Modeling Distribution Demand Reduction

In the past, distribution demand reduction was a technique used only in emergency situations a few times a year – if that. It was an all-or-nothing capability that you turned on, and hoped for the best until the emergency was over. Few utilities could measure the effectiveness, let alone the potential of any solutions that were devised.

Now, demand reduction is evolving to better support the distribution network during typical peaking events, rather than just emergencies. However, in this mode, it is important not only to understand the solution’s effectiveness, but to be able to treat it like any other dispatchable load-shaping resource. Advanced modeling techniques and capabilities are allowing utilities to do just that. This paper outlines various methods and tools that allow utilities to model distribution demand reduction capabilities within set time periods, or even in near real time.

Electricity demand continues to outpace the ability to build new generation and apply the necessary infrastructure needed to meet the ever-growing, demand-side increases dictated by population growth and smart residences across the globe. In most parts of the world, electrical energy is one of the most important characteristics of a modern civilization. It helps produce our food, keeps us comfortable, and provides lighting, security, information and entertainment. In short, it is a part of almost every facet of life, and without electrical energy, the modern interconnected world as we know it would cease to exist.

Every country has one or more initiatives underway, or in planning, to deal with some aspect of generation and storage, delivery or consumption issues. Additionally, greenhouse gases (GHG) and carbon emissions need to be tightly controlled and monitored. This must be carefully balanced with expectations from financial markets that utilities deliver balanced and secure investment portfolios by demonstrating fiduciary responsibility to sustain revenue projections and measured growth.

The architects of today’s electric grid probably never envisioned the day when electric utility organizations would purposefully take measures to reduce the load on the network, deal with highly variable localized generation and reverse power flows, or anticipate a regulatory climate that impacts the decisions for these measures. They designed the electric transmission and distribution systems to be robust, flexible and resilient.

When first conceived, the electric grid was far from stable and resilient. It took growth, prudence and planning to continue the expansion of the electric distribution system. This grid was made up of a limited number of real power and reactive power devices that responded to occasional changes in power flow and demand. However, it was also designed in a world with far fewer people, with a virtually unlimited source of power, and without much concern or knowledge of the environmental effects that energy production and consumption entail.

To effectively mitigate these complex issues, a new type of electric utility business model must be considered. It must rapidly adapt to ever-changing demands in terms of generation, consumption, environmental and societal benefits. A grid made up of many intelligent and active devices that can manage consumption from both the consumer and utility side of the meter must be developed. This new business model will utilize demand management as a key element to the operation of the utility, while at the same time driving the consumer spending behavior.

To that end, a holistic model is needed that understands all aspects of the energy value chain across generation, delivery and consumption, and can optimize the solution in real time. While a unifying model may still be a number of years away, a lot can be gained today from modeling and visualizing the distribution network to gauge the effect that demand reduction can – and does – play in near real time. To that end, the following solutions are surely well considered.

Advanced Feeder Modeling

First, a utility needs to understand in more detail how its distribution network behaves. When distribution networks were conceived, they were designed primarily with sources (the head of the feeder and substation) and sinks (the consumers or load) spread out along the distribution network. Power flows were assumed to be one direction only, and the feeders were modeled for the largest peak level.

Voltage and volt-ampere reactive power (VAR) management were generally considered for loss optimization and not load reduction. There was never any thought given to limiting power to segments of the network or distributed storage or generation, all of which could dramatically affect the flow of the network, even causing reverse flows at times. Sensors to measure voltage and current were applied at the head of the feeder and at a few critical points (mostly in historical problem areas.)

Planning feeders at most utilities is an exercise performed when large changes are anticipated (i.e., a new subdivision or major customer) or on a periodic basis, usually every three to five years. Loads were traditionally well understood with predictable variability, so this type of approach worked reasonably well. The utility also was in control of all generation sources on the network (i.e., peakers), and when there was a need for demand reduction, it was controlled by the utility, usually only during critical periods.

Today’s feeders are much more complex, and are being significantly influenced by both generation and demand from entities outside the control of the utility. Even within the utility, various seemingly disparate groups will, at times, attempt to alter power flows along the network. The simple model of worst-case peaking on a feeder is not sufficient to understand the modern distribution network.

The following factors must be considered in the planning model:

  • Various demand-reduction techniques, when and where they are applied and the potential load they may affect;
  • Use of voltage reduction as a load-shedding technique, and where it will most likely yield significant results (i.e., resistive load);
  • Location, size and capacity of storage;
  • Location, size and type of renewable generation systems;
  • Use and location of plug-in electrical vehicles;
  • Standby generation that can be fed into the network;
  • Various social ecosystems and their characteristics to influence load; and
  • Location and types of sensors available.

Generally, feeders are modeled as a single unit with their power characteristic derived from the maximum peaking load and connected kilovolt-amperage (KVA) of downstream transformers. A more advanced model treats the feeder as a series of connected segments. The segment definitions can be arbitrary, but are generally chosen where the utility will want to understand and potentially control these segments differently than others. This may be influenced by voltage regulation, load curtailment, stability issues, distributed generation sources, storage, or other unique characteristics that differ from one segment to the next.

The following serves as an advanced means to model the electrical distribution feeder networks. It provides for segmentation and sensor placement in the absence of a complete network and historical usage model. The modeling combines traditional electrical engineering and power-flow modeling with tools such as CYME and non-traditional approaches using geospatial and statistical analysis.

The model builds upon information such as usage data, network diagrams, device characteristics and existing sensors. It then adds elements that could present a discrepancy with the known model such as social behavior, demand-side programs, and future grid operations based on both spatio-temporal and statistical modeling. Finally, suggestions can be made about sensors’ placement and characteristics to the network to support system monitoring once in place.

Generally, a utility would take a more simplistic view of the problem. It would start by directly applying statistical analysis and stochastic modeling across the grid to develop a generic methodology for selecting the number of sensors, and where to place them based on sensor accuracy, cost and risk-of-error introduction from basic modeling assumptions (load allocation, timing of peak demand, and other influences on error.) However, doing so would limit the utility, dealing only with the data it has in an environment that will be changing dramatically.

The recommended and preferred approach performs some analysis to determine what the potential error sources are, which source is material to the sensor question, and which could influence the system’s power flows. Next, an attempt can be made to geographically characterize where on the grid these influences are most significant. Then, a statistical approach can be applied to develop a model for setting the number, type and location of additional sensors. Lastly sensor density and placement can be addressed.

Feeder Modeling Technique

Feeder conditioning is important to minimize the losses, especially when the utility wants to moderate voltage levels as a load modification method. Without proper feeder conditioning and sufficient sensors to monitor the network, the utility is at risk of either violating regulatory voltage levels, or potentially limiting its ability to reduce the optimal load amount from the system during voltage reduction operations.

Traditionally, feeder modeling is a planning activity that is done at periodic (for example, yearly) intervals or during an expected change in usage. Tools such as CYME – CYMDIST provide feeder analysis using:

  • Balanced and unbalanced voltage drop analysis (radial, looped or meshed);
  • Optimal capacitor placement and sizing to minimize losses and/or improve voltage profile;
  • Load balancing to minimize losses;
  • Load allocation/estimation using customer consumption data (kWh), distribution transformer size (connected kVA), real consumption (kVA or kW) or the REA method. The algorithm treats multiple metering units as fixed demands; and large metered customers as fixed load;
  • Flexible load models for uniformly distributed loads and spot loads featuring independent load mix for each section of circuit;
  • Load growth studies for multiple years; and
  • Distributed generation.

However, in many cases, much of the information required to run an accurate model is not available. This is either because the data does not exist, the feeder usage paradigm may be changing, the sampling period does not represent a true usage of the network, the network usage may undergo significant changes, or other non-electrical characteristics.

