companies achieve compliance with regulatory requirements and reductions in operational expenses while maintaining the security, integrity and high availability of their power infrastructure and services. We build Smart Networks to support the Smart Grid.

American Recovery and Reinvestment Act of 2009 Support from Alcatel-Lucent

The American Recovery and Reinvestment Act (ARRA) of 2009 was adopted by Congress in February 2009 and allocates $4.5 billion to the Department of Energy (DoE) for Smart Grid deployment initiatives. As a result of the ARRA, the DoE has established a process for awarding the $4.5 billion via investment grants for Smart Grid Research and Development, and Deployment projects. Alcatel-Lucent is uniquely qualified to help utilities take advantage of the ARRA Smart Grid funding. In addition to world-class technology and Smart Grid and Smart Metering solutions, Alcatel-Lucent offers turnkey assistance in the preparation of grant applications, and subsequent follow-up and advocacy with federal agencies. Partnership with Alcatel-Lucent on ARRA includes:

  • Design Implementation and support for a Smart Grid Network
  • Identification of all standardized and unique elements of each grant program
  • Preparation and Compilation of all required grant application components, such as project narratives, budget formation, market surveys, mapping, and all other documentation required for completion
  • Advocacy at federal, state, and local government levels to firmly establish the value proposition of a proposal and advance it through the entire process to ensure the maximum opportunity for success

Alcatel-Lucent is a Recognized Leader in the Energy and Utilities Market

Alcatel-Lucent is an active and involved leader in the Energy and Utility market, with active membership and leadership roles in key Utility industry associations, including the Utility Telecom Council (UTC), the American Public Power Association (APPA), and Gridwise. Gridwise is an association of Utilities, industry research organizations (e.g., EPRI, Pacific Northwest National Labs, etc.), and Utility vendors, working in cooperation with DOE to promote Smart Grid policy, regulatory issues, and technologies (see www.gridwise.org for more info). Alcatel-Lucent is also represented on the Board of Directors for UTC’s Smart Network Council, which was established in 2008 to promote and develop Smart Grid policies, guidelines, and recommended technologies and strategies for Smart Grid solution implementation.

Alcatel-Lucent IP MPLS Solution for the Next Generation Utility Network

Utility companies are experienced at building and operating reliable and effective networks to ensure the delivery of essential information and maintain flawless service delivery. The Alcatel-Lucent IP/MPLS solution can enable the utility operator to extend and enhance its network with new technologies like IP, Ethernet and MPLS. These new technologies will enable the utility to optimize its network to reduce both CAPEX and OPEX without jeopardizing reliability. Advanced technologies also allow the introduction of new Smart Grid applications that can improve operational and workflow efficiency within the utility. Alcatel-Lucent leverages cutting edge technologies along with the company’s broad and deep experience in the utility industry to help utility operators build better, next-generation networks with IP/MPLS.

Alcatel-Lucent has years of experience in the development of IP, MPLS and Ethernet technologies. The Alcatel-Lucent IP/MPLS solution offers utility operators the flexibility, scale and feature sets required for mission-critical operation. With the broadest portfolio of products and services in the telecommunications industry, Alcatel-Lucent has the unparalleled ability to design and deliver end-to-end solutions that drive next-generation utility networks.

About Alcatel-Lucent

Alcatel-Lucent’s vision is to enrich people’s lives by transforming the way the world communicates. As a leader in utility, enterprise and carrier IP technologies, fixed, mobile and converged broadband access, applications, and services, Alcatel-Lucent offers the end-to-end solutions that enable compelling communications services for people at work, at home and on the move.

With 77,000 employees and operations in more than 130 countries, Alcatel-Lucent is a local partner with global reach. The company has the most experienced global services team in the industry, and Bell Labs, one of the largest research, technology and innovation organizations focused on communications. Alcatel-Lucent achieved adjusted revenues of €17.8 billion in 2007, and is incorporated in France, with executive offices located in Paris.

The Smart Grid Gets Real

Utilities around the world are facing a future that demands technology and service to better measure, manage and control distributed resources. Sensus has anticipated that future with real-world solutions that are already at work in millions of households today. As a leading provider of advanced metering and related communications technologies to utilities worldwide, Sensus has been aggressively pushing the boundaries of utility management. Our innovative communication systems enable utilities to intelligently utilize their resources with unprecedented efficiency.

FlexNet Smart Grid Solution

FlexNet is the electric utility industry’s most powerful AMI solution. It meets AMI requirements of today; ubiquity, redundancy, security and demand response, and is smart grid ready. FlexNet is simple; its lean architecture uses a powerful, industry-leading two Watts of radio power to transmit information that maximizes range and minimizes operational costs with low infrastructure requirements. FlexNet insures sustainability, protecting the utility infrastructure investment and uninterrupted delivery.

Every FlexNet endpoint is equipped with the ability to accept downloadable revised code; modulations, protocols, frequency of operation, even data rate can be fully upgraded as future requirements and features are developed. Sensus FlexNet further mitigates risk by using APA™ (All Paths Always) technology; this ultimate form of self-healing ensures critical messages are delivered without re-routing delay.

iCon Smart Meters

The iCon line of solid state smart meters integrates seamlessly with the FlexNet AMI solution. Communication vendors and metrology engineers nationwide consistently find that the advanced family of Sensus meters provides complete functionality, superior reliability, flexible integration capability, industry standards compatibility, and economical value. The modular mechanical, electrical, and software designs, in combination with the advanced sensing capability, predictably deliver the speed, accuracy, and reliability required to meet today’s electric utility needs. With an unsurpassed accuracy exceeding ANSI C12.20 (Class 0.2), the iCon Meter by Sensus is built with a backbone of reliability and precision.

PHEVs Are on a Roll

The electric vehicle first made its appearance about a century ago, but it is only in recent years – months, to be more precise – that it has achieved breakthrough status as, quite possibly, the single-most important technological development having a positive impact on society today.

Climate change, over-dependence on fossil fuels, and the current economic crisis have combined to impact the automobile sector to a degree unforeseen, forcing technological innovation to direct its urgent attention toward the development of electric vehicles as an alternative means of transport, and a substitute for internal combustion engines. Many countries are supporting the approach in their political, energy and industrial planning directed toward the introduction of this type of vehicle. For example, the U.S. has a target of 1 million Plug-in Hybrid Electric Vehicles (PHEV) in operation by 2015. Spain expects to achieve the same number by 2014.

It is certainly true that there exist pressures capable of driving the introduction of the PHEV forward, but technological advances are the factors that underpin and give coherence to its development. There are several progressive improvements being made in technology, materials, and power generation and supply, which will support the deployment and use of electric vehicles in the coming years. They include: advances in battery manufacture and electronics (particularly in terms of power); the development of new communication protocols; ever more efficient and flexible information technologies; the growth of renewable energy sources in the electrical energy generation mix; and the concept of smart grids focused on more efficient electricity distribution. All of these improvements are underscored by a much greater degree of passion and personal involvement by the end-user.

Stakeholders and Utilities

With technology as the underlying catalyst, the scenario for electric vehicle use will include the impact and involvement of various stakeholders. This consists of: society itself, government and municipal entities, regulators, universities and research institutions, vehicle manufacturers, the ancillary automobile industry and its technological partners, battery manufacturers, the manufacturers of components, electrical and electronics systems, infrastructure suppliers, companies dedicated to mediation, billing and payment methods, ICT (Information and Communication Technology) companies, and of course, utilities.

If the electric vehicle is to become a genuinely alternative means of transportation, then this will depend on the involvement of, and interrelationship between, the above groups. One example of this is the formalizing of various agreements between certain stakeholders at both the national and international level (for example, Saab, Volvo, Wattenfall and ETC Battery in Sweden; Renault, PSA Peugeot Citroën, Toyota and EDF in France; and Iberdrola and General Motors at a global level) and the establishment of consortiums such as EDISON (Electric Vehicles in a Distributed and Integrated Market using Sustainable Energy and Open Networks) in Denmark.

If there is one dimension, however, which will be impacted most throughout the whole of the value chain, it is the electrical one. From power generation to retail, the introduction of this vehicle will require changes in current business models, and foreseeably, in utilities operational models. The short-term aim is to provide electrical energy for use in these vehicles in a more reliable and efficient way.

