Some outages are hard to predict based only on tree trimming cycle lengths. On March 6, 2017, the earliest confirmed tornados in Minnesota history touched down, causing tree and pole damage on the Connexus Energy system near the town of Zimmerman. This was immediately followed by about 6 inches of snow, subfreezing temperatures and 30-mph winds with even larger gusts, making damage removal difficult at first for this Asplundh lift crew assisting with power restoration.

Effect of Cycle Length on Tree-Related Outages

June 22, 2017
Connexus Energy dives deep into data for greater vegetation management insight.

Managing vegetation along overhead lines reduces outages and improves reliability. It is somewhat intuitive that more tree-related outages occur the longer a utility waits to maintain vegetation, but can it be predicted by how much? Specifically, how much incremental improvement may occur with shorter vegetation management cycles? Will the reliability improvements justify the cost?

Connexus Energy set out to find the answers to these questions to inform its decision making and optimize spending related to the cooperative’s vegetation management program.

Connexus is a Minnesota cooperative north of the Twin Cities, spanning 1000 sq miles and serving 130,000 members from 200 circuits. The utility’s vegetation management team wanted to answer the questions with a simple, easy-to-understand presentation of the analysis. Connexus started its investigation using five years of tree-related outage data.

The cooperative’s first goal was to find out the average number of outages per circuit that occurred because of vegetation on the primary line versus how many years since the circuit was last cleared of vegetation encroachments. This will help the utility to identify the trend of outage frequency per circuit as the years increase since the last vegetation maintenance. The second goal was to relate the magnitude of the outages (how many customers have been affected) to the years since a circuit was last cleared of vegetation.

Determining Outage Frequency

Connexus first set out to determine the outage frequency for the years since it last conducted maintenance using the following data:

  • Five years of tree-related outage data, including the date of outage, circuit affected, number of customer interruptions (CIs) and number of customers on the circuit.
  • Major event days (MEDs) — as defined by the Institute of Electrical and Electronics Engineers (IEEE) standard 1366 — were excluded to reduce anomalies within the outage data.
  • Year the circuit was last maintained for each outage event. If an outage occurred in the same year a circuit was maintained, it was assumed the outage occurred before the maintenance, and the previous year of maintenance was used.

The tree-related outage data was sorted into sets, with each set identified by the number of years since the affected circuit was last maintained. Each set was then summed. The sums of outages were compared with years elapsed since vegetation management (Fig. 1). Connexus could identify a trend for the average number of outages per circuit as the years increased since the last maintenance.

The number of vegetation-related outages per circuit increased by nearly 0.2 per year. Nearly five times as many outages occurred per circuit in the 12th year than the first year after last maintenance. Equally remarkable is how close the points were to the trend line in Fig. 1. This is indicative of a strong correlation between the rate of increase in tree-related outages per circuit and the increase in time since the last maintenance.

Understanding the Magnitude

However, the comparison depicted in Fig. 1 does not show the magnitude of the outages. How many customers were affected by these outages and how does that number affect system reliability? To begin to answer these questions, as part of its second goal, Connexus endeavored to find out the ratio of CIs to the total number of customers served by the affected circuits. This ratio is a special-case system average interruption frequency index (SAIFI) metric, because it is applied only to the affected circuits managed in any given year.

What percent of the relevant customers are being interrupted because of vegetation conflicts with the primary line? If Connexus could find the trend as the years increase since the last vegetation management cycle, it could answer the question, what value will shorter vegetation management cycles provide in terms of reliability?

Like the first analysis, Connexus performed the same data sort and summed the number of CIs for each set of outages. For the circuits affected in each set of outages, the ratio of CIs to the total number of customers served by these circuits was determined. Connexus then graphed the ratio (SAIFI) versus the years since the last vegetation management cycle (Fig. 2). This gives a trend of the percent of customers affected by vegetation outages on relevant circuits as the years increase since last vegetation management.

The analysis showed each year CIs increased by an additional 1.24% of relevant customers. Extrapolating to 12 years since the last vegetation management, CIs reached nearly 21% of relevant customers because of vegetation conflicts with the primary line. This data could be used to infer what effect longer vegetation management cycles may have on the IEEE SAIFI reliability metric.

The methodologies Connexus used for its first and second goals enabled the utility to identify trends in outage data when time since the last maintenance varies widely from circuit to circuit. This predictive analysis could be used to inform decision making on the benefits that shorter vegetation management cycles may provide a utility in terms of reliability improvements and how to optimize vegetation management spending.