This represents a bit of a chicken-or-egg problem. A utility needs to condition its feeders to change the operational paradigm, but it also needs operational information to make decisions on where and how to change the network. The solution is a combination of using existing known usage and network data, and combining it with other forms of modeling and approximation to build the best future network model possible.

Therefore, this exercise refines traditional modeling with three additional techniques: geospatial analysis; statistical modeling; and sensor selection and placement for accuracy.

If a distribution management system (DMS) will be deployed, or is being considered, its modeling capability may be used as an additional basis and refinement employing simulated and derived data from the above techniques. Lastly, if high accuracy is required and time allows, a limited number of feeder segments can be deployed and monitored to validate the various modeling theories prior to full deployment.

The overall goals for using this type of technique are:

  • Limit customer over or under voltage;
  • Maximize returned megawatts in the system in load reduction modes;
  • Optimize the effectiveness of the DMS and its models;
  • Minimize cost of additional sensors to only areas that will return the most value;
  • Develop automated operational scenarios, test and validation prior to system-wide implementation; and
  • Provide a foundation for additional network automation capabilities.

The first step starts by setting up a short period of time to thoroughly vet possible influences on the number, spacing and value offered by additional sensors on the distribution grid. This involves understanding and obtaining information that will most influence the model, and therefore, the use of sensors. Information could include historical load data, distribution network characteristics, transformer name plate loading, customer survey data, weather data and other related information.

The second step is the application of geospatial analysis to identify areas of the grid most likely to have influences driving a need for additional sensors. It is important to recognize that within this step is a need to correlate those influential geospatial parameters with load profiles of various residential and commercial customer types. This step represents an improvement over simply applying the same statistical analysis generically over the entirety of the grid, allowing for two or more “grades” of feeder segment characteristics for which different sensor standards would be developed.

The third step is the statistical analysis and stochastic modeling to develop recommended standards and methodology for determining sensor placement based on the characteristic segments developed from the geospatial assessment. Items set aside as not material for sensor placement serve as a necessary input to the coming “predictive model” exercise.

Lastly, a traditional electrical and accuracy- based analysis is used to model the exact number and placement of additional sensors to support the derived models and planned usage of the system for all scenarios depicted in the model – not just summertime peaking.

Conclusion

The modern distribution network built for the smart grid will need to undergo significantly more detailed planning and modeling than a traditional network. No one tool is suited to the task, and it will take multiple disciplines and techniques to derive the most benefit from the modeling exercise. However, if a utility embraces the techniques described within this paper, it will not only have a better understanding of how its networks perform in various smart grid scenarios, but it will be better positioned to fully optimize its networks for load and loss optimization.

Silver Spring Networks

When engineers built the national electric grid, their achievement made every other innovation built on or run by electricity possible – from the car and airplane to the radio, television, computer and the Internet. Over decades, all of these inventions have gotten better, smarter and cheaper while the grid has remained exactly the same. As a result, our electrical grid is operating under tremendous stress. The Department of Energy estimates that by 2030, demand for power will outpace supply by 30 percent. And this increasing demand for low-cost, reliable power must be met alongside growing environmental concerns.

Silver Spring Networks (SSN) is the first proven technology to enable the smart grid. SSN is a complete smart grid solutions company that enables utilities to achieve operational efficiencies, reduce carbon emissions and offer their customers new ways to monitor and manage their energy consumption. SSN provides hardware, software and services that allow utilities to deploy and run unlimited advanced applications, including smart metering, demand response, distribution automation and distributed generation, over a single, unified network.

The smart grid should operate like the Internet for energy, without proprietary networks built around a single application or device. In the same way that one can plug any laptop or device into the Internet, regardless of its manufacturer, utilities should be able to “plug in” any application or consumer device to the smart grid. SSN’s Smart Energy Network is based on open, Internet Protocol (IP) standards, allowing for continuous, two-way communication between the utility and every device on the grid – now and in the future.

The IP networking standard adopted by Federal agencies has proven secure and reliable over decades of use in the information technology and finance industries. This network provides a high-bandwidth, low-latency and cost-effective solution for utility companies.

SSN’s Infrastructure Cards (NICs) are installed in “smart” devices, like smart meters at the consumer’s home, allowing them to communicate with SSN’s access points. Each access point communicates with networked devices over a radius of one or two miles, creating a wireless communication mesh that connects every device on the grid to one another and to the utility’s back office.

Using the Smart Energy Network, utilities will be able to remotely connect or disconnect service, send pricing information to customers who can understand how much their energy is costing in real time, and manage the integration of intermittent renewable energy sources like solar panels, plug-in electric vehicles and wind farms.

In addition to providing The Smart Energy Network and the software/firmware that makes it run smoothly, SSN develops applications like outage detection and restoration, and provides support services to their utility customers. By minimizing or eliminating interruptions, the self-healing grid could save industrial and residential consumers over $100 billion per year.

Founded in 2002 and headquartered in Redwood City, Ca., SSN is a privately held company backed by Foundation Capital, Kleiner Perkins Caufield & Byers and Northgate Capital. The company has over 200 employees and a global reach, with partnerships in Australia, the U.K. and Brazil.

SSN is the leading smart grid solutions provider, with successful deployments with utilities serving 20 percent of the U.S. population, including Florida Power & Light (FPL), Pacific Gas & Electric (PG&E), Oklahoma Gas & Electric (OG&E) and Pepco Holdings, Inc. (PHI), among others.

FPL is one of the largest electric utilities in the U.S., serving approximately 4.5 million customers across Florida. In 2007, SSN and FPL partnered to deploy SSN’s Smart Energy Network to 100,000 FPL customers. It began with rigorous environmental and reliability testing to ensure that SSN’s technology would hold up under the harsh environmental conditions in some areas of Florida. Few companies are able to sustain the scale and quality of testing that FPL required during this deployment, including power outage notification testing, exposure to water and salt spray and network throughput performance test for self-healing failover characteristics.

SSN’s solution has met or exceeded all FPL acceptance criteria. FPL plans to continue deployment of SSN’s Smart Energy Network at a rate of one million networked meters per year beginning in 2010 to all 4.5 million residential customers.

PG&E is currently rolling out SSN’s Smart Energy Network to all 5 million electric customers over a 700,000 square-mile service area.

OG&E, a utility serving 770,000 customers in Oklahoma and western Arkansas, worked with SSN to deploy a small-scale pilot project to test The Smart Energy Network and gauge customer satisfaction. The utility deployed SSN’s network, along with an energy management web-based portal in 25 homes in northwest Oklahoma City. Another 6,600 apartments were given networked meters to allow remote initiation and termination of service.

Consumer response to the project was overwhelmingly positive. Participating residents said they gained flexibility and control over their household’s energy consumption by monitoring their usage on in-home touch screen information panels. According to one customer, “It’s the three A’s: awareness, attitude and action. It increased our awareness. It changed our attitude about when we should be using electricity. It made us take action.”

Based on the results, OG&E presented a plan for expanded deployment to the Oklahoma Corporation Commission for their consideration.

PHI recently announced its partnership with SSN to deliver The Smart Energy Network to its 1.9 million customers across Washington, D.C., Delaware, Maryland and New Jersey. The first phase of the smart grid deployment will begin in Delaware in March 2009 and involve SSN’s advanced metering and distribution automation technology. Additional deployment will depend on regulatory authorization.

The impact of energy efficiency is enormous. More aggressive energy efficiency efforts could cut the growth rate of worldwide energy consumption by more than half over the next 15 years, according to the McKinsey Global Institute. The Brattle Group states that demand response could reduce peak load in the U.S. by at least 5 percent over the next few years, saving over $3 billion per year in electricity costs. The discounted present value of these savings would be $35 billion over the next 20 years in the U.S. alone, with significantly greater savings worldwide.

