Application of observational weather data in evaluating resilience of power systems and adaptation to extreme wind events
In Great Britain, 70% of wind-related faults on the transmission power network are attributed to the top 1% gusts. These faults cause outages to millions of customers and have extensive cascading impacts. This study illustrated the application of historical ground measured wind data in a multi-phase resilience analysis process by: (i) projecting an extreme wind event, (ii) assessing components’ vulnerabilities, (iii) analysing system’s response, (iv) quantifying baseline resilience, and (v) evaluating the effectiveness of selected adaptation measures. The extreme event was modelled as a ubiquitous 100-year return gust event impacting upon the operations of the Reduced Great Britain transmission network test case. The results show an unmet demand of about 569 GWh/Week. Adaptation measures were necessary for 60% of transmission corridors with responsiveness improving resilience by 70%, robustness by 55%, and redundancy by 35%. The study implies that resilience enhancement can be prioritized within high potency corridors and organisational resilience could prove to be more effective than infrastructural and operational resilience.
History
School
- Mechanical, Electrical and Manufacturing Engineering
Research Unit
- Centre for Renewable Energy Systems Technology (CREST)
Published in
Energy and Sustainable Futures: Proceedings of the 3rd ICESF, 2022. ICESF 2022.Pages
127-136Source
The 3rd International Conference on Energy and Sustainable Development (ICESF)Publisher
SpringerVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher statement
This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.Acceptance date
2022-08-09Publication date
2023-08-12Copyright date
2023ISBN
9783031309601Publisher version
Book series
Springer Proceedings in EnergyLanguage
- en