What we really want is an optimal system: one that provides the best balance of technical performance, customer satisfaction, and utility financial success - the three legs of the electric utility success stool. Of these three success factors, the toughest one to achieve may be customer satisfaction. That may sound a little surprising because in the past we haven't, in general, heard much grumbling from utility ratepayers regarding system performance. In fact, we really haven't heard much from customers at all. As the old joke goes, for decades, the only communications most customers have received from their utility has been a bill in the mail or a turnoff notice.
That's all changing. Utility customers have been hearing about smart grid, alternative energy, rebates, subsidies – there was even the 2009 Super Bowl GE smart grid ad. The news media noise has been loud and ratepayers are fully alert, smarter and expecting something big.
Those expectations are shown in the Reliability Demand Survey (RDS) on American attitudes toward electric power outages that found that ratepayers are becoming hypersensitive about outages. They won't excuse them except, possibly, for extreme weather.
Enlightened ratepayers are looking at what they're getting for their money and the pressure is on utilities to measure electric service quality from the customer's perspective. We're not quite there yet but we're making progress.
For decades we have used a number of system performance indicators to measure a utility's power reliability from the system point of view:
SAIDI—System Average Interruption Duration Index—The average duration of sustained (minutes, hours, days) customer interruptions per customer over a specified period. It is the average time customers were without power. It is determined by dividing the sum of all sustained customer interruption durations, in minutes, by the total number of customers served.
CAIDI—Customer Average Interruption Duration Index—The average interruption duration of sustained interruptions for those customers who experience interruptions during the analysis period. CAIDI represents the average time required to restore service to the average customer per sustained interruption. It is determined by dividing the sum of all sustained customer interruption durations, in minutes, by the total number of interrupted customers.
SAIFI—System Average Interruption Frequency Index— the average frequency of sustained interruptions per customer over a specified period. It equals the total number of sustained customer interruptions divided by the total number of customers served.
MAIFI—Momentary Average Interruption Frequency Index—The average frequency of momentary interruptions (a few seconds duration) per customer over a specified period. It is calculated by dividing the total number of momentary customer interruptions by the total number of customers served.
I suspect that legacy reliability indices will continue to be used for rate approval and other regulatory oversight but there is a low key movement afoot in the industry to develop customer-centric performance indices that reflect service quality as perceived by the individual customer. These are particularly needed for commercial and industrial customers because there's a wide variation in customer tolerance to both outage frequency and outage duration. An example is the tolerance difference between a paper roller mill and a cold storage facility. The latter can tolerate short-term outages – seconds and minutes even, but generally not hours and certainly not days. On the other hand, some older roller mills can't tolerate any interruption, even momentary. Loss of power can result in loss of synch between rollers and a facility full of wasted product. At that point it doesn't much matter how long the power is off because it may take a day to start up again.
A section of the distribution system optimized for one of these customers probably won't meet the needs of the other and legacy reliability indices won't identify the issue.
So, these legacy indices may be good enough for regulators to get some idea of how well a utility is performing, but they mean almost nothing to the individual customer because the indices are based on system averages. It's like the example of the man with his feet encased in ice and his hair on fire – on average he's about the right temperature. Sure, we can estimate standard deviations and use other statistical metrics but we're still stuck with averages unless we get right to the individual customer meter.
Fortunately, more and more, we're able to do just that. Advanced Metering Infrastructure or AMI, is just the ticket. We can measure power quality and detect outages right at the customer's service connection. AMI data, new customer-centric performance measures are all part of the electric utility total makeover that's starting to take shape.
But customer satisfaction isn't just built on better technical service quality. Perception, particularly by residential customers, can even override reality. Recently the reliability of a British utility significantly dipped, but the company kicked its customer communication into high gear. During outages customers were notified and given estimations of when their service would be restored. As a result, customers reported that their service quality had improved by quite a margin!
On the other hand a utility in the U.S. Southwest made some big (expensive) system upgrades resulting in greatly improved reliability. Ironically, after the improvements were added and measured service quality went up, customers perceived it as getting worse! Again, customer care and communication (or lack of) was just as important as service quality in shaping customer perception.
Bottom line: Building operating and maintaining the optimal grid is a balancing act between meeting financial requirements and restraints, providing quality service, and satisfying customers. For the first time in the history of the electric utility industry it looks like we have the technical tools to do the job. But we can't have a "we know best" attitude.
Customer perception is job one!
About the Editor
Paul Mauldin earned his B.S. and an M.S. in electrical engineering from the University of California-Berkeley and is a registered professional engineer who has worked in the energy industry for more than 25 years. Mauldin is also editor of Smart Energy Portal smartenergyportal.net