SP Energy Networks turns to AI to forecast power demand and generation

The software will be used in the real-time management of the network and forward planning when assessing the impact of new connections across the system

SP Energy Networks is investing in cutting-edge software that applies machine learning algorithms and data science to predict electricity network demand and generation output.

The artificial intelligence (AI) forecasting software, which uses historical network data and detailed weather data to make the predictions, will enable the network operator to maximise capacity and reliability across the electricity distribution network.

Sia’s software will go live in March 2020 and will be used in the real-time management of the network and forward planning when assessing the impact of new connections across the system.

The investment comes as Britain’s electricity network experiences a rapid transition from fossil fuel generation to renewable energy, low carbon options and energy efficiency programmes.

Grant McBeath, Control Room Manager at SP Energy Networks, said: “Demand on the network is forecast to increase considering all future energy scenarios as we transition towards a zero carbon economy. We, therefore, have to change the way we manage the network – transitioning from passive approach to much more active and agile management, which requires a more dynamic approach to ensure capacity is maximised and customers’ supplies remain uninterrupted.

“Working with Sia on forecasting software will allow us a better understanding of the future flows of energy on the network right down to a half hourly basis. This will ultimately allow my team to ensure the network is optimised to deliver the supply resilience and customer service our customers expect and deserve.”

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