Battery Charging Impact

Given that charging could be the action having the greatest impact on the electrical sector, there are various alternatives for affecting this. These include:

  • Substitution. This involves a rapid exchange of vehicles and/or batteries, and the subsequent charging of both in an offline mode. It would require sharing of cars (vehicle usage and substitution) and battery charging stations for quick and automated battery exchange.
  • Direct Charging. This includes regular charging points situated in car parks, shopping centers and residences, and providing battery recharge while the vehicle is parked. There also need to be fast-charging points that could quickly charge a battery in 10 to 15 minutes.

To examine the advantages and disadvantages of the above methods, it helps to note the various pilot projects and research programs underway at both the conceptual and demonstration stages. These indicate the possibility of a coexistence scenario. Offline charging could be the least invasive method given the current system of fuel distribution. A network of “electricity stations” (as opposed to petrol stations) could provide a dedicated system of energy generation in a given location. As for direct charging, given the itinerant nature of user demand and his or her expected freedom to choose a particular charging method or location, this introduces an element of greater uncertainty, and impact on the electricity grid, requiring a system that better adapts to the lifestyle of the user.

Direct Charging and Its Impact on the Electricity Grid

Direct charging depends on various factors – notably battery characteristics (directly related to vehicle performance) and the range of time spans chosen to carry out the recharge. Associated with these are other variables: charging voltage, mode (DC, single-phase AC, and three-phase AC) and the characteristics of the charging systems employed: technology, components and their location, connectors, insulation, and the power and control electronics. All of these variables will influence the charging times, and will vary according to the power input (more power, less time) as shown in Figure 1. Therefore, depending on the kind of recharging, there will be an impact not only on the characteristics of the individual charging points but also on the supporting system.

Using extended range electrical vehicles (EREV) such as the Chevrolet Volt or Opel/Vauxhall Ampera as an example, it is estimated that annual home energy consumption from vehicle charging could be around 20 percent of the total, although some studies suggest this amount may be twice as much, based on the customer profile.

Based on the charging power input – and this is, of course, related to the methodology employed – it would be possible to fully recharge an EREV battery in about three hours. A fully charged battery would enable operation solely on electrical power for approximately 40 miles, a distance representing about 80 percent of daily car journeys based on the current averages. For a scenario like this it would be possible to use a charging method of about 4 kilowatt/220 volts.

If we analyze the impact in terms of energy supply and power capacity, there appears to be no medium-term problems in supporting these chargings, according to the data above. This is, however, a matter which depends on each individual country and also on the power transmission interconnections between them. In terms of the instantaneous power available, the charging method will have a greater or lesser impact, particularly on the distribution assets, depending on how it is carried out. Figure 2 shows how the power varies according to the charging method and the time of day when it is in use, taking into account the daily energy demand curve. We can, therefore, identify different scenarios from the most favourable (slow charging at off-peak times) to the most unfavourable (fast charging at peak times). With the latter we may find ourselves with distribution assets (e.g., transformers) incapable of supporting the heavy load of instant energy consumption.

It is necessary to link electric vehicle charging to the daily energy demand curve and instantaneous power availability in such a way that charging impacts the system as little as possible and maximizes the available energy resources. Ideally, there would be a move toward slow charging during off-peak periods. Furthermore, this kind of charging would not impact users as 90 percent of vehicles are not used between 11 a.m. and 6 p.m. Operating under such conditions would also permit the use of excess wind-generated power during off-peak times, enabling a clean locomotion device such as the PHEV to also use renewable (clean) energy as its primary source.

This all sounds reasonable, but the itinerant nature of roaming vehicle demand, together with relatively limited battery life, means that other variables such as home charging versus remote charging with the ability to measure consumption and set tariffs must be taken into account. What will be the charging price? How will charging be carried out when the vehicle is not parked at home, nor at its usual charging centre? What method will be used for making payments? Who will be involved in developing all this infrastructure and how will it all interrelate?

Smart Charging

One system providing answers to these questions is smart charging. Based on the concept, purpose and architecture of the smart grid, such technology can optimise charging in the most favorable way by considering several parameters. These may include: the current state of the electrical system; the battery charging level; tariff modes and associated demand-response models which may be applied (such as time of use, or TOU, tariffs); and the ability to use energy distributed and stored locally through an energy management system.

Smart charging would be capable of deciding when to charge in relation to different variables (for example, price and energy availability), and which energy sources to use (in-home energy storage, local and decoupled energy supply, plug-in to the distribution grid, etc.) Supporting the vehicle-to-grid (V2G) paradigm would enable managing and deciding not only when and how to best charge the vehicle, but also when to store energy in the vehicle battery that can later be returned to the grid for use in a local mode as a distributed energy source.

For all of this to be effective, a power and control electronics system (in both local and global mode), supported by information systems to manage those issues, is required. This will enable the optimal charging process (avoiding peak times, and doing fast charging only when necessary) and an intelligent measuring and tariff system. The latter may be either managed by utilities through advanced meter management (AMM), or virtually through energy tariffs and physical economic transactions. Such systems should allow for the interaction of various agents: end users, utilities, energy service companies (ESCO), infrastructure providers, banks and other method-of-payment companies.

Conclusion

Although there are still many unresolved issues around the introduction of electric vehicles (for example, incentives, carbon caps, tax collection, readiness of systems and business processes), the challenge associated with this means of locomotion and its effect on current business systems and models is a fascinating one. From an electrical viewpoint, there would not appear to be any significant impact on energy management in the medium term, but perhaps more so in terms of power requirements. As an example, some regions have adjusted to the massive introduction of air conditioning systems over recent years. While we are reassured as to the viability of electric vehicles, we are also alert to the possible significant impact of widespread vehicle charging, above all when considering a fast charging scenario.

The special characteristics of battery charging and its itinerant nature, the predicted volumes of power outlet and energy, the current state of tariff systems, the available technology, and the vision and state of deployment of smart grids and AMM, all add up to suggest a smart charging type of system would be the best option – though certainly complex to implement. Given the prominent role that information and communication technologies will play in such a system, it will be necessary to achieve consensus among various stakeholders over methodologies to be used, standards development, and in establishing a regulatory framework capable of supporting all the mechanisms and systems to be introduced.

We have already made good progress, and the electric vehicle could become an example that drives change in other business and technology models. It may well stimulate more rapid development of smart grids, encourage the creation of more efficient energy services and technologies, and lead to greater development and use of renewable energy sources, including a generation and distribution scenario based on the V2G paradigm.

It also may open the door to new businesses and stakeholders as well (such as the ESCOs) to introduce more dynamic, interactive demand response programs and broaden the function of battery storage as a provider of spinning reserves and ancillary services. These are all aspects for which it is now necessary to establish a basis for implementation and a short-term viability plan that will allow for the use of this technology with the aim of reaping its recognized benefits. Are we ready to step up to the challenge?

Successful Smart Grid Architecture

The smart grid is progressing well on several fronts. Groups such as the Grid Wise Alliance, events such as Grid Week, and national policy citations such as the American Recovery and Reinvestment Act in the U.S., for example, have all brought more positive attention to this opportunity. The boom in distributed renewable energy and its demands for a bidirectional grid are driving the need forward, as are sentiments for improving consumer control and awareness, giving customers the ability to engage in real-time energy conservation.

On the technology front, advances in wireless and other data communications make wide-area sensor networks more feasible. Distributed computation is certainly more powerful – just consider your iPod! Even architectural issues such as interoperability are now being addressed in their own forums such as Grid Inter-Op. It seems that the recipe for a smart grid is coming together in a way that many who envisioned it would be proud. But to avoid making a gooey mess in the oven, an overall architecture that carefully considers seven key ingredients for success must first exist.

Sources of Data

Utilities have eons of operational data: both real time and archival, both static (such as nodal diagrams within distribution management systems) and dynamic (such as switching orders). There is a wealth of information generated by field crews, and from root-cause analyses of past system failures. Advanced metering infrastructure (AMI) implementations become a fine-grained distribution sensor network feeding communication aggregation systems such as Silver Springs Network’s Utility IQ or Trilliant’s Secure Mesh Network.

These data sources need to be architected to be available to enhance, support and provide context for real-time data coming in from new intelligent electronic devices (IEDs) and other smart grid devices. In an era of renewable energy sources, grid connection controllers become yet another data source. With renewables, micro-scale weather forecasting such as IBM Research’s Deep Thunder can provide valuable context for grid operation.