Governments throughout the EU, Canada and Australia are now mandating implementation of alternate energy and grid efficiency network programs. The Smart Energy Network is the technology platform that makes energy efficiency and the smart grid possible. And, it is working in the field today.

Managing Communications Change

Change is being forced upon the utilities industry. Business drivers range from stakeholder pressure for greater efficiency to the changing technologies involved in operational energy networks. New technologies such as intelligent networks or smart grids, distribution automation or smart metering are being considered.

The communications network is becoming the key enabler for the evolution of reliable energy supply. However, few utilities today have a communications network that is robust enough to handle and support the exacting demands that energy delivery is now making.

It is this process of change – including the renewal of the communications network – that is vital for each utility’s future. But for the utility, this is a technological step change requiring different strategies and designs. It also requires new skills, all of which have been implemented in timescales that do not sit comfortably with traditional technology strategies.

The problems facing today’s utility include understanding the new technologies and assessing their capabilities and applications. In addition, the utility has to develop an appropriate strategy to migrate legacy technologies and integrate them with the new infrastructure in a seamless, efficient, safe and reliable manner.

This paper highlights the benefits utilities can realize by adopting a new approach to their customers’ needs and engaging a network partner that will take responsibility for the network upgrade, its renewal and evolution, and the service transition.

The Move to Smart Grids

The intent of smart grids is to provide better efficiency in the production, transport and delivery of energy. This is realized in two ways:

  • Better real-time control: ability to remotely monitor and measure energy flows more closely, and then manage those flows and the assets carrying them in real time.
  • Better predictive management: ability to monitor the condition of the different elements of the network, predict failure and direct maintenance. The focus is on being proactive to real needs prior to a potential incident, rather than being reactive to incidents, or performing maintenance on a repetitive basis whether it is needed or not.

These mechanisms imply more measurement points, remote monitoring and management capabilities than exist today. And this requires a greater reliance on reliable, robust, highly available communications than has ever been the case before.

The communications network must continue to support operational services independently of external events, such as power outages or public service provider failure, yet be economical and simple to maintain. Unfortunately, the majority of today’s utility communications implementations fall far short of these stringent requirements.

Changing Environment

The design template for the majority of today’s energy infrastructure was developed in the 1950s and 1960s – and the same is true of the associated communications networks.

Typically, these communications networks have evolved into a series of overlays, often of different technology types and generations (see Figure 1). For example, protection tends to use its own dedicated network. The physical realization varies widely, from tones over copper via dedicated time division multiplexing (TDM) connections to dedicated fiber connections. These generally use a mix of privately owned and leased services.

Supervisory control and data acquisitions systems (SCADA) generally still use modem technology at speeds between 300 baud to 9.6k baud. Again, the infrastructure is often copper or TDM running as one of many separate overlay networks.

Lastly, operational voice services (as opposed to business voice services) are frequently analog on yet another separate network.

Historically, there were good operational reasons for these overlays. But changes in device technology (for example, the evolution toward e-SCADA based on IP protocols), as well as the decreasing support by communications equipment vendors of legacy communications technologies, means that the strategy for these networks has to be reassessed. In addition, the increasing demand for further operational applications (for example, condition monitoring, or CCTV, both to support substation automation) requires a more up-to-date networking approach.

Tomorrow’s Network

With the exception of protection services, communications between network devices and the network control centers are evolving toward IP-based networks (see Figure 2). The benefits of this simplified infrastructure are significant and can be measured in terms of asset utilization, reduced capital and operational costs, ease of operation, and the flexibility to adapt to new applications. Consequently, utilities will find themselves forced to seriously consider the shift to a modern, homogeneous communications infrastructure to support their critical operational services.

Organizing For Change

As noted above, there are many cogent reasons to transform utility communications to a modern, robust communications infrastructure in support of operational safety, reliability and efficiency. However, some significant considerations should be addressed to achieve this transformation:

Network Strategy. It is almost inevitable that a new infrastructure will cross traditional operational and departmental boundaries within the utility. Each operational department will have its own priorities and requirements for such a network, and traditionally, each wants some, or total, control. However, to achieve real benefits, a greater degree of centralized strategy and management is required.

Architecture and Design. The new network will require careful engineering to ensure that it meets the performance-critical requirements of energy operations. It must maintain or enhance the safety and reliability of the energy network, as well as support the traffic requirements of other departments.

Planning, Execution and Migration. Planning and implementation of the core infrastructure is just the start of the process. Each service requires its own migration plan and has its own migration priorities. Each element requires specialist technical knowledge, and for preference, practical field experience.

Operation. Gone are the days when a communications failure was rectified by sending an engineer into the field to find the fault and to fix it. Maintaining network availability and robustness calls for sound operational processes and excellent diagnostics before any engineer or technician hits the road. The same level of robust centralized management tools and processes that support the energy networks have to be put in place to support communications network – no matter what technologies are used in the field.

Support. Although these technologies are well understood by the telecommunications industry, they are likely to be new to the energy utilities industry. This means that a solid support organization familiar with these technologies must be implemented. The evolution process requires an intense level of up-front skills and resources. Often these are not readily available in-house – certainly not in the volume required to make any network renewal or transformation effective. Building up this skill and resource base by recruitment will not necessarily yield staff that is aware of the peculiarities of the energy utilities market. As a result, there will be significant time lag from concept to execution, and considerable risk for the utility as it ventures alone into unknown territory.

Keys To Successful Engagement

Engaging a services partner does not mean ceding control through a rigid contract. Rather, it means crafting a flexible relationship that takes into consideration three factors: What is the desired outcome of the activity? What is the best balance of scope between partner assistance and in-house performance to achieve that outcome? How do you retain the flexibility to accommodate change while retaining control?

Desired outcome is probably the most critical element and must be well understood at the outset. For one utility, the desired outcome may be to rapidly enable the upgrade of the complete energy infrastructure without having to incur the upfront investment in a mass recruitment of the required new communications skills.

For other utilities, the desired outcome may be different. But if the outcomes include elements of time pressure, new skills and resources, and/or network transformation, then engaging a services partner should be seriously considered as one of the strategic options.

Second, not all activities have to be in scope. The objective of the exercise might be to supplement existing in-house capabilities with external expertise. Or, it might be to launch the activity while building up appropriate in-house resources in a measured fashion through the Build-Operate- Transfer (BOT) approach.

In looking for a suitable partner, the utility seeks to leverage not only the partner’s existing skills, but also its experience and lessons learned performing the same services for other utilities. Having a few bruises is not a bad thing – this means that the partner understands what is at stake and the range of potential pitfalls it may encounter.

Lastly, retaining flexibility and control is a function of the contract between the two parties which should be addressed in their earliest discussions. The idea is to put in place the necessary management framework and a robust change control mechanism based on a discussion between equals from both organizations. The utility will then find that it not only retains full control of the project without having to take day-to-day responsibility for its management, but also that it can respond to change drivers from a variety of sources – such as technology advances, business drivers, regulators and stakeholders.

Realizing the Benefits

Outsourcing or partnering the communications transformation will yield benefits, both tangible and intangible. It must be remembered that there is no standard “one-size-fits-all” outsourcing product. Thus, the benefits accrued will depend on the details of the engagement.

There are distinct tangible benefits that can be realized, including:

Skills and Resources. A unique benefit of outsourcing is that it eliminates the need to recruit skills not available internally. These are provided by the partner on an as-needed basis. The additional advantage for the utility is that it does not have to bear the fixed costs once they are no longer required.

