MDM’s Role in Utility


by Dan Hokanson, director of Gridstream MDM Solutions, Landis+Gyr and Matt Schwarz, director of marketing communication for Gridstream MDM Solutions, Landis+Gyr

The smart grid and smart meters are delivering data that is opening new possibilities for the way utilities do business. These always-on, intelligent devices provide the building blocks for quickly detecting energy loss or theft, analyzing usage patterns to determine optimal rate structures, responding rapidly to outages, maximizing the lifetime of distribution equipment, and connecting with customers in more convenient ways.

Utilities are in different stages of laying the foundation for delivering data. In addition to smart meters, utilities are receiving more data from many distribution assets: transformers, fuses, switches, reclosers and other devices and sensors. As data streams into the business from many disparate points, the potential to leverage the data beyond billing becomes an increasingly more realistic goal for most utilities.

The amount of data available is staggering. The many utilities that are embarking on smart grid initiatives are capturing terabytes of data each month in hourly and subhourly metering intervals, which equates to hundreds of millions of reads and millions of diagnostic events each day. Now the challenge utilities are beginning to tackle involves identifying ways this mountain of data can be used across the entire business.

According to Pike Research’s 2012 “Smart Grid Analytics Report,” the application of smart grid data analytics is varied and complex because it is employed to support multiple outcomes related to utility operations, customer-centric issues and business questions. Even so, Pike Research defines smart grid analytics as the process of examining raw data form smart grid sensors and devices, other forms of operational data, historical and business data to draw conclusions, make decisions and respond appropriately.

Many solutions play a role in a utility’s enterprise analytics approach, and the meter data management (MDM) system is one of them. MDM systems become critical assets to utilities’ analytic strategies when they are:

  • Built to normalize data from many different sources;
  • Scalable to meet the daily processing needs for hundreds of millions of reads and diagnostic events; and
  • Capable of providing accurate information to adjacent utility systems and business intelligence solutions.

When conceived a little more than a decade ago, MDM systems for mass market metering were little more than a repository to store meter data, a central collection point and a single system of record for all meter data. Today, MDM systems remain the central collection point and the single system of record, but these early systems have matured and are becoming part of an overall analytics strategy for utilities.

The most valuable MDM systems in an analytics strategy are those that validate every meter read every day to provide current, reliable data to adjacent solutions. MDM systems also must be easily interconnected with adjacent systems. The centralized and interconnected nature of MDM solutions give utility departments access to the most relevant data in a ready-for-use format to fulfill the department’s mission: accurate billing data for the billing department, real-time usage data for customer service representatives and timely outage information for grid operators.

One approach for providing analytics through the MDM system is a threefold strategy:

1. Offer business analytics embedded within the core product for the basic daily needs of understanding usage and creating billing determinants.

2. Provide additional add-on analytic packages for specialized business cases such as outage management, transformer load management, revenue assurance and more.

3. Make it easy to integrate and export the most current and valid data from the MDM system with enterprise business intelligence solutions for further actions and analysis.

Embedded analytics are foundational to any MDM system. These types of analytics provide the daily operational information necessary for the utilities to use the usage data and diagnostic event data from meters and other distribution assets effectively. Validation, estimation and editing rules help utilities systematically understand if the data received is complete and if values that are delivered are equal to what was expected for that period.

The second strategy taken within MDM solutions is the offering of specialized, extended analytics packages that leverage the current and valid data provided by the embedded processes and use it for specific utility programs to enable defined, measurable operation benefits.

An outage and restoration event is a great example of an operational use case that can leverage near real-time data of smart meters to augment the information typically found within an outage management system. The extended analytics approach for outage and restoration scenarios leverages data from smart meters to determine the location and size of outages and the effectiveness of the restoration activity.

Finally, it must be easy to extract the data from the MDM system to adjacent systems. International standards are critical to achieving well-defined, nonproprietary interfaces that will work in all regions of the world. One such set of standards are the International Electrotechnical Commission (IEC) 61968 family of standards. The functionality afforded by this series of standards aligns well with the functionality of other prevalent industry- or consortium-led standards. These include MultiSpeak and the SAP Meter Data Unification System (MDUS) specifications. These industry standards are compliant with the IEC 61968 standards and interoperate through a relatively short development cycle to create lightweight adapters between protocols. Standards-based approaches to integration speed a utility’s benefit realization.