Data Models

Once data is obtained, in order to preserve its value in a standard format, one can think in terms of an extensible markup language (XML)-oriented database. Modern implementations of these databases have improved performance characteristics, and the International Engineering Consortium (IEC) common information/ generic interface definition (CIM/GID) model, though oriented more to assets than operations, is a front-running candidate for consideration.

Newer entries, such as device language message specification – coincidence-ordered subsets expectation maximization (DLMS-COSEM) for AMI, are also coming into practice. Sometimes, more important than the technical implementation of the data, however, is the model that is employed. A well-designed data model not only makes exchange of data and legacy program adjustments easier, but it can also help the applicability of security and performance requirements. The existence of data models is often a good indicator of an intact governance process, for it facilitates use of the data by multiple applications.

Communications

Customer workshops and blueprinting sessions have shown that one of the most common issues needing to be addressed is the design of the wide-area communication system. Data communications architecture affects data rate performance, the cost of distributed intelligence and the identification of security susceptibilities.

There is no single communications technology that is suitable for all utilities, or even for all operational areas across any individual utility. Rural areas may be served by broadband over powerline (BPL), while urban areas benefit from multi-protocol label switching (MPLS) and purpose- designed mesh networks, enhanced by their proximity to fiber.

In the future, there could be entirely new choices in communications. So, the smart grid architect needs to focus on security, standardized interfaces to accept new technology, enablement of remote configuration of devices to minimize any touching of smart grid devices once installed, and future-proofing the protocols.

The architecture should also be traceable to the business case. This needs to include probable use cases that may not be in the PUC filing, such as AMI now, but smart grid later. Few utilities will be pleased with the idea of a communication network rebuild within five years of deploying an AMI-only network.

Communications architecture must also consider power outages, so battery backup, solar recharging, or other equipment may be required. Even arcane details such as “Will the antenna on a wireless device be the first thing to blow off in a hurricane?” need to be considered.

Security

Certainly, the smart grid’s purpose is to enhance network reliability, not lower its security. But with the advent of North American Reliability Corp. Critical Infrastructure Protection (NERC-CIP), security has risen to become a prime consideration, usually addressed in phase one of the smart grid architecture.

Unlike the data center, field-deployed security has many new situations and challenges. There is security at the substation – for example, who can access what networks, and when, within the control center. At the other end, security of the meter data in a proprietary AMI system needs to be addressed so that only authorized applications and personnel can access the data.

Service oriented architecture (SOA) appliances are network devices to enable integration and help provide security at the Web services message level. These typically include an integration device, which streamlines SOA infrastructures; an XML accelerator, which offloads XML processing; and an XML security gateway, which helps provide message-level, Web-services security. A security gateway helps to ensure that only authorized applications are allowed to access the data, whether an IP meter or an IED. SOA appliance security features complement the SOA security management capabilities of software.

Proper architectures could address dynamic, trusted virtual security domains, and be combined not only with intrusion protection systems, but anomaly detection systems. If hackers can introduce viruses in data (such as malformed video images that leverage faults in media players), then similar concerns should be under discussion with smart grid data. Is messing with 300 MegaWatts (MW) of demand response much different than cyber attacking a 300 MW generator?

Analytics

A smart grid cynic might say, “Who is going to look at all of this new data?” That is where analytics supports the processing, interpretation and correlation of the flood of new grid observations. One part of the analytics would be performed by existing applications. This is where data models and integration play a key role. Another part of the analytics dimension is with new applications and the ability of engineers to use a workbench to create their customized analytics dashboard in a self-service model.

Many utilities have power system engineers in a back office using spreadsheets; part of the smart grid concept is that all data is available to the community to use modern tools to analyze and predict grid operation. Analytics may need a dedicated data bus, separate from an enterprise service bus (ESB) or enterprise SOA bus, to meet the timeliness and quality of service to support operational analytics.

A two-tier or three-tier (if one considers the substations) bus is an architectural approach to segregate data by speed and still maintain interconnections that support a holistic view of the operation. Connections to standard industry tools such as ABB’s NEPLAN® or Siemens Power Technologies International PSS®E, or general tools such as MatLab, should be considered at design time, rather than as an additional expense commitment after smart grid commissioning.

Integration

Once data is sensed, securely communicated, modeled and analyzed, the results need to be applied for business optimization. This means new smart grid data gets integrated with existing applications, and metadata locked in legacy systems is made available to provide meaningful context.

This is typically accomplished by enabling systems as services per the classic SOA model. However, issues of common data formats, data integrity and name services must be considered. Data integrity includes verification and cross-correlation of information for validity, and designation of authoritative sources and specific personnel who own the data.

Name services addresses the common issue of an asset – whether transformer or truck – having multiple names in multiple systems. An example might be a substation that has a location name, such as Walden; a geographic information system (GIS) identifier such as latitude and longitude; a map name such as nearest cross streets; a capital asset number in the financial system; a logical name in the distribution system topology; an abbreviated logical name to fit in the distribution management system graphical user interface (DMS GUI); and an IP address for the main network router in the substation.

Different applications may know new data by association with one of those names, and that name may need translation to be used in a query with another application. While rewriting the applications to a common model may seem appealing, it may very well send a CIO into shock. While the smart grid should help propagate intelligence throughout the utility, this doesn’t necessarily mean to replace everything, but it should “information-enable” everything.

Interoperability is essential at both a service level and at the application level. Some vendors focus more at the service, but consider, for example, making a cell phone call from the U.S. to France – your voice data may well be code division multiple access (CDMA) in the U.S., travel by microwave and fiber along its path, and emerge in France in a global system for mobile (GSM) environment, yet your speech, the “application level data,” is retained transparently (though technology does not yet address accents!).

Hardware

The world of computerized solutions does not speak to software alone. For instance, AMI storage consolidation addresses the concern that the volume of data coming into the utility will be increasing exponentially. As more meter data can be read in an on-demand fashion, data analytics will be employed to properly understand it all, requiring a sound hardware architecture to manage, back-up and feed the data into the analytics engines. In particular, storage is needed in the head-end systems and the meter-data management systems (MDMS).

Head-end systems pull data from the meters to provide management functionality while the MDMS collects data from head-end systems and validates it. Then the data can be used by billing and other business applications. Data in both the head-end systems and the master copy of the MDMS is replicated into multiple copies for full back up and disaster recovery. For MDMS, the master database that stores all the aggregated data is replicated for other business applications, such as customer portal or data analytics, so that the master copy of the data is not tampered with.

Since smart grid is essentially performing in real time, and the electricity business is non-stop, one must think of hardware and software solutions as needing to be fail-safe with automated redundancy. The AMI data especially needs to be reliable. The key factors then become: operating system stability; hardware true memory access speed and range; server and power supply reliability; file system redundancy such as a JFS; and techniques such as FlashCopy to provide a point-in-time copy of a logical drive.

Flash Copy can be useful in speeding up database hot backups and restore. VolumeCopy can extend the replication functionality by providing the ability to copy contents of one volume to another. Enhanced remote mirroring (Global Mirror, Global Copy and Metro Mirror) can provide the ability to mirror data from one storage system to another, over extended distances.

Conclusion

Those are seven key ingredients for designing or evaluating a recipe for success with regard to implementing the smart grid at your utility. Addressing these dimensions will help achieve a solid foundation for a comprehensive smart grid computing system architecture.

A Smart Strategy for a Smart Grid

Every year, utilities are faced with the critical decision of where to invest capital. These decisions are guided by several factors, such as regulatory requirements, market conditions and business strategies. Given their magnitude, decisions are not made hastily. Careful consideration is given to the financial and operational prudence of large capital projects, such as power plants and new infrastructure.

The utility also makes sure that it has the resources to support the implementation and on-going operation of large projects. This discipline is necessary to do what is best for the utility, and ultimately, the customer. This same discipline is essential in assessing the use of smart grid technologies, such as advanced metering infrastructure (AMI), distribution automation (DA) and home area networks (HAN).

In the last several years, the ubiquitous coverage of the smart grid has sparked the interests of many utilities looking to modernize their infrastructures and find new ways to interact with their customers. Most recently, the excitement around smart grid initiatives has accelerated as a result of its inclusion in the U.S. government’s economic stimulus package. However, utilities must remain cautious as they evaluate these new technologies.

The current "rush" can result in a lack of structure around strategy and planning for smart grid improvements. As utilities embrace smart grid technologies, many are tempted to develop a vision and strategies in a hurried, reactionary fashion rather than taking a rigorous, structured approach to determine what technologies will deliver the most value to the utility and its customer base.

