Quantifying the risks of tree failure to guide proactive management and increase the resilience of electricity distribution networks.

强烈的暴风雨导致树木被连根拔起和折断，这反过来又会对电力供应网络造成相当大的破坏。例如，在2013/2014年圣诞节期间，英格兰东部有超过50万客户断电超过5天，这主要是由于风暴中灾难性的树木故障造成架空电力线路损坏。随着气候变化导致风暴变得更加频繁和严重，这种破坏在英国可能会变得更加普遍。通过砍伐那些靠近输电线、在强风暴中更有可能倒塌的树木，可以减少风暴对电网的破坏。不过，现时评估树木倒塌的可能性，是由测量师根据实地观察树木的情况，作出主观和定性的个人判断。这种方法缺乏一致性和科学严谨性，而且由于后勤和财政方面的限制，可评估的树木数量和重复调查的频率受到限制。该项目将通过开发一种新的方法来评估个别树木在恶劣天气下失败的风险，以解决这些限制。这将开始通过开发计算机软件，可以优先考虑树木在最大的失败风险，在景观，其中可能包含数千棵树木是接近电力线。然后，我们会针对那些风险最大的树木进行更详细的测量，特别是使用激光扫描仪，这将使我们能够对个别树木的失败风险提供更真实和客观的评估。我们将与我们的项目合作伙伴苏格兰电力公司合作，展示这种新方法如何能够帮助他们将资源用于管理最大故障风险的树木，以提高电力供应网络在恶劣天气下的恢复能力，并最大限度地减少对客户的干扰。这项研究开发的技术将有助于改善靠近公路、铁路和建筑物等其他基础设施的树木的管理，从而有助于减少风暴造成经济损失、服务中断和对人类造成伤害的可能性。

Severe storms lead to the uprooting and breakage of trees and this, in turn, can cause considerable damage to electricity supply networks. For example, over the Christmas period 2013/2014 over 500,000 customers were off supply for over five days in the East of England and this was mainly due to damage to overhead power lines caused by catastrophic tree failure in storms. This type of disruption is likely to become more common in the UK as climate change causes storms to become more frequent and severe. It is possible to reduce the impacts of storm damage on electricity networks by felling those trees that are close to power lines and are at more risk of failing in a severe storm. However, assessment of the likelihood of a tree failing is currently done by a surveyor who makes a subjective and qualitative personal judgement based on a field observation of the tree. This approach lacks consistency and scientific rigour and the number of trees that it is feasible to assess and the frequency of repeat surveys is restricted by logistical and financial constraints. This project will address these limitations by developing a new approach to evaluating the risk of failure of individual trees in severe weather. This will begin by developing computer software which can prioritise trees at greatest risk of failure across a landscape which may contain thousands of trees that are close proximity to power lines. Those trees at greatest risk will then be targeted for more detailed measurements, particularly using laser scanners, which will allow us to provide more realistic and objective assessments of the risk of failure of individual trees. We will work with our project partners Scottish Power to demonstrate how this new approach is able to help them target their resources for managing trees at greatest risk of failure, in order to increase the resilience of electricity supply networks in severe weather and minimise disruption to customers. The techniques developed in this research will be valuable for improving the management of trees that are in close proximity to other infrastructure such as roads, railways and buildings, thereby helping to reduce the likelihood that storms will cause financial losses, disruption to services and harm to humans.