Further Analyses

Many other questions could be asked and answered using the tree-related outage data investigated above. For example, what additional analyses would inform decisions related to optimizing a vegetation management program? Two questions come to mind: Does the duration of an outage increase as time since the last vegetation management increases? Do outages that occur on MEDs change the outcome of the analysis?

From a reliability perspective, it is advantageous to reduce the system average interruption duration index (SAIDI) and SAIFI. From a customer perspective, the customer average interruption duration index (CAIDI) is important. SAIDI can be improved by prioritizing high-density customer facilities, but it is possible for CAIDI to be worse in this scenario. When making decisions on vegetation management, the individual customer should not be forgotten. This fact is what a cooperative’s vegetation management program is built on. Looking at reliability from a customer’s perspective led the cooperative’s vegetation management team to ask, is there an effect on the duration of an outage as time increases since a circuit’s vegetation was last managed?

To answer this question, Connexus used the total customer minutes of interruption (CMI) for each outage on each circuit and related it to when the affected circuit was last managed. The same special-case sorting and summing methodologies were used, but CMI was applied in addition to CIs to derive CAIDI. When graphing the results, Connexus found a negligible increase in outage duration as the years increase since last being managed for vegetation (Fig. 3). One might conclude CAIDI would remain relatively the same if improvements were made to the vegetation management program to reduce the vegetation management cycle length.

In general, vegetation management reduces the number of outages. It also has the potential to reduce restoration times by eliminating trees that cause the most destruction and reducing the number of trees involved with any single outage. However, that trend was not proven in this analysis. CAIDI should still be monitored in a manner that ensures optimization strategies do not neglect customers who have lesser impacts on reliability.

What happens when MEDs are included in the analysis? During the 1,826 days from 2011 to 2015, only 12 MEDs occurred as a result of vegetation-caused outages on the system. Interestingly, five of those days occurred in 2011. The vegetation management team added the additional vegetation-caused outage data for those 12 days and graphed the results in the same manner as in Figs. 1 and 2. The data is more variable, and the relationship between time last managed and outage ratios was not as strong.

Nevertheless, Fig. 4 illustrates that MEDs had a dramatic effect on electric reliability. Fig. 4 includes Fig. 1 (green line) plus the same data with the MEDs added (orange line). The number of vegetation-caused outages per circuit increased by more than 0.1 per year (the difference in trend line slopes in Fig. 4, or 0.3053 minus 0.1917), with just the addition of the 12 MEDs.

Fig. 5 compares the non-MED special-case SAIFI from Fig. 2 (green line) with MED plus non-MED SAIFI (orange line). The CIs as a percentage of exposed customers nearly doubles with the addition of MEDs (the difference in trend line slopes in Fig. 5, or 2.24% minus 1.24%). Extrapolating to 12 years since the last vegetation management, the CI trend reached nearly 35% of exposed customers due to vegetation conflicts with the primary line. MEDs are often the result of extreme weather events. Excluding MEDs, as defined by IEEE standard 1366, attempts to control for these extreme and unpredictable events. This provides Connexus with a better picture of its average daily electric reliability performance.

Trends to Consider

Tree-related outages are a concern for any vegetation management program, and electric reliability is a major issue for every utility. Overall reliability metrics, although helpful for understanding system performance, do not always give a clear understanding of vegetation-caused outage data as it pertains to vegetation management scheduling decisions. However, the method described here brings into focus the relationship between cycle length and reliability. Two measurements — one with the raw number of outages and the other with the magnitude of outages — show the same trend. As each year passes after a circuit is managed, a consistent increase occurs in the number of outages and number of customers affected.

A utility may benefit from applying this method to its vegetation management scheduling. If vegetation management on distribution is performed regularly and at the right frequency, the number of outages and customers interrupted will be reduced. This is a goal most regulators and utility executives should be able to relate to, especially if there is a cost benefit of fewer outages and more satisfied customers.

Other aspects of electric reliability and vegetation management also are important for evaluation, such as the duration of outages and impact of storms. Performing these relatively simple analyses with data will help a utility to understand, in a quantified way, how resilient its system is in weather events. It is apparent non-MED and MED tree-related outages follow similar patterns. Managing to reduce non-MED outages likely would have a positive impact on storm resiliency. ♦

Drew Combs is the system operations engineer for Connexus Energy, responsible for calculating and helping to improve the reliability of the utility’s distribution system, along with various other responsibilities related to system operations. Prior to joining Connexus in 2010, Combs worked for KJWW Engineering Consultants in Des Moines, Iowa. He received a BSEE degree from Iowa State University in 2008.

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