Apr 2013
Electricity Distribution
Network Resilience
Apr 2013
Electricity North West Limited
Electricity North West Innovation Team
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Innovation Funding Incentive
LV & 11kV Networks
Electricity North West was one of a number of collaborating partners who supported the IFI funded Met Office EP2 project during 2007/2008. As part of EP2, weather related network faults for both the distribution and transmission networks were analysed in conjunction with the met office weather data for the period 1980 to 2007 and this preliminary study allowed a basic understanding of the dominant fault causes and their relationship with weather and the relevance of large scale atmospheric motion on network faults although this initial work offered little granularity for individual companies. The final reports were discussed at some length by the various partners and one aspect distribution companies identified that merited further work was the potential impacts on network resilience under various climate change projections.
A level of uncertainty exists within the industry relating to the variations in network design standards and their level of inherent resilience to weather conditions therefore this project was initiated to outline the basic requirements and investigate the possibility of delivering a realistic output. The study will develop the specific user requirements by consultation (based on what should be included i.e. lightning faults, rain faults, snow sleet and blizzard faults, freezing fog faults, wind and gale faults, solar heat faults, flooding faults, site specific and area representative wind resources) and then assess the various methods of modelling their effects on fault rates and network resilience.

There is low confidence associated with directly modelled winds in climate models and EP2 identified that weather type analysis (because the synoptic pattern is larger scale) may provide an alternative method to project wind and thus wind related faults and wind resource. The project will include an assessment of the potential confidence factors associated with various modelling techniques and include detailed minimum and optimum outputs for a range of timescales (5 days, 5 – 10 years and 40 – 50 years).