By Bob Heile, IEEE’s 802.15 Working Group on Wireless Personal Area Networks, P2030 Work Group Task Force 3 and the ZigBee Alliance
Utilities around the globe see in advanced metering infrastructure (AMI) tremendous and far-ranging potential—for empowering consumers to make more intelligent choices about their energy usage, reducing peak loads and thereby enhancing grid reliability, realizing new operational efficiencies and more.
Harnessing AMI’s remarkable promise, however, is no small consideration. The quantity of data being generated, collected and analyzed in an AMI-enabled world is orders of magnitude greater than what utilities have had to deal with before.
Consequently, meter data management (MDM) is revealing itself as an increasingly important topic for utilities as smart grid rollout intensifies worldwide.
In the excitement to realize the benefits that AMI and the smart grid’s promise, utilities can’t afford to rush through key strategic questions regarding MDM: What are the ramifications of introducing MDM across operations in storage and operational burden, for example? What is necessary to discern genuinely useful business intelligence from the unprecedented volume of raw data being put into play by AMI?
Making Room for AMI
The residue of the march toward a demand-responsive smart grid—a multisource fabric of power generation that is circularly interlinked with AMI gateways to home area networks (HANs) that produce load profiles and power factors across a range of appliances—is data, lots and lots and lots of data, perhaps in the hundreds of megabytes per meter per year.
AMI frequently records data on more types of events than utilities have attempted to gather from their business and residential users. This means that a utility must anticipate the kind of storage and processing footprints that its MDM approach imposes on its information technology (IT) infrastructure.
The volume of data from head-end servers must be securely stored, and tasks such as data validation, synchronization, estimation and editing must be carried out to ensure that automated back-office and delivery systems are accurately informed in their actions.
“The data synchronization issue alone is significant,” said Mark A. Ortiz, enterprise architect focused on smart grid application architecture with Consumers Energy, an electric and natural gas utility based in Jackson, Mich. “If a utility doesn’t have a good strategy in place, the potential to duplicate data is real. The volume of meter data including events is tremendous and will quickly increase as you consider scenarios for millions of meters. It is important to understand where customer and meter asset data belongs and avoid duplicating it, preventing scalability issues and costly storage footprints.”
Given that AMI and the smart grid naturally render IT a much larger portion of a utility’s operations, some are taking a divide-and-conquer approach to the task of MDM. Packaged, lightweight solutions for integrating multivendor meter reading and control have emerged. They are designed to free utility IT personnel to concentrate on interpreting and archiving data. Other utilities will find it more valuable to build their own MDM systems tailored to their own unique environments.
From Smart Grid Data to Intelligent Business Decisions
AMI is of no value to the utility or its customers unless it develops into something much more than an interesting IT challenge. The higher-level strategic concern of MDM is converting high-quality data into timely business intelligence that utilities can actually use to make good decisions in billing scenarios, customer service and operations management.
“A good information-management strategy is critical,” Ortiz said. “There must be semantics built around the data in order for a utility to act on it. What does the meter reading mean? It’s only when you understand this that you can start to do things with that information.”
A critical element in MDM must be back-office applications that correlate data and make meaning of events to intelligently inform better management of assets and customer relationships. Successfully adapted to a utility’s operations, MDM could fuel a range of valuable capabilities such as more cost-effectively planning for periods of high demand, seamlessly managing distributed generation sources, anticipating and averting system outages, identifying particular systems that are at risk of failure and monitoring for service theft.
Standards development in the area of open and interoperable MDM interfaces will be necessary to ensure that utilities do not invest and re-invest heavily again in multivendor AMI integration as technology and business realities inevitably evolve.
The regulatory environment must be closely watched, too. Questions such as how much AMI data must be archived, what pieces must be saved to address customer repudiation and other issues, what pains must be taken to ensure data security and privacy and who ultimately owns the data are likely to emerge from public utility commissions and other regulatory bodies. These market-specific answers must be be factored into utility MDM strategies, as well.
A well-conceived and executed strategy of MDM—encompassing its far-reaching IT implications and seamless contribution to decision-making—is one of the critical linchpins for the smart grid. Every day, more sensors and AMI systems are being deployed to produce real-time and near real-time data that utilities can use to gain a more precise definition of evolving energy needs. If not properly integrated with existing utility systems and business processes via smart MDM, AMI’s potential to enhance grid reliability, utility efficiencies and customer choice could be squandered—along with the billions of dollars being invested in it around the globe.
This article is the second in a series of articles on metering by Heile. His first article in the series was in the July 2010 issue. Look for his final article in this series in the upcoming September issue.
Bob Heile is a 30-year veteran in data communications and wireless data. He is the chairman and founding member of the IEEE 802.15 Working Group on WPANs, chairman of the ZigBee Alliance, co-chairman of IEEE P2030 Smart Grid Communications Task Force and is a founding member of 802.11. He holds a bachelor’s degree from Oberlin College and a master’s and doctorate in physics from The Johns Hopkins University.
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