Unlike planning for other capital projects, planning for smart grid is not simply about filing a regulatory business case; it is planning a business case for transformation. It is about implementing the right mix of smart grid technologies that delivers the greatest direct (operational savings) and indirect (customer benefits, customer satisfaction, reliability) benefits for the utility. Additionally, proper planning and strategy identifies risks and considerations that facilitate implementation of new technologies. Finally, a structured approach considers the organization’s capacity to complete the project. Just as you wouldn’t approve the construction of a power plant without ensuring that you have the resources to complete it, you shouldn’t begin the smart grid journey without a clear sense of where you are going and how you are going to get there.

A methodical approach to defining a smart grid vision can be accomplished through leadership workshops that define a portfolio of strategic options and establish the criteria to analyze the portfolio’s value (both quantitative and qualitative). These sessions assess the various smart grid technologies to determine what unique mix (technologies and geographies) is the best fit to meet the utility’s objectives.

The key steps to defining a smart grid vision are:

  • Define a decision framework;
  • Develop strategic options;
  • Analyze value; and
  • Ratify strategy.

Ultimately, this approach results in a richer smart grid strategy and decision making process that is consistent with other large capital projects.

Define a Decision Framework

The first step toward defining a smart grid vision is to develop a decision making process to establish the emphasis and focus of the smart grid program. Are upfront capital costs the main concern, or is selecting mature and proven technologies more crucial? Some utilities may seek technologies that can be implemented quickly, while others may be more focused on a multi-year rollout of smart grid initiatives.

Identifying these crucial drivers and understanding their importance is achieved by creating a baseline decision framework to evaluate smart grid technologies. The framework should be shaped by project management, sponsorship and subject matter experts (SMEs) from all functional groups (e.g., transmission and distribution, meter services, billing, call center, human resources, finance and information technology) within the organization. This ensures that the initiative has executive buy-in and input from all groups affected by a smart grid implementation.

A good decision framework incorporates company strategic priorities and consists of both qualitative and quantitative measures. Qualitative factors include customer satisfaction, technology maturity and obsolescence, implementation risks and alignment with business priorities. Quantitative factors examine product and resource costs, and product benefits and savings.

It is also important to understand and compare functionality available to functionality needed. For example, a utility might be interested in implementing HAN capabilities, but may ultimately realize that DA will generate greater value. In the end, the decision framework lays the foundation for the evaluation of a utility’s smart grid portfolio.

Finally, a decision framework should consider and evaluate the program risks and the organization’s ability to successfully execute the project (e.g., timeline, skill set required, availability of resources, competing projects, technological obsolescence/ maturity).

Develop Strategic Options

Smart grid is not a "one size fits all" initiative. Rather than view smart grid as an "all or nothing" proposition, each utility should define its own customized solution. The specific strategy and technologies of a smart grid program is driven by the needs of the utility. For instance, utilities focused on improving grid reliability will emphasize DA technologies, while others more interested in reducing operational costs will emphasize an AMI approach.

Once a decision framework has been created, the utility should begin to assess the advantages and disadvantages of smart grid technologies using a summary scorecard (Figure 1).

These scorecards provide a comprehensive view of the technology and identify risks, dependencies, resource effort, key benefits and costs associated with the technology. Once complete, scorecards can be used to identify different mixtures, or portfolios, of smart grid technology options.

The advantage of assembling technologies into a portfolio is that it enables an enterprise-wide perspective of the program. The value for each stakeholder organization can be identified and evaluated. The integration of smart grid technologies is made more apparent.

When selecting a portfolio, there are a few key points to keep in mind. First, a smart grid portfolio doesn’t have to incorporate all available technologies, only the ones that coincide with the business strategy. Next, smart grid technologies don’t have to be implemented uniformly across the entire service territory. For instance, a utility could elect to utilize substation automation only at critical or less reliable substations, or choose to install AMI meters in jurisdictions/areas where meter reading cost is high.

Finally, timing of the smart grid rollout is critical. A utility doesn’t have to provide all of the functionality on day 1. Subsequent capability releases can be planned many years in the future.

One of the major obstacles to implementing a smart grid program is the lack of maturity in emerging smart grid technologies. Utilities can counter this through the use of interim solutions. An interim solution helps the utility to recognize smart grid benefits in a "manumatic" environment, combining manual business processes and a degree of process and system automation, with the goal to transition to more integration and automation.

Examples of interim solutions include:

  • Advanced Metering Infrastructure (AMI) – If there is no regulatory structure for the use of interval data, a utility could initially use the technology for remote monthly register reads and remote connect/ disconnect with idea to transition to interval-based rates as they become required.
  • Meter Data Management System (MDMS) – If interval data is not yet needed, the utility may be able to defer investment in an MDMS. At a later date, a new CIS system/CIS modifications could provide MDMS functionality.
  • Wide Area Network (WAN) Communications Backhaul – A utility may start with a cellular backhaul and move to another technology (e.g., WiMax) as it evolves.
  • Direct Load Control – Initially, a utility could use a technology independent of AMI (e.g., paging network) and then transition to load control through the AMI meter.

Incorporating interim solutions gives utilities additional flexibility in what technologies can be included in its smart grid portfolio. Once a closer analysis is given to the technology portfolio, utilities can determine if and where interim solutions should be considered.

Analyze Value

Would a utility build a 2 GigaWatt power plant to satisfy a 100 MegaWatt demand? It’s safe to say most wouldn’t. The additional capacity of the plant does not justify the cost. Although this is an obvious example, it demonstrates that utilities have an existing decision process around large capital investments. In order to successfully define a smart grid strategy, utilities must find a way to transition this type of analysis to smart grid technologies. A qualitative and quantitative value analysis of smart grid portfolios will provide justification of which smart grid technologies to implement.

Qualitative review involves scoring the chosen technology portfolio(s) against the decision framework. This provides a sense of how the technologies match the utility’s risk profile, resource constraints and overall strategy. For instance, a utility may see that some technologies are cost-effective, but too risky to implement in the short-term. These factors are not captured in financial modeling and provide key information to aid in the transition from strategic planning to implementation.

Quantitative analysis assures cost effectiveness for smart grid technology portfolio(s) and is achieved through the use of a business case or financial model. This analysis factors in the various costs and benefits of the smart grid portfolio. For instance, a technology portfolio with AMI and DA would indicate significant costs for the purchase and deployment of new devices, but would calculate benefits on improved grid reliability and remote meter reading.

Figure 2 depicts an overview of a financial model that could be used for smart grid value analysis. As the cost-effectiveness of a particular technology portfolio is determined, the utility may find that the portfolio needs to be modified in order to achieve increased savings. For example, an advanced communications infrastructure to implement AMI alone may not be cost effective. However, if the same infrastructure was also used to enable DA and mobile dispatch it would become much more cost effective. The combination of financial data and qualitative options analysis will help the utility to determine the optimal mix of smart grid technologies to implement.

Ratify Strategy

The selection of a smart grid portfolio and the associated value analysis is only the starting point on the journey to a smart grid; it simply puts the building blocks in place for the utility to transition into implementation planning. The final step in developing a smart grid strategy is to understand how the project will be executed. Utilities should begin implementation planning by asking the following key questions:

  • What is the project scope?
  • What are the key success factors?
  • What is the timeline to complete the project?
  • Which technologies do we implement first (priority/critical path)?
  • What resources are going to do the work? What can be done with internal employees vs. consultants and contractors?
  • What are the risks? How will we manage them?
  • What are the key integration points?
  • What are the competing priorities/projects?
  • Are there regulatory constraints?

A final question leadership may want to ask is "What is the largest non-core project the company has ever undertaken?" and "Why was this project successful/ unsuccessful?" Considering this will allow the utility to consider lessons learned and better understand their capacity for change.

Once these questions have been answered, the utility is ready to begin a smart grid deployment roadmap. The purpose of this roadmap is to lay out the key initiatives over the project timeline, noting the key dependencies and integration points. At this point, it is crucial to transition the organization from a strategy focus to an implementation focus. Current project leadership/sponsorship and functional SMEs should not be released from the project, but rather retained to assist with implementation planning and execution in new roles within the utility’s smart grid organization.

