Can you describe your project in a few words?

The main goal of this project is to make accurate forecasts on the network’s future behaviour, taking into account, among other topics, problems related to the increasing integration of Distributed Energy Resources in LV networks.

For Medium and Low voltage networks, with thousands of electrical Transformation Centres (from now on, TC) widely distributed geographically, with coverage and connectivity problems, and with near-real-time needs in taking power decisions, Cloud is an option with limited viability due to latency, cost or scalability problems. SCADA technologies, highly oriented towards automation and with proprietary data structures, are not flexible and accessible and do not optimally cover the needs.

The solution is halfway between the Cloud and SCADAs: it is called Edge Computing.

The consortium members intend to distribute data analysis and decision-making among the different Edge Computing nodes, or distributed computing, located in adjacent TCs (e.g., in the same Medium Voltage ring) instead of sending this data to centralised servers (Cloud).

At Barbara, we are fast-tracking the digitalisation of the industry. Our mission is to facilitate the deployment of Artificial Intelligence at the Edge. We are the Challengers sector with a clear vision of where the future is headed and with the technological solution that allows for the creation, deployment and execution of Edge Computing algorithms in a secure and scalable way.

Cuerva is the partner who will help implement the AI solution. Cuerva is a multidisciplinary company within the energy sector whose main activities are Distribution, Generation, Commercialisation and R&D&I activities.

Cuerva is leading the digitisation of its network and utilising cutting-edge techniques to control and monitor its components. Thanks to its previous efforts, Cuerva has achieved the advanced digitisation of some strategic points in its network. One of those areas is the one proposed in this project, Lachar (Granada), whose network is highly digitised and monitored by implementing the Barbara IoT technology in the Edge Node. With these systems already installed, we propose their improvement:

• Including new Cuerva algorithms will allow the DSO to fully understand the network’s behaviour and predict future problems in the short term.
• Proposing practical solutions to those issues via the actions of various Flexibility Service Providers (FSPs).
• Integration of these algorithms and decisions into a replicable framework will allow other European DSOs to improve their network’s state.

What is the AI solution the project plans to implement?

The objective of the AI Solution is to develop a forecasting algorithm that will be able to overcome the limitations described before and predict, with accuracy, the demand and production values of the consumers connected to the transformation centre. During this project, a Digital Twin of the grid will also be developed, and through this, Cuerva will be able to detect events in the grid that could put the supply at risk.

The increasing number of Distributed Energy Resources throughout the Low Voltage Grid (a less digitised part of the grid itself) is increasing overvoltage and congestion events. This project aims to have a perspective on how the grid will behave in the future and to address techniques that solve the problems detected.