Outage Statistics As a Basis for Determining Line Clearance Program Status. Guggenmoos, Siegfried
Abstract: Outage statistics are the most meaningful measure of the success or failure of a line clearance program. Using vegetation inventories as a basis for modelling budget impacts on future outages and budget requirements represents a powerful tool for securing adequate funding. The combination of outage history and predictions can be used to demonstrate due diligence, thereby managing the risk associated with tree-conductor contacts.
Outage statistics are the most meaningful measure of the success or failure of a line clearance program. They are a powerful tool for assessing current program status and can provide an indication of future trends. Outage statistics provide information about how the tree inventory changes and this, in turn, can be used to make economic forecasts.
Why do we clear trees from around energized lines? The standard answer is to increase reliability and safety. Reliability is a quality of service issue. Quality of service is measured by the customer, not by company programs and initiatives. Will reliability be more or less important in a deregulated electric industry, where the customer has a choice in suppliers? In a 1993 survey, TransAlta Utilities (TAU) customers were asked to rate twenty service factors in terms of importance and how they perceived TAU’s performance on each of these. Reliability topped the list in importance at 98.8%. Cost was sixth.
Providing safe service in this litigious age, is managing a liability. Each tree-conductor contact holds the potential for human exposure. I believe the associated risk is greatly underestimated by utilities. If CEO’s and directors were cognizant of the unavoidable personal liability they assume for tree-conductor conflicts, utility foresters would be struggling to exceed industry standards rather than arguing for a budget based on a tree inventory.
The personal liability of directors is illustrated by the fact a judge in London, Ontario imposed not only heavy personal fines but also jail terms against directors and a senior executive of Bata Industries Ltd. for the release of an environmental contaminant. There was no associated death or injury reported. The judge reasoned that it is the responsibility of directors to ensure the legal and safe operation of the company. In this case, the two who had direct knowledge of the pollution activity were given jail terms. And while it seems outlandish that a jury would have McDonalds restaurants transfer millions of dollars to a woman seemingly surprised to learn that coffee is sold hot, the implications of a suit for damages against a utility whose product is admittedly potentially lethal are frighteningly severe.
My thoughts on the potential utility of outage statistics first coalesced in a struggle to salvage TransAlta Utilities’ Forestry or Line Clearance program as funding was cut. What might studying outages yield? Using data from TAU we can explore if there is a pattern to outages. Figure 1, which shows TAU’s outage history in customer hours lost for the years 1978 through 1984, suggests it may be exponential. Figure 2 shows the budget through this same period. It too appears to be increasing exponentially. In Figure 3, budget and outage statistics are overlaid to determine if there is any apparent relationship between the two. This chart showing both expenditures and outages expanding exponentially has the potential to alarm management to the point of undertaking a whole new course of action as was the case at TAU. It does appear that outages respond to sharp budget increases though it may take more than a year for the result to manifest.
Speculating about outages we would anticipate if the right amount of money was spent, that is the budget were linked to a tree inventory, we could expect outages to drop and equilibrate at a new, lower level. This new level would reflect operational and environmental factors such as: tree inventory; the clear distance; tree species characteristics; environmental factors such as weather events; insect and disease damage. The outage history at TAU confirms this speculation (Figure 4). From 1992 on budgets have been increasingly divorced from the inventory and outages are increasing.
In categorizing the factors affecting the number of tree related outages, we find clear distance is the most important since it is the only factor we control (Figure 5). While nature has provided a certain tree density, clear distance dramatically impacts the inventory capable of striking the line and hence outage probability.
We used outages for making program choices at TAU. Faced with budget reductions in 1992, prior to the completion of the first cycle, we wondered if we should simply hotspot the untouched areas until such time as the budget shortfall was rectified. We concluded the hotspotting would increasingly draw resources away from the maintenance grid eventually sinking the whole program (Figure 6).
Outages and budget are linked through inventory. The potential impact of underfunding the program has also been assessed (Figure 7). While the impact of underfunding a program is not very perceptible for a few years, the budget required to return outages to the low equilibrium level is quite significant and begins to show after five years.
Creating hypothetical situations for TAU permit a revealing economic comparison. In the first case (Figure 8) we assume the utility links the budget to the tree inventory. This requires a temporary but substantial increase in budget. Outages drop and level off at about 20,000 customer hours. In the second scenario (Figure 9), we assume TAU’s budget was frozen at the 1985 level. Outages increase and will of course eventually level off. At the end of 12 years, outages are in excess of 300,000 customer hours.
Comparing the dollars invested in line clearance and placing a value on the residual inventory after the 12 years we find in present value terms, the program with the budget linked to inventory cost 18.5% less. We could also say the program based on the inventory has an internal rate of return12.5%.
With returns like that, perhaps there is a ray of hope for line clearance programs. Use of outage statistics may get you the attention you need and deserve for your program.
Figure 1 Figure 2
Figure 3 Figure 4
Figure 5 Figure 6
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About the author:
Siegfried Guggenmoos, B.Sc.(Agr.), P.Ag. holds a degree in agriculture with a horticulture major from the University of Guelph, Ontario. He has been involved in research on growth regulators and herbicides; was the general manager of one of Canada’s major vegetation management contractors; Supervising Forester at TransAlta Utilities, 1985-1995, designing, implementing and assessing vegetation management programs and contracting methods; currently president of Ecological Solutions Inc. (Ecosync), Sherwood Park, Alberta.