Connecticut Light and Power (CL&P) was able to achieve significant improvement in outage response, as measured by CAIDI (Customer Average Interruption Duration Index),
y shifting from solving technical problems to coordinating sponses to outage events more effectively. The insight that mprovement had to be “event-driven” rather than “cause- civen” set the utility on a path to discover the critical elements f effective outage response.
e CAIDI improvement challenge
AIDI, which measures the yearly number of minutes the aver-ge customer is out of power, is used by electric utilities to mea-re system reliability. Included in the formula r SAIDI are a measure of outage frequency
AIFI) and a measure of outage duration CAIDI). Overall, SAIDI is affected by equip-ent, environmental conditions and outage recovery performance.
Like other utilities, CL&P has improved
reliability with sectionalized circuits and automatic switching. Instead of a feeder breaker outage affecting 3,000 to 4,000 people when the breaker goes out, automatic back-feeding immediately takes place and a much smaller number of customers are left without power. While this improved SAIDI, an unexpected outcome was that CAIDI actually increased, because the CAIDI measure improves when many customers go off line for a short period of time. The bigger events had provided a damper on the effects of smaller, longer outages. The reduction in the impact of the mass outage—a very good thing—meant that CAIDI performance became more vulnerable to how well the company responded to the remaining outages, highlighting an important customer service issue.
Authors
Keith Michaelson is a partner with the consulting firm Robert H. Schaffer & Associates in Stamford, Conn. He can be reached at kem@rhsa.com. Rod Kalbfleisch is the director of operation support at Connecticut Light & Power in Berlin, Conn. He can be reached at kalbfrs@nu.com. Bill Burley is a principal engineer with Northeast Utilities Service Company. Contact him at burlewj@nu.com.
Finding a focus for improvement In June 2007, a cross-functional team consisting of engineers, field supervisors and outage coordinators took a new look at the CAIDI challenge. To add a sense of urgency, the team was asked to deliver a measurable improvement within 100 days. The team make-up was ideal because each person brought a different perspective on the outage experience and a different view of how to make progress. The one thing they had in common, however, was the assumption that there were specific, identifiable causes for the high CAIDI numbers and
by Keith Michaelson, Rod Kalbfleisch and Bill Burley
each person passionately believed that solutions to the causes would bring the number down.
The team began by listing possible causes and discussing which ones to work on first. The list was long and comprehensive: switching isn’t being done quickly enough; specific equipment failures are causing longer restoration times; tree crews aren’t used effectively; cable and other critical material isn’t available when needed; there aren’t enough supervisors to work with the crews; crews aren’t dispatched efficiently enough; better coordination is needed with the phone company around repair to utility poles; incorrect choices are made about whether to repair equipment first or
restore service and then repair. The team couldn’t tackle all of these issues at once and consensus couldn’t be reached on which were most important. Each member of the team had to move beyond gut feelings to see if some data analysis could help identify the greatest contributors to CAIDI.
Fortunately, good data was available, and one by one the team isolated and removed from the calculation all outages related to a specific cause. In each case, total CAIDI changed only slightly. Then the team checked to see if CAIDI performance was regionally based, looking at each of the four operational divisions in isolation. Once again, the overall CAIDI number was essentially the same. What was going on? What did it mean that the data wasn’t providing any guidance?
Then came the brainstorm. Rather than look at presumed causes, the team took days as the unit of analysis. Review of
CAIDI continued on 64
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