Offset Risks. Because the partner is responsible for delivery, the utility is able to mitigate risk. For example, traditionally vendors are not motivated to do anything other than deliver boxes on time. But with a well-structured partnership, there is an incentive to ensure that the strategy and design are optimized to economically deliver the required services and ease of operation. Through an appropriate regime of business-related key performance indicators (KPIs), there is a strong financial incentive for the partner to operate and upgrade the network to maintain peak performance – something that does not exist when an in-house organization is used.

Economies of Scale. Outsourcing can bring the economies of scale resulting from synergies together with other parts of the partner’s business, such as contracts and internal projects.

There also are many other benefits associated with outsourcing that are not as immediately obvious and commercially quantifiable as those listed above, but can be equally valuable.

Some of these less tangible benefits include:

Fresh Point of View. Within most companies, employees often have a vested interest in maintaining the status quo. But a managed services organization has a vested interest in delivering the best possible service to the customer – a paradigm shift in attitude that enables dramatic improvements in performance and creativity.

Drive to Achieve Optimum Efficiency. Executives, freed from the day-to-day business of running the network, can focus on their core activities, concentrating on service excellence rather than complex technology decisions. To quote one customer, “From my perspective, a large amount of my time that might have in the past been dedicated to networking issues is now focused on more strategic initiatives concerned with running my business more effectively.”

Processes and Technologies Optimization. Optimizing processes and technologies to improve contract performance is part of the managed services package and can yield substantial savings.

Synergies with Existing Activities Create Economies of Scale. A utility and a managed services vendor have considerable overlap in the functions performed within their communications engineering, operations and maintenance activities. For example, a multi-skilled field force can install and maintain communications equipment belonging to a variety of customers. This not only provides cost savings from synergies with the equivalent customer activity, but also an improved fault response due to the higher density of deployed staff.

Access to Global Best Practices. An outsourcing contract relieves a utility of the time-consuming and difficult responsibility of keeping up to speed with the latest thinking and developments in technology. Alcatel-Lucent, for example, invests around 14 percent of its annual revenue into research and development; its customers don’t have to.

What Can Be Outsourced?

There is no one outsourcing solution that fits all utilities. The final scope of any project will be entirely dependent on a utility’s specific vision and current circumstances.

The following list briefly describes some of the functions and activities that are good possibilities for outsourcing:

Communications Strategy Consulting. Before making technology choices, the energy utility needs to define the operational strategy of the communications network. Too often communications is viewed as “plug and play,” which is hardly ever the case. A well-thought-out communications strategy will deliver this kind of seamless operation. But without that initial strategy, the utility risks repeating past mistakes and acquiring an ad-hoc network that will rapidly become a legacy infrastructure, which will, in turn, need replacing.

Design. Outsourcing allows utilities to evolve their communications infrastructure without upfront investment in incremental resources and skills. It can delegate responsibility for defining network architecture and the associated network support systems. A utility may elect to leave all technological decisions to the vendor and merely review progress and outcomes. Or, it may retain responsibility for technology strategy, and turn to the managed services vendor to turn the strategy into architecture and manage the subsequent design and project activities.

Build. Detailed planning of the network, the rollout project and the delivery of turnkey implementations all fall within the scope of the outsourcing process.

Operate, Administer and Maintain. Includes network operations and field and support services:

  • Network Operations. A vendor such as Alcatel-Lucent has the necessary experience in operating Network Operations Centers (NOCs), both on a BOT and ongoing basis. This includes handling all associated tasks such as performance and fault monitoring, and services management.
  • Network and Customer Field Services. Today, few energy utilities consider outside maintenance and provisioning activities to be a strategic part of their business and recognize they are prime candidates for outsourcing. Activities that can be outsourced include corrective and preventive maintenance, network and service provisioning, and spare parts management, return and repair – in other words, all the daily, time-consuming, but vitally important elements for running a reliable network.
  • Network Support Services. Behind the first-line activities of the NOC are a set of engineering support functions that assist with more complex faults – these are functions that cannot be automated and tend to duplicate those of the vendor’s. The integration and sharing of these functions enabled by outsourcing can significantly improve the utility’s efficiency.

Conclusion

Outsourcing can deliver significant benefits to a utility, both in terms of its ability to invest in and improve its operation and associated costs. However, each utility has its own unique circumstances, specific immediate needs, and vision of where it is going. Therefore, each technical and operational solution is different.

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.

Empowering the Smart Grid

Trilliant is the leader in delivering intelligent networks that power the smart grid. Trilliant provides hardware, software and service solutions that deliver on the promise of Advanced Metering and Smart Grid to utilities and their customers, including improved energy efficiency, grid reliability, lower operating cost, and integration of renewable energy resources.

Since its founding in 1985, the company has been a leading innovator in the delivery and implementation of advanced metering infrastructure (AMI), demand response and grid management solutions, in addition to installation, program management and meter revenue cycle services. Trilliant is focused on enabling choice for utility companies, ranging from meter, network and IT infrastructures to full or hybrid outsource models.

Solutions

Trilliant provides fully automated, two-way wireless network solutions and software for smart grid applications. The company’s smart grid communications solutions enable utilities to create a more efficient and robust operational infrastructure to:

  • Read meters on demand with five minute or less intervals;
  • Improve cash flow;
  • Improve customer service;
  • Decrease issue resolution time;
  • Verify outages and restoration in real time;
  • Monitor substation equipment;
  • Perform on/off cycle reads;
  • Conduct remote connect/disconnect;
  • Significantly reduce/eliminate energy theft through tamper detection; and
  • Realize accounting/billing improvements.

Trilliant solutions also enable the introduction of services and programs such as:

  • Dynamic demand response; and
  • Time-of-use (TOU), critical peak pricing (CPP) and other special tariffs and related metering.

Solid Customer Base

Trilliant has secured contracts for more than three million meters to be supported by its network solutions and services, encompassing both C&I and residential applications. The company has delivered products and services to more than 200 utility customers, including Duke Energy, E.ON US (Louisville Gas & Electric), Hydro One, Hydro Quebec, Jamaica Public Service Company Ltd., Milton Hydro, Northeast Utilities, PowerStream, Public Service Gas & Electric, San Diego Gas & Electric, Toronto Hydro Electric System Ltd., and Union Gas, among others.

Helping North American Utilities Transform the Way They Do Business

Utilities are facing a host of challenges ranging from environmental concerns, aging infrastructure and systems, to Smart Grid technology and related program decisions. The future utility will be required to find effective solutions to these challenges, while continuing to meet the increasing expectations of newly empowered consumers. This brings an opportunity to create stronger, more profitable relationships with customers, and to do so more cost effectively.

Since our formation in 1996 as the subsidiary of UK-based United Utilities Plc., Vertex Business Services has grown to serve over 70 North American utilities and retail energy clients, who in turn serve over 23 million end-use customers. Our broad portfolio of Business Process Outsourcing (BPO) and Information Technology (IT) solutions enables our clients to more effectively manage operational costs, improve efficiencies, develop front-line employees, and achieve superior customer experience.

Improving Utility Collection Performances

Utilities can greatly benefit from the debt management practices and experience of industries such as banking and retail that have developed a more sophisticated skill set. Benefits can come from adoption of proven methodologies for managing accounts receivable and managing outsourced agency collections business processes, as well as from the use of appropriate software for these processes. There is also benefit to using analytical tools to evaluate the process of collections and optimizing processes based on metrics collected.

Improve your collection rates and lower outstanding accounts receivable through Vertex’s proven collection services. Our rich heritage results in our ability to implement best practices and provide quality reporting strategies, ironclad credit and collection processes, and innovative training programs.