For a variety of reasons, a utility may decide not to immediately begin its smart grid implementation once the vision and strategy have been defined. All is not lost as this analysis helps to identify the key drivers, benefits, risks and obstacles associated with the smart grid program. This can be used as a baseline for future analysis or planning once the utility is ready to continue its smart grid journey.

Conclusion

Implementing a smart grid strategy and plan is an enterprise-transforming endeavor. It may be one of the most pervasive programs a utility has ever attempted. It will impact most every energy delivery organization/function; from operations to customer service and from procurement to human resources. The information technology/operations technology boundary will be crossed many times. Appropriate evaluation of the options and alignment with the company’s strategic goals and challenges is perhaps the most critical step in the smart grid journey. Strategic decisions should be based on rigorous analysis of internal and external aspects, and not an industry trend.

Shaping a New Era in Energy

In the last few years, the world has seen the energy & utilities business accelerate into a significant period of transformation as a result of the smart grid and related technologies. Today, with some early proponents leading the way, the industry is on the verge of a step-change improvement that some might even classify as a full-scale revolution. Utilities are viewed not only as being a critical link in solving the challenges we face related to climate change and the care of our planet’s energy resources, but they’re becoming enablers of growth and innovation – and even new products, services and jobs. Clearly the decisions the industry is making today around the world’s electricity networks will impact our lives for decades to come.

If the current economic environment has muted any enthusiasm for this transformation, it hasn’t been much. With the exception, perhaps, of plummeting oil prices temporarily providing some sense of calm in the sector, there are probably few people left who don’t believe the world needs to urgently address its clean, smart energy future. As of this writing, fledgling signs of an economic recovery are emerging, and along with it, increases in fossil fuel prices. As such, enthusiasm is growing over the debate about how countries will utilize billions in stimulus funding to enable the industry to achieve a new level of greatness.

There is a confluence of events helping us along this path of dramatic and beneficial change. IBM’s recent industry consumer survey (selected findings of which are featured in this publication in "Lighting the Way" by John Juliano) signals a future that is being shaped in part by a younger generation of digitally savvy people who care about – and are willing to participate in – our collective energy future. They willingly engage in more open communication with utility providers and tend to be better at understanding and controlling energy utilization.

As utilities instrument virtually all elements of the energy value chain from the power plant to the plug, they will improve service quality to these customers while reducing cost and improving reliability to a degree never before achievable. Customers engage because they see themselves as part of a larger movement to forestall the effects of climate change, or to battle price instability. This fully connected, instrumented energy ecosystem takes advantage of the data it collects, applying advanced analytics to enable real-time decisions on energy consumption. Some smart grid projects are already helping consumers save 10% of their bills, and reduce peak demand by 15%. Imagine the potential total savings when this is scaled to include companies, governments and educational institutions.

While positive new developments abound, they also are creating a highly complex environment, raising many difficult questions. For example, are families and businesses truly prepared to go on a "carbon diet" and will they stay on it? How will governments, with their increased stake in auto manufacturers, effectively and efficiently manage the transition toward PHEVs? Will industry players collaborate with one another to deal with stealth attacks on smart grids that are no longer the stuff of spy novels, but current realities we must face 24/7? How do we responsibly support the resurgence of nuclear-based power generation?

Matters of investment are also complex. Will there be sufficient public/private partnership to effectively stimulate investment in new businesses and models to profitably progress safe alternative energy forms such as solar, tidal, wind, geothermal and others? Will we have the "smarts" – and the financial commitment – to build more smarts into the reconstruction of ailing infrastructures?

Leading the Way

IBM has been a leading innovator in smart grid technology, significantly investing in energy and environmental programs designed to promote the use of intelligent energy worldwide. We created the Global Intelligent Utility Network Coalition, a strategic relationship with a small group of select utilities from around the world to shape, accelerate and share in the development of the smart grid. With the goal to lead industry organizations to smart grid transformation, we actively lead and participate in a host of global organizations including the GridWise® Alliance, Gridwise Architecture Council, EPRI’s Intelligrid program, and the World Energy Council, among others. By coming together around a shared vision of a smarter grid, we have an unprecedented opportunity to reshape the energy industry and our economic future.

The IBM experts who engage in these groups – along with the thousands of other IBMers working in the industry – have contributed significant thinking to the industry’s progress, not the least of which is the creation of the Smart Grid Maturity Model (SGMM) which has been handed over to the Carnegie Mellon Software Engineering Institute (SEI) for ongoing governance, growth and evolution of the model. Furthermore, the World Energy Council (WEC) has become a channel for the global dissemination of the model among its worldwide network of member committees.

IBM’s own Intelligent Utility Network (IUN) solution enables a utility to instrument everything from the meter in the home to miles of power lines to the network itself. In fact, the IUN looks a lot more like the Internet than a traditional grid. It can be interconnected to thousands of power sources – including climate-friendly ones – and its instrumentation generates new data for analysis, insight and intelligence that can be applied for the benefit of businesses and consumers alike.

Our deep integration skills, leading-edge technology, partner ecosystem and business and regulatory expertise have earned us roles in more than 50 smart grid projects around the globe with showcase projects in the U.S. Pacific Northwest, Texas, Denmark and Malta (See "The Smart Grid in Malta" by Carlo Drago in this publication) to name just a few. IBM also has a role in seven out of the world’s 10 largest advanced meter management projects.

The IBM Solution Architecture for Energy (SAFE), is a specialized industry framework focused on the management, maintenance, and integration of a utility’s assets and information, inclusive of generation, transmission and distribution, and customer operations. This is complemented by a world-class solution portfolio based on the most comprehensive breadth of hardware, software, consulting services, and open standards-based IT infrastructure that can be customized to meet the needs of today’s energy and utilities enterprises around the globe.

These activities are augmented by the renowned IBM Research organization that engages in both industry-specific and cross-industry research that influences our clients’ progress. This includes new computing models to handle the proliferation of end-user devices, sensor and actuators, connecting them with powerful back-end systems. How powerful? In the past year IBM’s Roadrunner supercomputer broke the "petaflop" barrier – one thousand trillion calculations per second using standard chip sets. Combined with advanced analytics and new computing models like "clouds" we’re turning mountains of data into intelligence, making systems like the smart grid more efficient, reliable and adaptive – in a word, smarter.

IBM Research also conducts First-of-a-Kind research – or FOAKs – in partnership with our clients, turning promising research into market-ready products and services. And our Industry Solution Labs around the world give IBM clients the chance to discover how leading-edge technologies and innovative solutions can be assembled and proven to help solve real business problems. For example, we’re exploring how to turn millions of future electric vehicles into a distributed storage system, and we maintain a Center of Excellence for Nuclear Power to improve design, safety analysis, operation, and nuclear modeling / simulation processes.

IBM is excited to be at the forefront of this changing industry – and our changing world. And we’re honored to be working closely with our clients and business partners in helping to evolve a smarter planet.

Thinking Smart

For more than 30 years, Newton- Evans Research Company has been studying the initial development and the embryonic and emergent stages of what the world now collectively terms the smart, or intelligent, grid. In so doing, our team has examined the technology behind the smart grid, the adoption and utilization rates of this technology bundle and the related market segments for more than a dozen or so major components of today’s – and tomorrow’s – intelligent grid.

This white paper contains information on eight of these key components of the smart grid: control systems, smart grid applications, substation automation programs, substation IEDs and devices, advanced metering infrastructure (AMI) and automated meter-reading devices (AMR), protection and control, distribution network automation and telecommunications infrastructure.

Keep in mind that there is a lot more to the smart grid equation than simply installing advanced metering devices and systems. A large AMI program may not even be the correct starting point for hundreds of the world’s utilities. Perhaps it should be a near-term upgrade to control center operations or to electronic device integration of the key substations, or an initial effort to deploy feeder automation or even a complete production and control (P&C) migration to digital relaying technology.

There simply is not a straightforward roadmap to show utilities how to develop a smart grid that is truly in that utility’s unique best interests. Rather, each utility must endeavor to take a step back and evaluate, analyze and plan for its smart grid future based on its (and its various stakeholders’) mission, its role, its financial and human resource limitations and its current investment in modern grid infrastructure and automation systems and equipment.

There are multiple aspects of smart grid development, some of which involve administrative as well as operational components of an electric power utility, and include IT involvement as well as operations and engineering; administrative management of customer information systems (CIS) and geographic information systems (GIS) as well as control center and dispatching operation of distribution and outage management systems (DMS and OMS); substation automation as well as true field automation; third-party services as well as in-house commitment; and of course, smart metering at all levels.

