Smart Metering Data: from burden to bonanza


By Guerry Waters

Smart Metering brings with it a data inundation. How can you ensure a positive return on the costs to gather, process, and store it?

It’s hard to open your inbox these days without finding announcements for Smart Grid and Smart Metering conferences. When you attend them, you hear speakers full of optimism. Smart Meters will improve relationships with customers, speakers declare. They will foster wiser use of energy and help protect the world’s climate.

Few dispute the long-term validity of those assertions. But during the breaks, you hear an undertone of skepticism about the short term. In the coffee line, a consultant asks about rumors that one U.S. project has spent $2,000 on infrastructure for each of its “Smart Grid ready” residences. An analyst searching for a teabag in a flavor other than passion fruit refers to U.K. estimates that a £9 billion Smart Metering rollout might return only £300 million per year. At the fruit plate, a regulator speculates that if Smart Metering fails to lower customer costs, backlash could result.

As you bypass the brownies, you think about the changes Smart Metering will require: a new CIS that can handle complex rates and multiple programs; a meter data management application and database expansions to handle the 730-fold increase in customer data.

Will the benefits of Smart Metering be worth these risks and the costs?

Putting Pilots Into Perspective
Smart Metering pilots that have tested energy conservation potential or demand response participation suggest positive results. But pilots do not cover the full range of Smart Metering benefits. Their small size and limited duration cannot, for instance, calculate the true savings from remote disconnects because only a tiny fraction of pilot customers move during the pilot’s duration. Thus there is no reported reduction in the field force, no cutback on distance driven, no reduction in vehicular wear and tear.

Similarly, pilot testing of Smart Meter detection of nested outages or transformer sizing is impossible when pilot customers are scattered across a utility’s territory.

Estimating Projected Benefits
Small sizes and the random nature of subject selection will continue to make it impossible for pilots to test many of the uses to which utilities can put universally collected Smart Metering data. The Smart Metering business cases of leadingedge utilities may likewise hold few clues because the sizes, locations, grid conditions, and existing IT infrastructures of different utilities exert powerful influences on eventual results.

It would be foolish to posit Smart Metering business cases that ignore non-customer uses for Smart Metering data. It would be equally foolish—and undoubtedly unconvincing to regulators and other stakeholders—to pull numbers out of a hat.

Fortunately, there is a way to test a wide variety of potential Smart Metering benefits without using pilots: the “what if” scenario based on data extrapolated from your own Smart Metering customer pilot, from post-pilot data from those same customers, or from data borrowed from a utility similar to yours.

Most utilities have at least a few analysts eager to try their hand at creating “what if” scenarios that test Smart Metering proposals. Using basic business intelligence tools and existing information from departments across the utility, analysts should be able to come up with reasonable estimates for potential:

  • Supply cost reductions. Can your analysts detect patterns in the data that would permit you to hone generation scheduling and supply contracts? Does the amount of reduction depend on time of day or time of year? Is it limited to a specific subgroup of customers or geographic area? Imagine you use only half the results your analysts project over the course of the year and calculate the savings. How far would they go toward justifying Smart Metering?
  • Asset cost savings. The lack of detailed understanding of consumption patterns has long led grid engineers to size distribution equipment with generous margins that prevent damage from a consumption surge. That makes sense. The cost of an outage almost always exceeds the cost of transformer oversizing. But ask your analysts to estimate your current excess margins given their analysis of their interval data set. Project the savings from right sizing over a year or a decade. See if asking your most experienced grid engineers to examine initial results permits them to add knowledge your analysts may not have and possibly result in solutions for other grid inefficiencies.
  • Peak shaving. The calculation involved here is probably different from what it would have been a year ago. The global recession has markedly reduced both overall and peak consumption at many utilities, evaporating near-term grid expansion needs. Still, it may be valuable to calculate projected demand response results against previous peaks and then estimate the saving from an additional year or two during which to defer grid expansion.
  • Reductions in fines. When Smart Meters are concentrated geographically and equipped to send “last gasp” signals, utilities can reduce outage durations and thus the risk of fines for exceeding standard indices. Smart Metering may also help utilities stay within outage performance limits while also reducing the cost of vegetation management by using “blink out” reports to prioritize tree trimming.

Utilities may achieve better results if they put analytical teams into competition with each other to find ways to use Smart Metering data to achieve the best results. A nearby university might be willing to use the task as an assignment for MBA students. Municipal and cooperative utilities might consider joining association benchmark programs to add this competitive edge and bring in perspectives from other utilities.

Some Estimates Are Easy
It takes little more than a manager and a calculator to estimate savings from:

  • Disconnections. Smart Metering can virtually eliminate the costs to send field crews and vehicles to disconnect customers who are vacating a property or who, after repeated warnings, have not paid their bills. Remote reconnections also represent considerable cost saving potential provided utilities take appropriate safety measures, such as ensuring that an adult is on the premises and knows to check all appliances for those inadvertently left on.
  • Service calls. Simply add up the personnel and vehicular expenses for responding to incorrect reports of no service. Checking meter functioning before dispatching crews is a basic Smart Metering practice that virtually eliminates unnecessary “truck rolls.”
  • Fewer final-bill problems. The vast majority of your customers have no intention to leave unpaid bills behind them when they move. But the hassle of moving—lack of clarity about the new address, too many things on the to-do list—often forces utilities to wait for payment as bills are forwarded across the country and get lost in a jumble of moving-in tasks. It should be possible to isolate and calculate the financial impact of your final-bill problems. What if you could reduce them even ten percent—probably a very low estimate—by permitting customers to call, spend a minute or two on hold while you retrieve the final consumption figure and calculate the final bill, then pay with a credit card as the moving van pulls away?
  • Reducing the time between your final decision to disconnect a customer for non-payment and the actual disconnection. What is the average time currently between your completion of all legal requirements regarding a non-paying customer and the actual moment of disconnection? How much does the average non-paying customer consume during that period? How much would you save if there were no time at all between decision and disconnect?

Some Benefits Will Remain Unsized
Not all Smart Metering benefits translate into bottom-line numbers. There is no revenue connected with the thanks from the jewelry-store owner whose Smart Metering data reveals a remarkable surge in consumption at 4:00 p.m.—the time the pizza parlor next door turns on its oven. Few utilities will be able to put a precise monetary value on the ability to correct voltage fluctuations before customers complain or the contribution supply reductions make to a cleaner environment. Those benefits are nonetheless real.

Change is undoubtedly coming. Rising populations and dwindling resources make a compelling case for the smarter use of increasingly expensive energy resources. Sizing anticipated uses and benefits helps utilities select IT vendors, applications, and infrastructure that can move utilities costeffectively into this new era.