Handling Demand Response and Efficiency In the Call Center

In the next five to 10 years, utilities will be forced to change more than at any time in their previous history. These changes will be profound, widespread and will affect not only utilities themselves, but virtually all parts of our modern electrified culture. One of the most dramatic changes will be in the traditional relationship between utilities and their customers, especially at the residential level. Passive electricity "rate payers" are about to become very active participants in the relationship with their utility.

Smart Metering Options for Electric and Gas Utilities

Should utilities replace current consumption meters with “smart metering” systems that provide more information to both utilities and customers? Increasingly, the answer is yes. Today, utilities and customers are beginning to see the advantages of metering systems that provide:

  • Two-way communication between the utility and the meter; and
  • Measurement that goes beyond a single consolidated quarterly or monthly consumption total to include time-of-use and interval measurement.

For many, “smart metering” is synonymous with an advanced metering infrastructure (AMI) that collects, processes and distributes metered data effectively across the entire utility as well as to the customer base (Figure 1).

SMART METERING REVOLUTIONIZES UTILITY REVENUE AND SERVICE POTENTIAL

When strategically evaluated and deployed, smart metering can deliver a wide variety of benefits to utilities.

Financial Benefits

  • Significantly speeds cash flow and associated earnings on revenue. Smart metering permits utilities to read meters and send the data directly to the billing application. Bills go out immediately, cutting days off the meter-to-cash cycle.
  • Improves return on investment via faster processing of final bills. Customers can request disconnects as the moving van pulls away. Smart metering polls the meter and gives the customer the amount of the final bill. Online or credit card payments effectively transform final bill collection cycles from a matter of weeks to a matter of seconds.
  • Reduces bad debt. Smart metering helps prevent bad debt by facilitating the use of prepayment meters. It also reduces the size of overdue bills by enabling remote disconnects, which do not depend on crew availability.

Operational Cost Reductions

  • Slashes the cost to connect and disconnect customers. Smart metering can virtually eliminate the costs of field crews and vehicles previously required to change service from the old to the new residents of a metered property.
  • Lowers insurance and legal costs. Field crew insurance costs are high – and they’re even higher for employees subject to stress and injury while disconnecting customers with past-due bills. Remote disconnects through smart metering lower these costs. They also reduce medical leave, disability pay and compensation claims. Remote disconnects also significantly cut the number of days that employees and lawyers spend on perpetrator prosecutions and attempts to recoup damages.
  • Cuts the costs of managing vegetation. Smart metering can pinpoint blinkouts, reducing the cost of unnecessary tree trimming.
  • Reduces grid-related capital expenses. With smart metering, network managers can analyze and improve block-by-block power flows. Distribution planners can better size transformers. Engineers can identify and resolve bottlenecks and other inefficiencies. The benefits include increased throughput and reductions in grid overbuilding.
  • Shaves supply costs. Supply managers use interval data to fine-tune supply portfolios. Because smart metering enables more efficient procurement and delivery, supply costs decline.
  • Cuts fuel costs. Many utility service calls are “false alarms.” Checking meter status before dispatching crews prevents many unnecessary truck rolls. Reduces theft. Smart metering can identify illegal attempts to reconnect meters, or to use energy and water in supposedly vacant premises. It can also detect theft by comparing flows through a valve or transformer with billed consumption.

Compliance Monitoring

  • Ensures contract compliance. Gas utilities can use one-hour interval meters to monitor compliance from interruptible, or “non-core,” customers and to levy fines against contract violators.
  • Ensures regulatory compliance. Utilities can monitor the compliance of customers with significant outdoor lighting by comparing similar intervals before and during a restricted time period. For example, a jurisdiction near a wildlife area might order customers to turn off outdoor lighting so as to promote breeding and species survival.
  • Reduces outage duration by identifying outages more quickly and pinpointing outage and nested outage locations. Smart metering also permits utilities to ensure outage resolution at every meter location.
  • Sizes outages more accurately. Utilities can ensure that they dispatch crews with the skills needed – and adequate numbers of personnel – to handle a specific job.
  • Provides updates on outage location and expected duration. Smart metering helps call centers inform customers about the timing of service restoration. It also facilitates display of outage maps for customer and public service use.
  • Detect voltage fluctuations. Smart metering can gather and report voltage data. Customer satisfaction rises with rapid resolution of voltage issues.

New Services

For utilities that offer services besides commodity delivery, smart metering provides an entry to such new business opportunities as:

  • Monitoring properties. Landlords reduce costs of vacant properties when utilities notify them of unexpected energy or water consumption. Utilities can perform similar services for owners of vacation properties or the adult children of aging parents.
  • Monitoring equipment. Power-use patterns can reveal a need for equipment maintenance. Smart metering enables utilities to alert owners or managers to a need for maintenance or replacement.
  • Facilitating home and small-business networks. Smart metering can provide a gateway to equipment networks that automate control or permit owners to access equipment remotely. Smart metering also facilitates net metering, offering some utilities a path toward involvement in small-scale solar or wind generation.

Environmental Improvements

Many of the smart metering benefits listed above include obvious environmental benefits. When smart metering lowers a utility’s fuel consumption or slows grid expansion, cleaner air and a better preserved landscape result. Smart metering also facilitates conservation through:

  • Leak detection. When interval reads identify premises where water or gas consumption never drops to zero, leaks are an obvious suspect.
  • Demand response and critical peak pricing. Demand response encourages more complete use of existing base power. Employed in conjunction with critical peak pricing, it also reduces peak usage, lowering needs for new generators and transmission corridors.
  • Load control. With the consent of the owner, smart metering permits utilities or other third parties to reduce energy use inside a home or office under defined circumstances.

CHALLENGES IN SMART METERING

Utilities preparing to deploy smart metering systems need to consider these important factors:

System Intelligence. There’s a continuing debate in the utility industry as to whether smart metering intelligence should be distributed or centralized. Initial discussions of advanced metering tended to assume intelligence embedded in meters. Distributed intelligence seemed part of a trend, comparable to “smart cards,” “smart locks” and scores of other everyday devices with embedded computing power.

Today, industry consensus favors centralized intelligence. Why? Because while data processing for purposes of interval billing can take place in either distributed or central locations, other applications for interval data and related communications systems cannot. In fact, utilities that opt for processing data at the meter frequently make it impossible to realize a number of the benefits listed above.

Data Volume. Smart metering inevitably increases the amount of meter data that utilities must handle. In the residential arena, for instance, using hour-long measurement intervals rather than monthly consumption totals replaces 12 annual reads per customer with 8,760 reads – a 730-fold increase.

In most utilities today, billing departments “own” metering data. Interval meter reads, however, are useful to many departments. These readings can provide information on load size and shape – data that can then be analyzed to help reduce generation and supply portfolio costs. Interval reads are even more valuable when combined with metering features like two-way communication between meter and utility, voltage monitoring and “last gasp” messages that signal outages.

This new data provides departments outside billing with an information treasure trove. But when billing departments control the data, others frequently must wait for access lest they risk slowing down billing to a point that damages revenue flow.

Meter Data Management. An alternative way to handle data volume and multiple data requests is to offload it into a stand-alone meter data management (MDM) application.

MDM applications gather and store meter data. They can also perform the preliminary processing required for different departments and programs. Most important, MDM gives all units equal access to commonly held meter data resources (Figure 2).

MDM provides an easy pathway between data and the multiple applications and departments that need it. Utilities can more easily consolidate and integrate data from multiple meter types, and reduce the cost of building and maintaining application interfaces. Finally, MDM provides a place to store and use data, whose flow into the system cannot be regulated – for example, in situations such as the flood of almost simultaneous messages from tens of thousands of meters sending a “last gasp” during a major outage.