Space Station

I have often compared the evolution of the smart grid to the iterative process of building the international space station: a long-term strategy, a flexible planning environment, responsive changes incorporated into the plan as technology develops and matures, properly phased. What function we might need is really that of a skilled smart grid architect to oversee the increasingly complex duties of an effective systems planning organization within the utility organization.

All of these soon-to-be-interrelated activities need to be viewed in light of the value they add to operational effectiveness and operating efficiencies as well as the effect of their involvement with one another. If the utility has not yet done so, it must strive to adopt a systems-wide approach to problem solving for any one grid-related investment strategy. Decisions made for one aspect of control and automation will have an impact on other components, based on the accumulated 40 years of utility operational insights gained in the digital age.

No utility can today afford to play whack-a-mole with its approach to the intelligent grid and related investments, isolating and solving one problem while inadvertently creating another larger or more costly problem elsewhere because of limited visibility and “quick fix” decision making.

As these smart grid building blocks are put into service, as they become integrated and are made accessible remotely, the overall smart grid necessarily becomes more complex, more communications-centric and more reliant on sensor-based field developments.

In some sense, it reminds one of building the space station. It takes time. The process is iterative. One component follows another, with planning on a system-wide basis. There are no quick solutions. Everything must be very systematically approached from the outset.

Buckets of Spending

We often tackle questions about the buckets of spending for smart grid implementations. This is the trigger for the supply side of the smart grid equation. Suppliers are capable of developing, and will make the required R&D investment in, any aspect of transmission and distribution network product development – if favorable market conditions exist or if market outlooks can be supported with field research. Hundreds of major electric power utilities from around the world have already contributed substantially to our ongoing studies of smart grid components.

In looking at the operational/engineering components of smart grid developments, centering on the physical grid itself (whether a transmission grid, a distribution grid or both), one must include what today comprises P&C, feeder and switch automation, control center-based systems, substation measurement and automation systems, and other significant distribution automation activities.

On the IT and administrative side of smart grid development, one has to include the upgrades that will definitely be required in the near- or mid-term, including CIS, GIS, OMS and wide area communications infrastructure required as the foundation for automatic metering. Based on our internal estimates and those of others, spending for grid automation is pegged for 2008 at or slightly above $1 billion nationwide and will approach $3.5 billion globally. When (if) we add in annual spending for CIS, GIS, meter data management and communications infrastructure developments, several additional billions of dollars become part of the overall smart grid pie.

In a new question included in the 2008 Newton-Evans survey of control center managers, these officials were asked to check the two most important components of near-term (2008-2010) work on the intelligent grid. A total of 136 North American utilities and nearly 100 international utilities provided their comments by indicating their two most important efforts during the planning horizon.

On a summary basis, AMI led in mentions from 48 percent of the group. EMS/ SCADA investments in upgrades, new applications, interfaces et al was next, mentioned by 42 percent of the group. Distribution automation was cited by 35 percent as well.

Spending Outlook

The financial environment and economic outlook do not bode well for many segments of the national and global economies. One question we have continuously been asked well into this year is whether the electric power industry will suffer the fate of other industries and significantly scale back planned spending on T&D automation because of possible revenue erosion given the slowdown and fallout from this year’s difficult industrial and commercial environments.

Let’s first take a summary look at each of the five major components of T&D automation because these all are part and parcel of the operations/engineering view of the smart grid of the future.

Control Systems Outlook: Driven by SCADA-like systems and including energy management systems and distribution management software, this segment of the market is hovering around the $500 million mark on a global scale – excluding the values of turn-key control center projects (engineering, procurement and construction (EPC) of new control center facilities and communications infrastructure). We see neither growth nor erosion in this market for the near-term, with some up-tick in spending for new applications software and better visualization tools to compensate for the “aging” of installed systems. While not a control center-based system, outage management is a closely aligned technology development, and will continue to take hold in the global market. Sales of OMS software and platforms are already approaching the $100 million mark led by the likes of Oracle Utilities, Intergraph and MilSoft.

Substation Automation and Integration Programs: The market for substation IEDs, for new communications implementations and for integration efforts has grown to nearly $500 million. Multiyear programs aimed at upgrading, integrating and automating the existing global base of about a quarter million or so transmission and primary distribution substations have been underway for some time. Some programs have been launched in 2008 that will continue into 2011. We see a continuation of the growth in spending for critical substation A&I programs, albeit 2009 will likely see the slowest rate of growth in several years (less than 3 percent) if the current economic malaise holds up through the year. Continuing emphasis will be on HV transmission substations as the first priority for upgrades and addition of more intelligent electronic devices.

AMI/AMR: This is the lynchpin for the smart grid in the eyes of many industry observers, utility officials and perhaps most importantly, regulators at the state and federal levels of the U.S., Canada, Australia and throughout Western Europe. With nearly 1.5 billion electricity meters installed around the world, and about 93 percent being electro-mechanical, interest in smart metering can also be found in dozens of other countries, including Indonesia, Russia, Honduras, Malaysia, Australia, and Thailand. Another form of smart meters, the prepayment meter, is taking hold in some of the developing nations of the world. The combined resources of Itron, coupled with its Actaris acquisition, make this U.S. firm the global share leader in sales and installations of AMI and AMR systems and meters.

Protection and Control: The global market for protective relays, the foundation for P&C has climbed well above $1.5 billion. Will 2009 see a drop in spending for protective relays? Not likely, as these devices continue to expand in capabilities, and undertake additional functions (sequence of event recording, fault recording and analysis, and even acting as a remote terminal unit). To the surprise of many, there is still a substantial amount (perhaps as much as $125 million) being spent annually for electro-mechanical relays nearly 20 years into the digital relay era. The North American leader in protective relay sales to utilities is SEL, while GE Multilin continues to hold a leading share in industrial markets.

Distribution Automation: Today, when we discuss distribution automation, the topic can encompass any and all aspects of a distribution network automation scheme, from the control center-based SCADA and distribution management system on out to the substation, where RTUs, PLCs, power meters, digital relays, bay controllers and a myriad of communicating devices now help operate, monitor and control power flow and measurement in the medium voltage ranges.

Nonetheless, it is beyond the substation fence, reaching further down into the primary and secondary network, where we find reclosers, capacitors, pole top RTUs, automated overhead switches, automated feeders, line reclosers and associated smart controls. These are the new smart devices that comprise the basic building blocks for distribution automation. The objective will be achieved with the ability to detect and isolate faults at the feeder level, and enable ever faster service restoration. With spending approaching $1 billion worldwide, DA implementations will continue to expand over the coming decade, nearing $2.6 billion in annual spending by 2018.

Summary

The T&D automation market and the smart grid market will not go away this year, nor will it shrink. When telecommunications infrastructure developments are included, about $5 billion will have been spent in 2008 for global T&D automation programs. When AMI programs are adding into the mix, the total exceeds $7 billion. T&D automation spending growth will likely be subdued, perhaps into 2010. However, the overall market for T&D automation is likely to be propped up to remain at or near current levels of spending for 2009 and into 2010, benefiting from the continued regulatory-driven momentum for AMI/ AMR, renewable portfolio standards and demand response initiatives. By 2011, we should once again see healthier capital expenditure budgets, prompting overall T&D automation spending to reach about $6 billion annually. Over the 2008-2018 periods, we anticipate more than $75 billion in cumulative smart grid expenditures.

Expenditure Outlook

Newton-Evans staff has examined the current outlook for smart grid-related expenditures and has made a serious attempt to avoid double counting potential revenues from all of the components of information systems spending and the emerging smart grid sector of utility investment.

While the enterprise-wide IT portions (blue and red segments) of Figure 1 include all major components of IT (hardware, software, services and staffing), the “pure” smart grid components tend to be primarily in hardware, in our view. Significant overlap with both administrative and operational IT supporting infrastructure is a vital component for all smart grid programs underway at this time.

Between “traditional IT” and the evolving smart grid components, nearly $25 billion will likely be spent this year by the world’s electric utilities. Nearly one-third of all 2009 information technology investments will be “smart grid” related.

By 2013, the total value of the various pie segments is expected to increase substantially, with “smart grid” spending possibly exceeding $12 billion. While this amount is generally understood to be conservative, and somewhat lower than smart grid spending totals forecasted by other firms, we will stand by our forecasts, based on 31 years of research history with electric power industry automation and IT topics.