The analytic capabilities of a central and intelligent MDM system open the possibility for utilities to begin identifying many new use cases for smart meter data. The combination of embedded and extended analytics is critical in enabling many utility programs and adds business and operational value for smart grid infrastructure.

Dan Hokanson is director product management at Ecologic Analytics, a Landis+Gyr company.

Matt Schwarz is director of marketing communication at Ecologic Analytics, a Landis+Gyr company.

Case Study

Oncor Uses MDM Data to Boost Operations, Customer Satisfaction

Since a Texas utility in the final stages of one of the largest, fastest and most advanced smart meter deployments in the U.S. synced its meter data management system (MDMS) and outage management system (OMS), it has been leveraging billions of pieces of interval data every day to improve outage management and customer service.

Oncor, the largest regulated transmission and distribution utility in Texas, has made inroads in leveraging AMI data and proving its value to utilities. It has demonstrated success in using AMI and MDMS in tandem with OMS to improve operational efficiency and the consumer experience

Smart Texas

Oncor delivers power to some 3 million homes and businesses and operates some 117,000 miles of distribution and transmission line in Texas. As part of its Smart Texas smart grid deployment, Oncor set out in 2008 to merge the functions of multiple information technology systems. The goal was to collect and use 15-minute-interval electricity consumption data. Since then, Oncor has installed Landis+Gyr smart meters in most of North Texas-most of its customer base. Deployment of smart meters for all Oncor customers was completed by the end of 2012. In 2009, Oncor deployed Ecologic Analytics’ MDM software integrated with a Landis+Gyr smart meter system. At the same time, the utility deployed Intergraph’s OMS.

“There was a lot of siloed thinking at the time,” said Mark Carpenter, Oncor senior vice president of transmission and distribution system operations and measurement services.

The tools were designed originally for future integration with each other, but they were owned by different internal teams and used independently.

Importance of Integration

The utility recognized the importance of leveraging meter information from its MDMS to augment utility OMS data so it could pinpoint areas with outages more accurately. But with widely varying opinions’ swirling around the company about the value of AMI data, would Oncor be able to integrate systems and meet its objectives? Oncor’s distribution operators were skeptical. They, like many others in the industry, were under the impression that AMI generated too many false positives. The focus of the integration team was to design a system that would eliminate false positives, optimize the number and quality of alarms, prioritize system messages and reconcile AMI and OMS data. Working with IBM as system integrator, Oncor developed a plan to link its MDMS and OMS more closely. IBM helped all the players involved understand the commonalities of the systems and establish consistency. The result was a system of systems. Each component was designed to derive valuable data. Now, Oncor dispatchers can use push-reads to validate power restoration after large storms and perform verifications with a single click.

A New Approach to Outage Management

Between March and April 2012-within the first six weeks of completion of the system integration project-the AMI system generated more than 1,400 notifications that signaled unusual events at smart meter locations. Of those issues that were outages, more than half were restored before customers reported them. In addition, some notifications identified failing distribution equipment, which provided the utility the opportunity to initiate repairs before an outage occurred. Although 100 percent of these events were validated as actual, only 35 percent resulted in customer calls or complaints. Most of the issues were actual outages, and others were power quality issues created by bad connections or opened neutrals. In many cases, repair technicians had visited the locations of the issues in the past but had not identified the problem.

Oncor Chief Operating Officer Jim Greer called the new approach a game changer.

“In the past, we didn’t know about an outage until a customer reported it,” he said. “Now, we are able to use the information from our advanced meters to diagnose and fix many issues on our system before they cause problems.”

Oncor is beginning to recognize clear patterns in its data that help it address problems before they occur. There is no longer a need to wait until a customer discovers a power outage, so the utility can provide customers with significant improvements in service restoration.


Greer said the progress made by the utility since integrating the two systems is just the beginning of possible efficiencies and service improvements from the use of AMI data.

“Using this new information, we can continue to make adjustments and address issues on our grid as needed to ensure that our customers are receiving the quality of service they demand and deserve, and our advanced meters are helping us deliver on that promise,” he said.

Previous articleMeasure to Win – 3 Ways to Achieve More Value From Grid Performance Metrics
Next articleIEC 61850-Why all the Hype?

No posts to display