WEIGHING THE COSTS AND BENEFITS OF SMART METERING

Smart metering on a mass scale is relatively new. No utility can answer all questions in advance. There are ways, however, to mitigate the risks:

Consider all potential benefits. Smart metering may be a difficult cost to justify if it rests solely on customer acceptance of demand response. Smart metering is easier to cost-justify when its deployment includes, for instance, the value of the many benefits listed above.

Evaluate pilots. Technology publications are full of stories about successful pilots followed by unsuccessful products. That’s because pilots frequently protect participants from harsh financial consequences. And it’s difficult for utility personnel to avoid spending time and attention on participants in ways that encourage them to buy into the program. Real-life program rollouts lack these elements.

Complicating the problem are likely differences between long-term and short-term behavior. The history of gasoline conservation programs suggests that while consumers initially embrace incentives to car pool or use public transportation, few make such changes on a permanent basis.

Examining the experiences of utilities in the smart metering forefront – in Italy, for example, or in California and Idaho – may provide more information than a pilot.

Develop a complete business case. Determining the cost-benefit ratio of smart metering is challenging. Some costs – for example, meter prices and installation charges – may be relatively easy to determine. Others require careful calculations. As an example, when interval meters replace time-of-use meters, how does the higher cost of interval meters weigh against the fact that they don’t require time-of-use manual reprogramming?

As in any business case, some costs must be estimated:

  • Will customer sign-up equal the number needed to break even?
  • How long will the new meters last?
  • Do current meter readers need to be retrained, and if so, what will that cost?
  • Will smart metering help retain customers that might otherwise be lost?
  • Can new services such as equipment efficiency analyses be offered, and if so, how much should the utility charge for them?

Since some utilities are already rolling out smart metering programs, it’s becoming easier to obtain real-life numbers (rather than estimates) to plug into your business case.

CONSIDER ALTERNATIVES

Technology is “smart” only when it reduces the cost of obtaining specified objectives. Utilities may find it valuable to try lower-cost routes to some results, including:

  • Customer charges to prevent unnecessary truck rolls. Such fees are common among telephone service providers and have worked well for some gas utilities responding to repeated false alarms from householder-installed carbon monoxide detectors.
  • Time-of-use billing with time/rate relationships that remain constant for a year or more. This gives consumers opportunities to make time-shifting a habit.
  • Customer education to encourage consumers to use the time-shifting features on their appliances as a contribution to the environment. Most consumers have no idea that electricity goes to waste at night. Keeping emissions out of the air and transmission towers out of the landscape could be far more compelling to many consumers than a relatively small saving resulting from an on- and off-peak pricing differential.
  • Month-to-month rate variability. One study found that approximately a third of the efficiency gains from real-time interval pricing could be captured by simply varying the flat retail rates monthly – and at no additional cost for metering. [1] While a third of the efficiency gains might not be enough to attain long-term goals, they might be enough to fill in a shorter-term deficit, permitting technology costs and regulatory climates to stabilize before decisions must be made.
  • Multitier pricing based on consumption. Today, two-tier pricing – that is, a lower rate for the first few-hundred kilowatt-hours per month and a higher rate for additional hours – is common. However, three or four tiers might better capture the attention of those whose consumption is particularly high – owners of large homes and pool heaters, for instance – without burdening those at the lower end of the economic ladder. Tiers plus exception handling for hardships like high-consuming medical equipment would almost certainly be less difficult and expensive than universal interval metering.

A thorough evaluation of the benefits and challenges of advanced metering systems, along with an understanding of alternative means to achieving those benefits, is essential to utilities considering deployment of advanced metering systems.

Note: The preceding was excerpted from the Oracle white paper “Smart Metering for Electric and Gas Utilities.” To receive the complete paper, Email oracleutilities_ww@oracle.com.

ENDNOTE

  1. Holland and Mansur, “The Distributional and Environmental Effects of Time-varying Prices in Competitive Electricity Markets.” Results published in “If RTP Is So Great, Why Don’t We See More of It?” Center for the Study of Energy Markets Research Review, University of California Energy Institute, Spring 2006. Available at www.ucei.berkeley.edu/

Trilliant: Advanced Metering Infrastructure Solutions for Utilities and Green Energy Markets

Trilliant Incorporated provides wireless network solutions and software for advanced metering, demand response, smart grid and submetering. With more than 20 years’ experience solving utility meter communications needs, the company empowers flexibility and choice through the adoption and integration of open standards-based technologies.

ADVANCED METERING

Trilliant SecureMesh™ AMI solutions enable utilities to introduce services and programs such as time-of-use (TOU) metering, CIS initiated real-time meter reads and customer disconnect/ reconnect. These programs are transforming the traditional customer-utility relationship through interval-based consumption data and two-way messaging, resulting in reduced operational costs and improved reliability.

DEMAND RESPONSE

Many utilities are initiating smart metering and AMI programs with a primary goal of ad dressing critical peak demand challenges using TOU pricing, critical peak pricing and demand response programs. Trilliant is the first AMI supplier to provide an open standards-based platform for AMI-integrated demand response (i.e., load control) incorporating smart thermostats – and thus air conditioning equipment – and other loads such as pool pumps and water heaters. The Trilliant Demand Response solution also supports in-premise (“in-home”) displays that offer consumers real-time information on energy usage and utility-initiated messages.

SMART GRID

By leveraging Smart Grid solutions from Trilliant, utilities can realize dramatic improvements in system performance and cost. System operational challenges such as outage detection and restoration verification are supported through a combination of network-based intelligence and operations center applications. Trilliant’s Smart Grid solutions enable operations to more effectively identify faults and rapidly restore service on the basis of real-time readings of on-premise conditions. These offerings may also be integrated with extended enterprise systems supporting the mobile field force. Smart Grid solutions from Trilliant provide the foundation for advanced applications such as utility asset life cycle management and others that can benefit from the use of actual loading data.

SUBMETERING

Trilliant Energy Services offerings include turnkey submetering solutions, utility data profiling and online presentment to meet the needs of electric and natural gas utilities. Because Trilliant is an expert in energy technology the company’s solutions offer benefits to all stakeholders – from condo developers and corporations to owners and managers and directly to residential suite owners.

Real-Time Automation Solutions for Operation of Energy Assets and Markets

Areva T&D offers solutions to bring electricity from the source to end-users, building high- and medium-voltage substations and develops technologies to manage power grids and energy markets worldwide. It is a full-fl edged solution provider, offering safe, reliable, efficient power distribution down to the lowest level end-user consumption. Its software applications cover all the strategic operational business processes of an energy utility, including optimization of transmission and distribution grid operation; management of wholesale and retail market operations; and energy transaction solutions involving strategic business processes from energy trading, energy scheduling and dispatch management to demand-side management and settlements.

As long as advanced monitoring and control infrastructures have been used for grid management, Areva T&D has been at the forefront of innovation. Its strategy has always been to supply the most accurate real-time vision of the network infrastructure. This has led to several major breakthroughs, including Areva’s latest e-terraVision™ product.

The e-terraVision technology provides control rooms with higher level decision support capabilities through visualization tools, “smart applications” and simulation – thus improving situation awareness. This operator-friendly system enables power dispatchers to fully visualize their networks with the right level of situation awareness and proactively operate the grid by taking the necessary real-time corrective actions.

Expertise acquired in the high-voltage network enables Areva to supply distribution monitoring and control applications as well, and these have greatly influenced its distribution management strategy. As a result of early successes, the company developed an adapted eterra product offer for distribution customers.

Areva T&D continues to integrate unique new concepts to meet market trends and innovation. For example, Areva T&D SmartGrid solutions are designed to supply the following benefits.

