UK Power Networks Partners with GE Digital on Smart Substation Project

GE Digital announced that it is partnering with its valued customer UK Power Networks on a world-first smart substation project.

December 10, 2021. By News Bureau

GE Digital announced that it is partnering with its valued customer UK Power Networks on a world-first smart substation project.

The project, known as Constellation, is designed to optimize utilization of the distribution network to facilitate the rise of renewable energy generation across the United Kingdom.
 

Constellation is a world-first innovation project that will see powerful computers installed in a series of substations, turning them into smart substations. To do this, Constellation will leverage advances in software engineering, machine learning, and system optimization to make substations interoperable and secure.

The project aims to release 1.4 GW of capacity (enough to power more than 700,000 homes) and save consumers more than £750 million by 2050. It is also forecast to save more than 17.8m tons of harmful greenhouse gas emissions by 2050.

A key aspect of Constellation is the installation of GE Digital’s PhasorController in substations to enable the deployment of multiple smart applications.

This will include functionality to optimize distribution network utilization and contribute to net-zero targets while reducing the need for investment in additional infrastructure.

Ian Cameron, head of customer service and innovation at UK Power Networks said: “UK Power Networks is adapting to increasingly complex power flows by becoming smarter so we can safely release more capacity and enable more renewable energy to connect at lower cost – saving customers money and helping the environment at the same time. We already have smart control rooms and grid edge devices like smart electric vehicle chargers. Having smart substations in the middle pulling it all together is a logical next step.”

PhasorController distributes intelligence and control to the substation and Distributed Energy Resources (DER) connections to complement the existing central control, providing resilience and continuity of DER operation when communications links are unavailable. Currently, when a utility loses communications, it will fall back to safe power level which can lead to time periods when DER cannot operate.

The solution uses data analytics and machine learning (ML) to incorporate data from periods when communication and the network is managed normally. This then trains Machine Learning models centrally and then distributes the models to the local renewable generation controls, so they are ready to go live if/when communications are lost.

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