Development of a Regional Research Approach to Modeling Tree Failure Risk Probability Affecting Distribution Overhead Lines
2019, Gregory A. Dahle, PhD, Co-PIs Rick P. Voland, Ph.D., Ryan R. Brockbank, Paul J. Appelt, Environmental Consultants, LLC d.b.a. ECI
Electric utilities and regulators are constantly evaluating means to improve both reliability and public safety while also reducing cost. As trees are among the most frequent causes of interruptions and represent one of the largest maintenance costs, vegetation management is a frequent subject of inquiry.Recent development in tree risk management has moved the arboriculture industry from simply identifying hazard trees, toward a Tree Risk Assessment process where both the risk and consequences of a tree failure are taken into account. The primary inputs include the likelihood of failure, likelihood of impact and consequence of the potential impact to derive a risk rating that ranges from low to extreme. While determining the likelihood of impact and the potential consequence has a degree of subjectivity, these two inputs are reasonably objective. Yet, determining the likelihood of failure continues to be a challenging task as there are a large host of factors that potentially influence the tree stability. Which explains why understanding the probability of tree failure is listed as one of the Utility Arborist Association’s top 5 research priorities. Trees continue to be among the leading causes of electric distribution system service interruptions. Tree maintenance is often the largest O&M expenses. Utilities are increasingly looking beyond routine maintenance zones to address tree conditions that may lead to interruptions. Failure can be categorized as either from roots, stems or branches. Our team will review what is known about failures from these three zones, concentrating on why seemingly healthy trees fail. The approach of investigating why seemingly healthy trees fail is important as it has been reported that as many as 50-65% of failures take place in trees with no externally detectable defects. This suggests the utility arboriculture industry has much to learn as to why trees fail and how to predict the likelihood of failure. Development of failure risk probability models to include observable and non-observable defects and lack thereof within severity ranges will help utilities and regulators better understand the risks and benefits of programs designed to further reduce tree-caused outages over specific time periods. Environmental and fiscal responsibility can be enhanced through prioritization of high failure probability conditions.The project will result in a technical report that explores key issues, summarizes the literature review and provides a basis for future investigations.On the basis of the literature review and associated work outlined in work scope, a technical report will be developed. A summary of findings will be prepared for publication in the UAA Utility Arborist Newsline and Arboriculture & Urban Forestry journal. The results of this project will lay the groundwork for a future project by identifying the methodology, protocols, and criteria for designing that future study to collect tree failure data and develop failure models. The models may be used by utility vegetation managers to:
1. Identify high risk trees that may lead to tree-caused outages, thereby reducing total tree outages.
2. Reduce tree risk mitigation costs by identifying and prioritizing risk factors for tree failure.
3. Reduce safety concerns to the public by mitigating wire-downs from tree failures.
4. Reduce property damage by mitigating tree failures.
5. Improve customer satisfaction through improved quality of service.
Year: 2019
Funding Duration: 1 year
Grant Program: UAA Sponsored Grant
Grant Title: Development of a Regional Research Approach to Modeling Tree Failure Risk Probability Affecting Distribution Overhead Lines
Researcher: Dr. Gregory A. Dahle
Key words:
Peer Reviewed Publications from Grant:
General Audience/Trade Publications:
Professional Presentations:
For more information on this project, contact the researcher via TREE Fund at treefund@treefund.org.