  1. Alignment with deregulation trends in the consumer electricity market, including:
    • Making the process of changing energy supplier easier;
    • Providing better service quality for energy usage, including accurate and appropriate billing of actual consumed energy;
    • For specific countries where nontechnical losses are significant, allowing accurate audits to be conducted; and
    • Allowing for differentiated energy offerings with greater pricing flexibility and integration of renewable energy offers.
  2. Support for further structural benefits discussed and validated as part of international working groups on SmartGrid initiatives:
    • Better selectivity of the IEDs in medium- and low-voltage leads to reduce the number of customers affected by outages, thus improving service quality and reducing maintenance costs.
    • Careful monitoring of low-voltage grids, including consumption by phase and distribution cell – which is especially relevant in terms of renewable energy generation.
    • Online asset monitoring, which enables predictive maintenance, thus increasing assets’ life span.
    • Dynamic security management of primary and secondary networks. Introducing renewable energy sources into the distribution network poses a challenge. Combined infrastructures for monitoring systems for distribution and metering will be needed in the near future.

All these challenges have driven the definition and development of Areva SmartGrid solutions. The company’s enhanced supervision and control center products, including smart metering, supply all the advantages of automation technologies to distribution networks.

Achieving Decentralized Coordination In the Electric Power Industry

For the past century, the dominant business and regulatory paradigms in the electric power industry have been centralized economic and physical control. The ideas presented here and in my forthcoming book, Deregulation, Innovation, and Market Liberalization: Electricity Restructuring in a Constantly Evolving Environment (Routledge, 2008), comprise a different paradigm – decentralized economic and physical coordination – which will be achieved through contracts, transactions, price signals and integrated intertemporal wholesale and retail markets. Digital communication technologies – which are becoming ever more pervasive and affordable – are what make this decentralized coordination possible. In contrast to the “distributed control” concept often invoked by power systems engineers (in which distributed technology is used to enhance centralized control of a system), “decentralized coordination” represents a paradigm in which distributed agents themselves control part of the system, and in aggregate, their actions produce order: emergent order. [1]

Dynamic retail pricing, retail product differentiation and complementary end-use technologies provide the foundation for achieving decentralized coordination in the electric power industry. They bring timely information to consumers and enable them to participate in retail market processes; they also enable retailers to discover and satisfy the heterogeneous preferences of consumers, all of whom have private knowledge that’s unavailable to firms and regulators in the absence of such market processes. Institutions that facilitate this discovery through dynamic pricing and technology are crucial for achieving decentralized coordination. Thus, retail restructuring that allows dynamic pricing and product differentiation, doesn’t stifle the adoption of digital technology and reduces retail entry barriers is necessary if this value-creating decentralized coordination is to happen.

This paper presents a case study – the “GridWise Olympic Peninsula Testbed Demonstration Project” – that illustrates how digital end-use technology and dynamic pricing combine to provide value to residential customers while increasing network reliability and reducing required infrastructure investments through decentralized coordination. The availability (and increasing cost-effectiveness) of digital technologies enabling consumers to monitor and control their energy use and to see transparent price signals has made existing retail rate regulation obsolete. Instead, the policy recommendation that this analysis implies is that regulators should reduce entry barriers in retail markets and allow for dynamic pricing and product differentiation, which are the keys to achieving decentralized coordination.

THE KEYS: DYNAMIC PRICING, DIGITAL TECHNOLOGY

Dynamic pricing provides price signals that reflect variations in the actual costs and benefits of providing electricity at different times of the day. Some of the more sophisticated forms of dynamic pricing harness the dramatic improvements in information technology of the past 20 years to communicate these price signals to consumers. These same technological developments also give consumers a tool for managing their energy use, in either manual or automated form. Currently, with almost all U.S. consumers (even industrial and commercial ones) paying average prices, there’s little incentive for consumers to manage their consumption and shift it away from peak hours. This inelastic demand leads to more capital investment in power plants and transmission and distribution facilities than would occur if consumers could make choices based on their preferences and in the face of dynamic pricing.

Retail price regulation stifles the economic processes that lead to both static and dynamic efficiency. Keeping retail prices fixed truncates the information flow between wholesale and retail markets, and leads to inefficiency, price spikes and price volatility. Fixed retail rates for electric power service mean that the prices individual consumers pay bear little or no relation to the marginal cost of providing power in any given hour. Moreover, because retail prices don’t fluctuate, consumers are given no incentive to change their consumption as the marginal cost of producing electricity changes. This severing of incentives leads to inefficient energy consumption in the short run and also causes inappropriate investment in generation, transmission and distribution capacity in the long run. It has also stifled the implementation of technologies that enable customers to make active consumption decisions, even though communication technologies have become ubiquitous, affordable and user-friendly.

Dynamic pricing can include time-of-use (TOU) rates, which are different prices in blocks over a day (based on expected wholesale prices), or real-time pricing (RTP) in which actual market prices are transmitted to consumers, generally in increments of an hour or less. A TOU rate typically applies predetermined prices to specific time periods by day and by season. RTP differs from TOU mainly because RTP exposes consumers to unexpected variations (positive and negative) due to demand conditions, weather and other factors. In a sense, fixed retail rates and RTP are the end points of a continuum of how much price variability the consumer sees, and different types of TOU systems are points on that continuum. Thus, RTP is but one example of dynamic pricing. Both RTP and TOU provide better price signals to customers than current regulated average prices do. They also enable companies to sell, and customers to purchase, electric power service as a differentiated product.

TECHNOLOGY’S ROLE IN RETAIL CHOICE

Digital technologies are becoming increasingly available to reduce the cost of sending prices to people and their devices. The 2007 Galvin Electricity Initiative report “The Path to Perfect Power: New Technologies Advance Consumer Control” catalogs a variety of end-user technologies (from price-responsive appliances to wireless home automation systems) that can communicate electricity price signals to consumers, retain data on their consumption and be programmed to respond automatically to trigger prices that the consumer chooses based on his or her preferences. [2] Moreover, the two-way communication advanced metering infrastructure (AMI) that enables a retailer and consumer to have that data transparency is also proliferating (albeit slowly) and declining in price.

Dynamic pricing and the digital technology that enables communication of price information are symbiotic. Dynamic pricing in the absence of enabling technology is meaningless. Likewise, technology without economic signals to respond to is extremely limited in its ability to coordinate buyers and sellers in a way that optimizes network quality and resource use. [3] The combination of dynamic pricing and enabling technology changes the value proposition for the consumer from “I flip the switch, and the light comes on” to a more diverse and consumer-focused set of value-added services.

These diverse value-added services empower consumers and enable them to control their electricity choices with more granularity and precision than the environment in which they think solely of the total amount of electricity they consume. Digital metering and end-user devices also decrease transaction costs between buyers and sellers, lowering barriers to exchange and to the formation of particular markets and products.

Whether they take the form of building control systems that enable the consumer to see the amount of power used by each function performed in a building or appliances that can be programmed to behave differently based on changes in the retail price of electricity, these products and services provide customers with an opportunity to make better choices with more precision than ever before. In aggregate, these choices lead to better capacity utilization and better fuel resource utilization, and provide incentives for innovation to meet customers’ needs and capture their imaginations. In this sense, technological innovation and dynamic retail electricity pricing are at the heart of decentralized coordination in the electric power network.

EVIDENCE

Led by the Pacific Northwest National Laboratory (PNNL), the Olympic Peninsula GridWise Testbed Project served as a demonstration project to test a residential network with highly distributed intelligence and market-based dynamic pricing. [4] Washington’s Olympic Peninsula is an area of great scenic beauty, with population centers concentrated on the northern edge. The peninsula’s electricity distribution network is connected to the rest of the network through a single distribution substation. While the peninsula is experiencing economic growth and associated growth in electricity demand, the natural beauty of the area and other environmental concerns served as an impetus for area residents to explore options beyond simply building generation capacity on the peninsula or adding transmission capacity.

