Storm Risk Assessment of Interdependent Infrastructure Networks

相互依赖的基础设施网络的风暴风险评估

• 批准号: NE/N012852/1
• 负责人: Richard Dawson
• 金额: $ 20.56万
• 依托单位: Newcastle University
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FN012852%2F1
• 关键词: Storm; Risk; Assessment; Interdependent; Infrastructure

Electricity infrastructure provides a vital services to consumers. Across the UK there are thousands of miles of overhead lines and other assets that are vulnerable to a number of environmental risks. Wind risks have caused more disruptions to power supplies in the UK than any other environmental risks. Despite their importance, the future risks associated with windstorm disruption are currently highly uncertain as the coarse spatial resolution of climate models makes them unable to properly represent wind storm processes.STRAIN will address two challenges for infrastructure operators and stakeholders who are urgently seeking to understand and mitigate wind related risks in their pursuit to deliver more reliable services:(i) Build upon state-of-the-art modelling and analysis capabilities to assess the vulnerability of electricity networks and their engineering assets to high winds. This will consider the impact of different extreme wind events, over different parts of the electricity network, the households and businesses connected, and also apply a model representing infrastructure inter-connections to understand the potential impact on other infrastructures that require electricity such as road, rail and water systems.(ii) Climate models provide very uncertain wind projections, yet infrastructure operators require an understanding of future climate change to develop long term asset management strategies. To provide the necessary information we shall work with the Met Office and benefit from new high resolution simulations of future wind climate using a 1.5km climate model. These simulations have proven capable of representing convective storm processes, that drive many storms across the UK, and have already proven that they better capture extreme rainfall events.These methods will be applied to a case study of an electricity distribution network. These are more vulnerable to windstorms than the high voltage national transmission network.STRAIN will therefore, by synthesising and translating cutting-edge research, provide electricity distribution network operators with a significantly improved understanding of wind risks both now and in the longer term. This will improve the reliability of electricity supply to UK consumers including other infrastructure providers reliant on electricity distribution networks, and reduce costs by enabling more effective allocation of investments in adaptation and asset management. Furthermore, it will help other infrastructure service providers better understand the impacts of electricity disruption on their own systems, and plan accordingly. The improved understanding of future extreme wind storms will provide benefits across an even wider group of infrastructure and built environment stakeholders.

电力基础设施为消费者提供重要服务。在英国各地，有数千英里的架空线路和其他资产容易受到一些环境风险的影响。风力风险对英国电力供应造成的干扰比任何其他环境风险都多。尽管其重要性，与风暴中断相关的未来风险目前高度不确定，因为气候模型的粗糙空间分辨率使其无法正确地表示风暴过程。STRAIN将为基础设施运营商和利益相关者解决两个挑战，他们迫切寻求了解和减轻与风相关的风险，以追求提供更可靠的服务：（i）利用最先进的建模和分析能力，评估电力网络及其工程资产易受大风影响的程度。这将考虑不同极端风事件对电网不同部分、连接的家庭和企业的影响，并应用代表基础设施互连的模型，以了解对其他需要电力的基础设施（如公路、铁路和供水系统）的潜在影响。(ii)气候模型提供了非常不确定的风力预测，但基础设施运营商需要了解未来的气候变化，以制定长期的资产管理战略。为了提供必要的信息，我们将与英国气象局合作，并利用1.5公里气候模型对未来风气候进行新的高分辨率模拟。这些模拟已被证明能够代表对流风暴过程，驱动许多风暴在英国，并已证明，他们更好地捕捉极端降雨事件。这些方法将被应用到一个配电网络的案例研究。因此，STRAIN将通过综合和转化前沿研究，为配电网络运营商提供对当前和长期风风险的显著改善的理解。这将提高对英国消费者的电力供应可靠性，包括依赖配电网络的其他基础设施供应商，并通过更有效地分配适应和资产管理投资来降低成本。此外，它将帮助其他基础设施服务提供商更好地了解电力中断对其系统的影响，并相应地进行规划。对未来极端风暴的进一步了解将为更广泛的基础设施和建筑环境利益相关者带来好处。

项目成果

A Spatial Network Model for Civil Infrastructure System Development

• DOI: 10.1111/mice.12204
• 发表时间: 2016-09
• 期刊: Computer‐Aided Civil and Infrastructure Engineering
• 作者: G. Fu;S. Wilkinson;R. Dawson

A systems approach to assess the resilience of future infrastructure networks

评估未来基础设施网络弹性的系统方法

• 发表时间: 2018
• 作者: Dawson RJ

A geospatial modelling framework to assess flood risk under future scenarios of urban form (vision paper)

用于评估未来城市形态情景下洪水风险的地理空间建​​模框架（愿景文件）

• DOI: 10.1145/3557915.3560945
• 发表时间: 2022
• 作者: Burke R

Enhanced Urban Growth Modelling: Incorporating Regional Development Heterogeneity and Noise Reduction in a Cellular Automata Model - A Case Study of Zhengzhou, China

• DOI: 10.1016/j.scs.2023.104959
• 发表时间: 2023-09
• 期刊: Sustainable Cities and Society
• 影响因子: 11.7
• 作者: Xuanchi Chen;Zongmin Wang;Haibo Yang;Alistair C. Ford;Richard J. Dawson

Integrated Approach to Assess the Resilience of Future Electricity Infrastructure Networks to Climate Hazards

• DOI: 10.1109/jsyst.2017.2700791
• 发表时间: 2018-12-01
• 期刊: IEEE SYSTEMS JOURNAL
• 影响因子: 4.4
• 作者: Fu, Gaihua;Wilkinson, Sean;Mancarella, Pierluigi
• 通讯作者: Mancarella, Pierluigi