ScottishPower Energy Networks (SPEN) is leveraging artificial intelligence (AI) to predict faults in their electricity network and restore power more efficiently. The £5 million Predict4Resilience project is described as “revolutionary” and will use AI to forecast potential outages up to a week in advance. By analysing historic weather and fault data, as well as network asset and landscape information, machine learning models will be developed to predict where and when outages may occur. Real-time weather forecasting will also be incorporated to provide control room staff with more accurate information on upcoming severe weather events and expected damage.
The trial of this AI technology comes on the heels of Storm Babet, which caused power outages for several homes in Scotland. Guy Jefferson, chief operating officer at SPEN, explained the importance of being well-prepared for severe weather events. He stated, “Ahead of a severe weather event, we mobilise hundreds of engineers, vehicles, and generators so we are ready to restore power as quickly and as safely as possible. Projects like Predict4Resilience offer us another tool to help inform our decision making during a storm and reduce the time it takes us to restore power.”
The project has received £4.5 million in funding from the Strategic Innovation Fund, which supports innovative projects that contribute to the transition to net zero. SPEN is collaborating with partners such as the University of Glasgow, SSEN Distribution, and management consulting firm Sia Partners to develop the AI methods underlying the forecasting capability. Jethro Browell, a senior lecturer in statistics at the University of Glasgow, expressed enthusiasm about the project, stating, “We are excited to be working with a great team of partners to make our electricity networks more resilient in the face of climate change.”
Sebastien Gerber, head of data science and AI in the UK and Ireland at Sia Partners, anticipates that Predict4Resilience will bring significant benefits to the networks and their customers. He mentioned the importance of creating a more resilient network that minimises disruption and stress, especially for vulnerable customers. With the ability to predict outages in advance, power companies can allocate resources more efficiently and potentially reduce downtime for customers.
This trial marks an important step forward in the integration of AI technology within the power industry. By harnessing the power of machine learning and weather forecasting, power companies like SPEN can improve their response to severe weather events and ultimately reduce the impact on customers and communities. As AI technology continues to advance, its applications in various sectors become increasingly evident, revolutionizing the way we approach and solve problems.
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