Some industry sources may include the total value of T&D capital spending in their smart grid outlook.

But that portion of the market is already approaching $100 billion globally, and will likely top $120 billion by 2013. Much of that market would go on whether or not a smart grid is involved. Clearly, all new procurements of infrastructure equipment will be made with an eye to including as much smart content as is available from the manufacturers and integrators.

What we are limiting our definition to is edge investment, the components of the 21st century digital transport and delivery systems being added on or incorporated into the building blocks (power transformers lines, switchgear, etc.) of electric power transmission and delivery.

The Smart Grid Maturity Model

The software industry has been using maturity models to define and measure software development capabilities for decades. These models have helped the industry create a shared vision for these capabilities. They also have driven individual software development organizations to set and pursue aggressive capabilities goals while allowing these groups to measure progress in reaching those objectives along the way.

As the utility industry embarks on the complex and ambitious transformation of the outdated power grid to the new smart grid, it has struggled to develop a shared vision for the smart grid end-state and the path to its development and deployment. Now, the smart grid maturity model (SGMM) is helping the industry overcome these challenges by presenting a consensus vision of the smart grid, the benefits it can bring and the various levels of smart grid development and deployment maturity. SGMM is helping numerous utilities worldwide develop targets for their smart grid strategy, and build roadmaps of the activities, investments and best practices that will lead them to their future smart grid state.

IBM worked closely with members of the Intelligent Utility Network Coalition (IUNC) to develop, discuss and revise several drafts of the SGMM. This team was assisted by APQC, a member-based nonprofit organization that provides benchmarking and best-practice research for approximately 500 organizations worldwide. The goal in the development process was to ensure the SGMM reflects a consensus industry vision for the smart grid, and brings together a wide range of industry experts to define the technical, organizational and process details supporting that vision.

APQC has a long history of benchmarking, performance measurement and maturity definition, and was therefore able to provide critical experience to drive development of a clear, measureable maturity model. IBM has worked on smart grid initiatives with numerous utilities around the world, and provided guidance and some initial structure to help start the development process. But the most important contributors to the SGMM were utilities themselves, as they brought a wealth of deep technical and strategic knowledge to build a shared vision of the smart grid and the various stages of maturity that could be achieved.

Because of this consensus development process, the SGMM reflects a broad industry vision for the smart grid, and it now gives utilities a tool for both strategic and tactical use to guide, measure and assess a utility’s smart grid transformation:

Strategic uses of the SGMM:

  • Establish a shared vision for the smart grid journey;
  • Communicate the smart grid vision, both internally and externally;
  • Use as a strategic framework for evaluating smart grid business and investment objectives;
  • Plan for technological, regulatory, and organizational readiness; and
  • Benchmark and learn from others

Tactical uses of the SGMM:

  • Guide development of a specific smart grid roadmap or blueprint;
  • Assess and prioritize current smart grid opportunities and projects;
  • Use as a decision-making framework for smart grid investments;
  • Assess resource needs to move from one smart grid level to another; and
  • Measure smart grid progress using key performance indicators (KPIs).

The SGMM structure is based on three fundamental concepts:

Domains: eight logical groupings of functional components of a smart grid transformation implementation;

Maturity Levels: five sets of defined characteristics and outcomes; and

Characteristics: descriptions of over 200 capabilities that are expected at each stage of the smart grid journey.

As Figure 1 shows, the domains span eight areas covering people, technology, and process, and comprise all of the fundamental components of smart grid capabilities.

Maturity levels range from an entry level of 1, up to a top level of 5, and can be summarized as follows:

Level 1 – Exploring and Initiating: contemplating smart grid transformation; may have a vision, but no strategy yet; exploring options; evaluating business cases and technologies; may have some smart grid elements already deployed.

Level 2 – Functional Investing: making decisions, at least at a functional level; business cases in place and investments being made; one or more functional deployments under way with value being realized; strategy in place.

Level 3 – Integrating Cross Functional: smart grid spreading; operational linkages established between two or more functional areas; management ensuring decisions span functional interests, resulting in cross-functional benefits.

Level 4 – Optimizing Enterprise-Wide: smart grid functionality and benefits realized; management and operational systems rely on and take full advantage of observability and integrated control, both across and between enterprise functions.

Level 5 – Innovating Next Wave of Improvements: new business, operational, environmental, and societal opportunities present themselves, and the capability exists to take advantage of them.

It is important to note that a utility may not choose to target maturity level 5 in every domain – in fact, it may not target level 5 for any domain. Instead, each utility using the SGMM must consider its own strategic direction and performance goals, and then decide on the levels of smart grid maturity that will support those goals to determine the target maturity in each domain. For example, a utility that is strategically focused on the retail side of the business may want to achieve relatively high maturity in the customer management and experience domain, but have a much lower target for maturity in the grid operations domain.

The key point is that the SGMM is not a report card with those utilities reaching the highest maturity levels "winning the game." Instead, each utility uses the SGMM to understand how the smart grid can help optimize its planning and investment to achieve its aspirations.

With over 200 characteristics describing the capabilities for each domain and maturity level, it is not possible to describe them here, but an example of a typical characteristic shown in Figure 2 provides a good sense of the level of detail in each characteristic of the SGMM.

Taken together, the domains, maturity levels, and characteristics form a detailed matrix that describes smart grid maturity across all critical areas.

Evaluating Smart Grid Maturity

A utility uses two surveys in conjunction with the SGMM structure described above to: assess its smart grid maturity; and track its progress and the resulting benefits during deployment. The first survey is the maturity assessment, which asks a series of about 40 questions that cover the current state of the utility’s smart grid strategy and spending, and the current penetration of smart grid capabilities into various areas of the business. The assessment yields a detailed report, providing the results for each domain, as well as higher-level reports that show the broader view of the utility’s current state and aspirations for the smart grid.

In this example, the utility’s current smart grid maturity is shown by the green circles, while its maturity aspirations are shown by the yellow circles. This highlevel view can be very useful as support for detailed plans on how to get from current state to aspirational state. It is also helpful for conveying maturity concepts and results to various stakeholders – both inside and outside the utility.

The second survey is the opportunity and results survey, which focuses on KPIs that track progress in smart grid deployment, as well as realization of the resulting benefits. For example, many questions in the survey cover grid operations, with the focus on cost, reliability and penetration of smart grid capabilities into the "daily life" of grid operations. The survey is expected to be completed annually, allowing each utility using the SGMM to track its deployment progress and benefits realization.

Using SGMM Results

The results from the SGMM can be applied in many ways to gauge a utility’s smart grid progress. From a practical management standpoint, the following important indicators can be derived directly from the SGMM process:

  • How the utility compares to other survey participants overall;
  • Where the utility has deficiencies in one domain that may adversely affect other domains;
  • Effects of being potentially projectoriented rather than program-driven, resulting in a jagged, "peaks and valleys" maturity profile with uneven advancement;
  • Indications that some domains are too far ahead of others, resulting in the risk of putting the "cart before the horse;" and
  • Confirmation of progress in domains that have been given particular focus by the utility, and indications of domains that may require increased focus.

More broadly, completion of the SGMM surveys provide a utility with the information needed to establish a shared smart grid vision with both internal and external stakeholders, mesh that vision with the utility’s overall business strategy to set maturity targets, and then build a detailed roadmap for closing the gaps between the current and target maturity levels.

Transition of SGMM Stewardship

IBM has been pleased to work with APQC and members of the IUNC to support definition and early roll-out of the SGMM. But as an important and evolving industry tool, IBM believes that the SGMM should be supported and maintained by a broader group. Therefore, we are planning to transition to a stewardship model with three organizations each playing a critical role:

  • Governance, Management, and Growth: the Carnegie Mellon Software Engineering Institute will govern the SGMM, working in conjunction with Carnegie Mellon University and the Carnegie Mellon Electricity Industry Center. The institute and its 500 employees will leverage its 20 years of experience as stewards of the Capability Maturity Model for software development.
  • Global Stakeholder Representation and Advocacy: the World Energy Council will provide representation for stakeholders around the globe. The council was established in 1923, represents 95 member countries and regularly hosts the World Energy Congress. Its mission is to promote the sustainable supply and use of energy for the greatest benefit of all people. This mission fits well with the development of the smart grid and the expanding use of the SGMM.
  • Data Collection and Reporting: APQC will provide further support for the SGMM survey process. With over 30 years of quality and process improvement research, APQC will continue the work it has done to date to assist utilities in assessing their smart grid maturity and tracking their progress during deployment.

