Meter data is the lifeblood of any utility, primarily because it forms the basis for billing customers and so is directly tied to revenue. The strategic importance of the data, however, has only recently begun to emerge. Utilities are now marketing value-added services that leverage the vast quantities of usage data they collect, making the meter data process more visible from a strategic perspective.
There has been a corresponding increase in the number and sophistication of technologies used to manage the flow of data from customer meter to downstream applications like billing and CIS, but this has also introduced a new level of complexity as well. Optimizing the meter data process to minimize the length of time it takes to go from meter to end use is not as straightforward as it may seem, but automation and the implementation of a relatively new data standard may hold the answer.
What’s the holdup?
For now, however, there several points along the processing path where meter data can get held up. Here are just some of the speed bumps that can affect meter data:
“-Communications systems are a notorious source of problems, as any meter data manager can tell you. Even the most reliable systems will eventually experience failure thanks to problems with customer phone lines, cellular drop-outs, and other disruptions.
“-Speed is another issue. Phone line-based metering systems use dial-up connections, and slow ones at that. High-speed LAN connections are another option. Internet-based systems have the advantage of not requiring a phone line (with its attendant monthly fee), but obviously these systems are predicated on a given facility having an existing network that is linked to the Internet via something other than a dial-up connection.
“-Mergers, acquisitions or expansion into restructured markets have produced energy companies that are now doing business in multiple territories. This in turn means multiple meter data systems and integration issues in trying to consolidate data from those sources, issues that can take a substantial amount of time to address. Problems can also arise with daylight savings time throughout the process–in the device itself, in the extraction of data from the meter, in the data collection system, and in other applications downstream. For example, one metering system might address DST by using a “25 hour day” once a year while another simply uses standard time over the course of the entire year.
“-Human error is always a locus for meter data problems. A customer might unwittingly change the phone number the utility’s data collection system calls to interrogate their meter. A meter tech might forget to take a reading before swapping out an old meter, or make an error in programming a meter remotely. People make mistakes, and there are many ways that they can affect the integrity and/or timeliness of meter data.
“-Validation and estimation might seem a likely point in the meter data process to address at least some of these issues. At its simplest, the V&E process involves performing a number of tests on incoming meter data to determine if it is accurate, and estimating values for data points found to be invalid. Problems like missing data and highly improbable readings, for example, can be identified and even corrected programmatically. But V&E presents its own roadblocks to meter data processing.
MV90, the industry standard data collection system, provides a certain level of V&E capability, but when market rules require more extensive validation procedures (e.g., California), the utility must implement a more robust V&E application, adding another step to the process. In practice, a lot of validation is still done manually–which gets back to the issue of human error–and there may be points along the way where meter data is diverted from the main meter-to-bill flow to meet a particular need (e.g., posting directly to a Web site).
Opportunities for improved efficiency
Automation can address some of the holdups in meter data processing, in particular by minimizing the level of human intervention. The cost of implementing automated solutions, however, is often difficult for metering departments to justify. The key is to tie the investment in IT to something other than simply replacing the meter reader. For example, AMR is also an enabling technology for demand response programs, and some utilities have even sold it to end customers as a value-added “privacy” service–automated meters mean no utility personnel in your back yard.
Vendors are also working to improve efficiency and flexibility in meter data processing with support for a standard data format (ANSI c12.19) that will obviate the need for data collection systems to ‘speak the language’ of a given meter. This could open the market to alternatives to the dominant MV90, but as some utility managers point out, there is not a compelling economic incentive today for replacing older meters with ones that support the standard.
Deregulation could expedite the process. A metering service provider, for example, might install new advanced meters in order to collect power quality data and in the process install standard-compliant devices. Still, for the immediate future, and especially in the current business climate, utilities will expect any IT investment to show a speedy payback. Some industry analysts have even pushed the energy sector’s financial recovery out to 2004. That will likely delay any potential revolution in meter data processing.
Fesmire is a marketing writer in ABB’s utilities division. He can be reached at 405-615-6289 or email@example.com.