Thus, this project tested how the combination of enabling technologies and market-based dynamic pricing affected utilization of existing capacity, deferral of capital investment and the ability of distributed demand-side and supply-side resources to create system reliability. Two questions were of primary interest:

1) What dynamic pricing contracts do consumers find attractive, and how does enabling technology affect that choice?

2) To what extent will consumers choose to automate energy use decisions?

The project – which ran from April 2006 through March 2007 – included 130 broadband-enabled households with electric heating. Each household received a programmable communicating thermostat (PCT) with a visual user interface that allowed the consumer to program the thermostat for the home – specifically to respond to price signals, if desired. Households also received water heaters equipped with a GridFriendly appliance (GFA) controller chip developed at PNNL that enables the water heater to receive price signals and be programmed to respond automatically to those price signals. Consumers could control the sensitivity of the water heater through the PCT settings.

These households also participated in a market field experiment involving dynamic pricing. While they continued to purchase energy from their local utility at a fixed, discounted price, they also received a cash account with a predetermined balance, which was replenished quarterly. The energy use decisions they made would determine their overall bill, which was deducted from their cash account, and they were able to keep any difference as profit. The worst a household could do was a zero balance, so they were no worse off than if they had not participated in the experiment. At any time customers could log in to a secure website to see their current balances and determine the effectiveness of their energy use strategies.

On signing up for the project, the households received extensive information and education about the technologies available to them and the kinds of energy use strategies facilitated by these technologies. They were then asked to choose a retail pricing contract from three options: a fixed price contract (with an embedded price risk premium), a TOU contract with a variable critical peak price (CPP) component that could be called in periods of tight capacity or an RTP contract that would reflect a wholesale market-clearing price in five-minute intervals. The RTP was determined using a uniform price double auction in which buyers (households and commercial) submit bids and sellers submit offers simultaneously. This project represented the first instance in which a double auction retail market design was tested in electric power.

The households ranked the contracts and were then divided fairly evenly among the three types, along with a control group that received the enabling technologies and had their energy use monitored but did not participate in the dynamic pricing market experiment. All households received either their first or second choice; interestingly, more than two-thirds of the households ranked RTP as their first choice. This result counters the received wisdom that residential customers want only reliable service at low, stable prices.

According to the 2007 report on the project by D.J. Hammerstrom (and others), on average participants saved 10 percent on their electricity bills. [5] That report also includes the following findings about the project:

Result 1. For the RTP group, peak consumption decreased by 15 to 17 percent relative to what the peak would have been in the absence of the dynamic pricing – even though their overall energy consumption increased by approximately 4 percent. This flattening of the load duration curve indicates shifting some peak demand to nonpeak hours. Such shifting increases the system’s load factor, improving capacity utilization and reducing the need to invest in additional capacity, for a given level of demand. A 15 to 17 percent reduction is substantial and is similar in magnitude to the reductions seen in other dynamic pricing pilots.

After controlling for price response, weather effects and weekend days, the RTP group’s overall energy consumption was 4 percent higher than that of the fixed price group. This result, in combination with the load duration effect noted above, indicates that the overall effect of RTP dynamic pricing is to smooth consumption over time, not decrease it.

Result 2. The TOU group achieved both a large price elasticity of demand (-0.17), based on hourly data, and an overall energy reduction of approximately 20 percent relative to the fixed price group.

After controlling for price response, weather effects and weekend days, the TOU group’s overall energy consumption was 20 percent lower than that of the fixed price group. This result indicates that the TOU (with occasional critical peaks) pricing induced overall conservation – a result consistent with the results of the California SPP project. The estimated price elasticity of demand in the TOU group was -0.17, which is high relative to that observed in other projects. This elasticity suggests that the pricing coupled with the enabling end-use technology amplifies the price responsiveness of even small residential consumers.

Despite these results, dynamic pricing and enabling technologies are proliferating slowly in the electricity industry. Proliferation requires a combination of formal and informal institutional change to overcome a variety of barriers. And while formal institutional change (primarily in the form of federal legislation) is reducing some of these barriers, it remains an incremental process. The traditional rate structure, fixed by state regulation and slow to change, presents a substantial barrier. Predetermined load profiles inhibit market-based pricing by ignoring individual customer variation and the information that customers can communicate through choices in response to price signals. Furthermore, the persistence of standard offer service at a discounted rate (that is, a rate that does not reflect the financial cost of insurance against price risk) stifles any incentive customers might have to pursue other pricing options.

The most significant – yet also most intangible and difficult-to-overcome – obstacle to dynamic pricing and enabling technologies is inertia. All of the primary stakeholders in the industry – utilities, regulators and customers – harbor status quo bias. Incumbent utilities face incentives to maintain the regulated status quo as much as possible (given the economic, technological and demographic changes surrounding them) – and thus far, they’ve been successful in using the political process to achieve this objective.

Customer inertia also runs deep because consumers have not had to think about their consumption of electricity or the price they pay for it – a bias consumer advocates generally reinforce by arguing that low, stable prices for highly reliable power are an entitlement. Regulators and customers value the stability and predictability that have arisen from this vertically integrated, historically supply-oriented and reliability-focused environment; however, what is unseen and unaccounted for is the opportunity cost of such predictability – the foregone value creation in innovative services, empowerment of customers to manage their own energy use and use of double-sided markets to enhance market efficiency and network reliability. Compare this unseen potential with the value creation in telecommunications, where even young adults can understand and adapt to cell phone-pricing plans and benefit from the stream of innovations in the industry.

CONCLUSION

The potential for a highly distributed, decentralized network of devices automated to respond to price signals creates new policy and research questions. Do individuals automate sending prices to devices? If so, do they adjust settings, and how? Does the combination of price effects and innovation increase total surplus, including consumer surplus? In aggregate, do these distributed actions create emergent order in the form of system reliability?

Answering these questions requires thinking about the diffuse and private nature of the knowledge embedded in the network, and the extent to which such a network becomes a complex adaptive system. Technology helps determine whether decentralized coordination and emergent order are possible; the dramatic transformation of digital technology in the past few decades has decreased transaction costs and increased the extent of feasible decentralized coordination in this industry. Institutions – which structure and shape the contexts in which such processes occur – provide a means for creating this coordination. And finally, regulatory institutions affect whether or not this coordination can occur.

For this reason, effective regulation should focus not on allocation but rather on decentralized coordination and how to bring it about. This in turn means a focus on market processes, which are adaptive institutions that evolve along with technological change. Regulatory institutions should also be adaptive, and policymakers should view regulatory policy as work in progress so that the institutions can adapt to unknown and changing conditions and enable decentralized coordination.

ENDNOTES

1. Order can take many forms in a complex system like electricity – for example, keeping the lights on (short-term reliability), achieving economic efficiency, optimizing transmission congestion, longer-term resource adequacy and so on.

2. Roger W. Gale, Jean-Louis Poirier, Lynne Kiesling and David Bodde, “The Path to Perfect Power: New Technologies Advance Consumer Control,” Galvin Electricity Initiative report (2007). www.galvinpower.org/resources/galvin.php?id=88

3. The exception to this claim is the TOU contract, where the rate structure is known in advance. However, even on such a simple dynamic pricing contract, devices that allow customers to see their consumption and expenditure in real time instead of waiting for their bill can change behavior.

4. D.J. Hammerstrom et. al, “Pacific Northwest GridWise Testbed Demonstration Projects, volume I: The Olympic Peninsula Project” (2007). http://gridwise.pnl.gov/docs/op_project_final_report_pnnl17167.pdf

5. Ibid.