SAIDI, CAIFI, & SAIFI: A Guide to Utility Reliability Metrics

In this blog, we break down the meaning of some important metrics (commonly referred to via acronym) used by the Federal Energy Regulatory Commission, along with utilities themselves, when measuring utility service reliability.

These metrics are helpful for understanding how regulators and utilities think about measuring and improving the quality of their services for end-users.

What is the Federal Energy Regulatory Commission (FERC)?

The Federal Energy Regulatory Commission (FERC) is “is an independent agency that regulates the interstate transmission of natural gas, oil, and electricity.” Its mission is to provide efficient, safe, reliable, and secure energy for consumers through “appropriate regulatory and market means.”

The FERC uses reliability statistics as quantitative metrics for measuring the quality of management practices employed by various utilities. Standards may vary from utility to utility (e.g. regions with more storms or colder weather may face more risk for service interruptions). For this reason, these metrics are most valuable for making period-to-period comparisons within the same utility as it seeks continuous improvement.

As a starting place for evaluating reliability, FERC relies on the standard metrics defined by The Institute of Electrical and Electronics Engineers (IEEE). These metrics are found in the IEEE 1366 guide.

What are important IEEE reliability indices used by FERC?

  1. SAIDI: System Average Interruption Duration Index
  2. SAIFI: System Average Interruption Frequency Index
  3. CAIDI: Customer Average Interruption Duration Index
  4. CAIFI: Customer Average Interruption Frequency Index
  5. MAIDI: Momentary Average Interruption Duration Index
  6. MAIFI: Momentary Average Interruption Frequency Index 

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We explore each of the above terms in the article below. While the IEEE describes SAIFI, SAIDI, and CAIDI as the “big three,” the other terms in the list provide helpful context. These terms are virtually always analyzed or compared within a particular period. Examples include within a specific year, between the same months from different years, or within a specific storm.

Reliability data is analyzed in terms of momentary versus sustained interruptions.

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What is a momentary interruption?

The IEEE defines a momentary interruption as “the brief loss of power delivery to one or more customers caused by the opening and closing operation of an interrupting device.” In general, these interruptions are defined as less than five minutes in length.

What is a sustained interruption?

The IEEE defines sustained interruptions as any disruption lasting more than five minutes (e.g. any interruption longer than momentary). We have seen some utilities using an even more rigorous 1-minute standard.

Why is measuring momentary v. sustained interruptions important?

The most important conceptual difference between sustained and momentary interruptions is whether they are resolved automatically, as with a “recloser” device. A recloser is “an automatic, high-voltage electric switch...it shuts off electric power when trouble occurs.” It then “automatically tests the electrical line to determine whether the trouble has been removed. If the problem was only temporary, then the recloser automatically resets itself and restores the electrical power.”

In general, momentary interruptions are resolved automatically. Sustained interruptions require a coordinated maintenance intervention. For the indices below, SAIDI, SAIFI, CAIDI, and CAIFI refer only to sustained interruptions. MAIDI and MAIFI are focused specifically on momentary interruptions.

What is SAIDI?

SAIDI refers to “System Average Interruption Duration Index.” It is calculated by multiplying the average duration of customer interruptions by their total number and then dividing by the total number of customers in the system.

SAIDI describes the total duration of the average customer interruption. Logically, improved response to outages is the most direct way to improve SAIDI. Strategies to reduce the frequency of interruptions (see the next acronym below) will also help improve SAIDI: if an outage is prevented, its duration isn’t added to the index.

What is SAIFI?

SAIFI refers to “System Average Interruption Frequency Index.” It is calculated by dividing the total number of customers interrupted by an outage by the total number of customers in the system.

In short, SAIFI describes how often the average customer experiences an interruption.

SAIFI can be improved by reducing the frequency of outages through better preventative maintenance. Improved equipment maintenance and tree-trimming, for example, can limit the number of service interruptions. This article in T&D world also notes that SAIFI can also be improved by “reducing the number of customers interrupted when outages do occur (for example, by adding reclosers and fuses).”

What is CAIDI?

CAIDI refers to “Customer Average Interruption Duration Index.” It is calculated as total minutes of customer interruption divided by the total number of customers interrupted.

CAIDI describes the average time required to restore service. Unlike SAIDI/SAIFI, CAIDI includes only customers who actually experienced an interruption. This fact makes it useful for measuring response to interruptions, but not the prevention of interruptions.

