Apr 2013
Electricity Distribution
Network Resilience to Weather
Apr 2013
Scottish and Southern Electricity Networks
SSEN Future Networks Team
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Innovation Funding Incentive
LV & 11kV Networks
The Met Office has previously worked closely with UK energy companies on EP2, an innovative project looking at the effects of climate change on the energy industry.

During this project the potential impacts of climate change on the frequency of weather-related network faults was identified as an area of particular interest. A preliminary analysis was undertaken in WP3 where historical data of both network faults and various weather variables were collated and analysed.

This project facilitates the development of a statistical model to encompass the relationships between weather-related faults and different weather variables. The objective of this model would be to drive it with projections of climate variables to investigate how the future frequency of faults may change over time.

The project was undertaken in two stages which were:

  • Completion of a baseline survey for each distribution/ transmission license area

  • Applying future climate projections to the baseline in order to assess future risk.
The project investigated the potential impact of climate change on UK electricity networks, in order to identify whether the networks risk to weather-related faults may change in the future as a result of climate change.

To carry out a full climate change risk assessment, the networks baseline risks to climate were assessed; this baseline knowledge being essential to enable a future assessment of risk. Next, the relationships between faults and weather derived for the baseline were driven with future projections of climate to assess how the networks risk to climate may change in the future.

This project has developed innovative techniques to combine climate model output with historical fault data to project future distributions of weather-related network faults. These can then be used to assist with future long-term investment decisions and in particular identifying areas of the network that would benefit from adaptation measures.