Laying the foundations for a weather pattern conditioned power outage forecasting system in the United Kingdom

Links between weather patterns and power system failures across seasons in the United Kingdom could help distribution network operators to better protect themselves from disruptive weather
Laying the foundations for a weather pattern conditioned power outage forecasting system in the United Kingdom
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Across the winter of 2023/24, the UK has experienced 10 named storms and two spells of cold weather (with ice and snow warnings), with a broad range of impacts.  In January 2024, Storm Isha struck across the United Kingdom.  While impacts on airplane landings made a splash across social media and the news, in excess of 350,000 homes were left without power across the UK according to the Energy Networks Association, with tens of thousands experiencing a “multi-day event” and the associated impacts on their daily lives. It is well known that different weather phenomena such as: lightning strikes, high winds (especially gale force winds), snow and ice, are common causes of power system failures, and their frequency of occurrence varies depending on weather conditions and seasons. In previous works, the probability of occurrence of power outages caused by extreme weather was obtained from exposure and fragility modelling of individual system components. Some of these efforts relied on weather forecasts to prepare for widespread power outages induced by extreme weather event. Others identified the meteorological conditions which led to major power outages with the objective of providing reliable meteorological data for distribution network operators. However, none of them considered that the occurrence of different types of weather-induced power system failures is related to specific large-scale atmospheric circulation types, which we refer to here as weather patterns. None of them looked at relationships between these weather patterns and power system failures with the objective of identifying relevant trends to predict and prepare for power outages.

In our “Identification of weather patterns and transitions likely to cause power outages in the United Kingdom” paper, we extended the application of an existing set of 30 Met Office daily weather pattern definitions to the electricity infrastructure, by expanding the analysis from previous works by the authors to different severe weather event categories. In this interdisciplinary collaborative work involving researchers from the University of Bristol and the Met Office, we envisaged to provide answers to the following two main questions:

1) Are weather-induced power outages in the UK related to specific weather patterns / weather pattern transitions across seasons?

2) Can we improve current practices adopted to predict weather-induced power outages by using information about weather patterns and pattern transitions?

We analysed large datasets of weather patterns and power distribution network failures, taking advantage of our collaboration with the Met Office, Northern Powergrid, Scottish Power Energy Networks, and Energy Networks Association. More specifically, we analysed the occurrence of 30 pre-defined daily weather patterns along with nearly 70,000 power system failures in the UK between 2010 and 2019 and two smaller complementary datasets of regional power system failures.

We identified high-risk weather patterns, as well as weather pattern transitions and persistence, likely to cause power outages across seasons in the UK. We identified relevant trends between weather patterns and power system failures caused by different weather phenomena, such as wind and gale, lightning strikes, snow and ice. Winter weather patterns characterized by high wind speeds and high precipitation volumes are responsible for many instances of power outages caused by wind and gale and lightning strikes. Weather patterns with moderate to high snowfall are often linked to power outages caused by snow and ice. We found very similar trends between weather patterns and weather-induced power system failures using a large dataset for Great Britain and two smaller complementary datasets representing Southern Scotland and Northeast England.

An important implication of this work is the potential for a development of a weather pattern-conditioned fault forecasting system for distribution network operators. Firstly, because our findings highlight that in most cases there are relevant connections between each type of fault and a set of relevant weather patterns, that tend to persist or transition between each other with high probability. Secondly, because the high-risk weather patterns identified in our work are shown to have good levels of predictability with valuable lead time (i.e., up to several weeks in advance), overcoming limitations in the temporal resolution of current practices adopted by UK distribution network operators to prepare for extreme weather. These clear links between specific weather patterns / pattern transitions and power outages can significantly improve the preparedness of the United Kingdom distribution network operators for adverse weather conditions.

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Energy Security
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences > Energy Policy, Economics and Management > Energy Security
Energy Grids and Networks
Technology and Engineering > Electrical and Electronic Engineering > Electrical Power Engineering > Energy Grids and Networks
Energy Supply and Demand
Physical Sciences > Earth and Environmental Sciences > Environmental Sciences > Energy Policy, Economics and Management > Energy Supply and Demand
Atmospheric Dynamics
Physical Sciences > Earth and Environmental Sciences > Earth Sciences > Atmospheric Science > Atmospheric Dynamics
Natural Hazards
Physical Sciences > Earth and Environmental Sciences > Earth Sciences > Natural Hazards

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