CAIDI improvement strategies include automated call-out of troubleshooters and crews for faster outage resolution and increased troubleshooter staffing.

What is CAIFI? 

CAIFI refers to “Customer Average Interruption Frequency Index.” It is calculated by dividing the number of interruptions by the number of customers experiencing interruptions.

It describes how many interruptions each impacted customer experiences. Therefore, it helps detect whether problems are being resolved effectively or left vulnerable to recurrence. Like CAIDI, this metric only includes customers who actually experienced interruptions (not customers across the whole system).

What is MAIDI?  

MAIDI refers to “Momentary Average Interruption Duration Index.” Unlike the statistics above, this category includes only momentary interruptions. IEEE defines momentary disruptions as those lasting less than five minutes. Besides the inclusion of momentary events, it is conceptually similar to SAIDI. While not as common as the other terms on the list, capturing the duration of even momentary interruptions is important to some utilities.

What is MAIFI?

MAIFI refers to “Momentary Average Interruption Frequency Index.” Like MAIDI, this category includes only momentary disruptions (<5 minutes).

Otherwise, it is conceptually similar to SAIFI. It is calculated by dividing the total number of momentary interruptions by the number of customers in the network.

How do utilities capture and utilize reliability performance data?

Capturing the data needed to calculate all of the indices above is vital for utilities seeking to improve the management of their system and fulfill regulatory requirements.

The information captured in the metrics above gives decision-makers crucial guideposts as they seek to:

  • Improve system reliability year-over-year.
  • Pinpoint and resolve chronic trouble-spots in the system.
  • Integrate incoming customer outage reports and service requests (collected via CIS, or Customer Integrated System) with outage data.
  • Minimize the frequency and impact of customer outages.
  • Respond as quickly and impactfully as possible in response to a storm or other major outage event.
  • Direct crews to restore service in the most efficient manner possible.

To do so, utilities make use of an Outage Management System.

What is an Outage Management System?

An outage management system is a specialized software that uses equipment monitoring and geographic information system (GIS) data to track a utility network’s performance and reliability.

Traditionally, outage management was conducted using paper-based tracking of reported outages (and a lot of deduction work). This article provides a useful overview of the evolution of computer-based OMS systems. Today, computerized OMS systems are the norm for utilities.

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Utility360 Helps Utilities Capture & Use Reliability Performance Data

Outage Management Systems capture the raw data needed to monitor and manage network reliability. Capturing this data is just the beginning, however. Utilities need a solution like Utility360 to take that raw outage data and use it to calculate the reliability metrics discussed above (and conduct deeper analysis to build a more reliable network). This calculation could be accomplished using a spreadsheet or similar tool. This approach, however, can be cumbersome, time consuming, and error prone. And spreadsheets simply do not provide efficient workflows for diving deeper into the data.

Utility360 helps utilities to get the most out of their outage data by comparing reliability metrics across different time periods, quickly drilling down into details about a particular outage, and viewing outage data sorted by specific events (like storms). Organizing outage data into interfaces like real-time outage maps and dashboards helps decision-makers make use of outage analytics as quickly and effectively as possible. Data also needs to be able to be separated for analysis across different categories. Many utilities, for example, segregate outages generated by Major Event Days. This practice helps analyze routine issues distinctly from the waves of outages generated by a major storm.

HEXstream’s Utility360 solution provides a business-ready platform for utilities seeking a comprehensive outage analytics toolkit. Utility360 integrates directly with leading OMS systems, and its frontend can support any of your favorite visualization tools, including Tableau and PowerBI. It automatically calculates reliability statistics and provides reliability reports, offers configurable outage maps and dashboards, and helps immediately connect outage data to relevant information on customers and crews.  

Contact us using the link below to learn how Utility360 can be aligned with your utility's specific requirements to deliver powerful reliability reporting and analytics throughout your organization.

Utility360: More Powerful Analytics for  Better Outage Management

About the Author

Kiran Boddireddy

Kiran Boddireddy

Kiran Boddireddy is a Senior Technical Consultant at HEXstream. He has many years of IT experience and specializes in Analytics and Data Warehousing. He is responsible for many successful OMS analytics project implementations at various clients. He holds a Masters Degree in Computer Science from University Of Central Missouri. In his free time, Kiran likes to watch sports and movies.

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