Summary

All utilities should consider using the SGMM as they develop their vision for the smart grid and begin to plan and execute the projects that will take them on the journey. The SGMM represents the best strategic and technical thinking of a broad cross-section of the utility industry. We believe that the SGMM will continue to represent a thoughtful and consensus view as the smart grid – and the technology that supports it – evolves over the next few years.

At Your Service

Today’s utility companies are being driven to upgrade their aging transmission and distribution networks in the face of escalating energy generation costs, serious environmental challenges and rising demand for cleaner, distributed generation from both developing and digital economies worldwide.

The current utilities environment requires companies to drive down costs while increasing their ability to monitor and control utility assets. Yet, due to aging infrastructure, many utilities operate without the benefit of real-time usage and distribution loads – while also contending with limited resources for repair and improvement. Even consumers, with climate change on their minds, are demanding that utilities find more innovative ways to help them reduce energy consumption and costs.

One of the key challenges facing the industry is how to take advantage of new technologies to better manage customer service delivery today and into the future. While introducing this new technology, utilities must keep data and networks secure to be in compliance with critical infrastructure protection regulations. The concept of “service management” for the smart grid provides an approach for getting started.

A Smart Grid

A smart grid is created with new solutions that enable new business models. It brings together processes, technology and business partners, empowering utilities with an IP-enabled, continuous sensing network that overlays and connects a utility’s equipment, devices, systems, customers, partners and employees. A smart grid also enables on-demand access to data and information, which is used to better manage, automate and optimize operations and processes throughout the utility.

A utility relies on numerous systems, which reside both within and outside their physical boundaries. Common internal systems include: energy trading systems (ETS), customer information systems (CIS), supervisory control and data acquisition systems (SCADA), outage management systems (OMS), enterprise asset management (EAM); mobile workforce management systems (MWFM), geospatial information systems (GIS) and enterprise resource planning systems (ERP).

These systems are purchased from multiple vendors and often use a variety of protocols to communicate. In addition, utilities must interface with external systems – and often integrate all of them using a point-to-point model and establish connectivity on an as-needed basis. The point-to-point approach can result in numerous complex connections that need to be maintained.

Service Management

The key concept behind service management is the idea of managing assets, networks and systems to provide a “service,” as opposed to simply operating the assets. For example, Rolls Royce Civil Aerospace division uses this concept to sell “pounds of thrust” as a service. Critical to a utility’s operation is the ability to manage all facets of the services being delivered. Also critical to the operation of the smart grid are new solutions in advanced meter management (AMM), network automation and analytics, and EAM, including meter asset management.

A service management platform provides a way for utility companies to manage the services they deliver with their enterprise and information technology assets. It provides a foundation for managing the assets, their configuration, and the interrelationships key to delivering services. It also provides a means of defining workflow for the instantiation and management of the services being delivered. Underlying this platform is a range of tools that can assist in management of the services.

Gathering and analyzing data from advanced meters, network components, distribution devices, and legacy SCADA systems provides a solid foundation for automating service management. When combined with the information available in their asset management systems, utility companies can streamline operations and make more efficient use of valuable resources.

Advanced Reading

AMM centers on a more global view of the informational infrastructure, examining how automatic meter reading (AMR) and advanced metering infrastructure (AMI) integrate with other information systems to provide value-added benefits. It is important to note that for many utilities, AMM is considered to be a “green” initiative since it has the ability to influence customer usage patterns and, therefore, lower peak demand.

The potential for true business transformation exists through AMM, and adopting this solution is the first stage in a utility’s transformation to a more information-powered business model. New smart meters are network addressable, and along with AMM, are core components of the grid. Smart meters and AMM provide the capability to automatically collect usage data in near real time and to transport meter reads at regular intervals or on demand.

AMR/AMIs that aggregate their data in collection servers or concentrators, and expose it through an interface, can be augmented with event management products to monitor the meter’s health and operational status. Many organizations already deploy these solutions for event management within a network’s operations center environments, and for consolidated operations management as a top-level “manager of managers.”

A smart grid includes many devices other than meters, so event management can also be used to monitor the health of the rest of the network and IT equipment in the utility infrastructure. Integrating meter data with operations events gives network operations center operators a much broader view of a utility’s distribution system.

These solutions enable end-to-end data integration, from the meter collection server in a substation to the back-end helpdesk and billing applications. This approach can lead to improved speed and accuracy of data, while leveraging existing equipment and applications.

Network Automation and Analytics

Most utility companies use SCADA systems to collect data from sensors on the energy grid and send events to applications with SCADA interfaces. These systems collect data from substations, power plants and other control centers. They then process the data and allow for control actions to be sent back out. Energy management and distribution management systems typically provide additional features on top of SCADA, targeting either the transmission or distribution grids.

SCADA systems are often distributed on several servers (anywhere from two to 100) connected via a redundant local area network. The SCADA system, in turn, communicates with remote terminal units (RTUs), other devices, and other computer networks. RTUs reside in a substation or power plant, and are hardwired to other devices to bring back meaningful information such as current megawatts, amps, volts, pressure, open/closed or tripped. Distribution business units within a utility company also utilize SCADA systems to track low voltage applications, such as meters and pole drops, compared to the transmission business units’ larger assets, including towers, circuits and switchgear.

To facilitate network automation, IT solutions can help utilities to monitor and analyze data from SCADA systems in real time, monitor the computer network systems used to deploy SCADA systems, and better secure the SCADA network and applications using authentication software. An important element of service management is the use of automation to perform a wide range of actions to improve workfl ow efficiency. Another key ingredient is the use of service level agreements (SLAs) to give a business context for IT, enabling greater accountability to business user needs, and improving a utility’s ability to prioritize and optimize.

A smart grid includes a large number of devices and meters – millions in a large utility – and these are critical to a utility’s operations. A combination of IT solutions can be deployed to manage events from SCADA devices, as well as the IT equipment they rely on.

EAM For Utilities

Historically, many utility companies have managed their assets in silos. However, the emergence of the smart grid and smart meters, challenges of an aging workforce, an ever-demanding regulatory environment, and the availability of common IT architecture standards, are making it critical to standardize on one asset management platform as new requirements to integrate physical assets and IT assets arise (see Figure 1).

Today, utility companies are using EAM to manage work in gas and electric distribution operations, including construction, inspections, leak management, vehicles and facilities. In transmission and substation, EAM software is used for preventative and corrective maintenance and inspections.

EAM also helps track financial assets such as purchasing, depreciation, asset valuation and replacement costs. This solution helps integrate this data with ERP systems, and stores the history of asset testing and maintenance management. It integrates with GIS or other mapping tools to create geographic and spatial views of all distribution and smart grid assets.

Meter asset management is another area of increasing interest, as meters have an asset lifecycle similar to most other assets in a utility. Meter asset management involves tracking the meter from receipt to storeroom, to truck, to final location – as compared to managing the data the meter produces.

Now there is an IT asset management solution with the ability to manage meters as part of the IT network. This solution can be used to provision the meter, track configurations and provide service desk functionality. IT asset management solutions also have the ability to update meter firmware, and easily move and track the location and status of the assets over time in conjunction with a configuration database.

Reducing the number of truck rolls is another key focus area for utility companies. Using a combination of solutions, companies can:

  • Better manage the lifecycles of physical assets such as meters, meter cell relays, and broadband over powerline (BPL) devices to improve preventive maintenance;
  • Reconcile deployed asset information with information collected by meter data management systems;
  • Correlate the knowledge of physical assets with problems experienced with the IT infrastructure to better analyze a problem for root cause; and
  • Establish more efficient business process workflows and strengthen governance across a company.

Utilities are facing many challenges today and taking advantage of new technologies that will help better manage the delivery of service to customers tomorrow. The deployment of the smart grid and related solutions is a significant initiative that will be driving utilities for the next 10 years or more.

The concept of “service management” for the smart grid provides an approach for getting started. But these do not need to be tackled all at once. Utilities should develop a roadmap for the smart grid; each one will depend on specific priorities. But utilities don’t have to go it alone. The smart grid maturity model (SGMM) can enable a utility to develop a roadmap of activities, investments and best practices to ensure success and progress with available resources.