Start-up challenge:
Planning new electricity grid scenarios

Plexigrid wins our challenge to optimise grid capacity

PERSEO selects Plexigrid to develop a pilot to help secure long-term grid capacity through data and artificial intelligence.

October 2024

The start-up Plexigrid wins our challenge for the planning of new electricity grid scenarios thanks to its innovative solution to optimise grid capacity through data and artificial intelligence. The technology company, based in Gijón (Spain) and Stockholm (Sweden), will now have the opportunity to deploy a pilot test as part of the challenge organised by our PERSEO start-up programme together with I-DE, our distributor in Spain.

Plexigrid External link, opens in new window. has been selected after an international search process to which more than 30 different solutions have been submitted. A procedure that has culminated in the framework of the B Acceleration Week, the largest event of innovation and entrepreneurship in northern Spain, in which the technical team of I-DE could personally meet six of these proposals.

The winner will become part of the BAT Community, and will also be invited to participate in a personalised acceleration programme to boost its growth, within the framework of collaboration between Iberdrola and BAT.

Context of the challenge

Decarbonisation in our society implies the electrification of many energy-consuming industries and the integration of renewable power generation technologies. This distributed generation requires stable and flexible operation of the electricity grid, which implies significant new investments to guarantee long-term capacity. Grid management in a scenario of high integration of renewable generation, self-consumption and storage, together with the electrification of industrial processes and new demands, is evolving towards a Distribution System Operator (DSO) model. This model requires increasingly complex proactive management to optimise the capacity of its regulated assets.

The DSO needs to plan and operate a flexible grid access system using new technological tools and smart grid data to better forecast electricity flows. This requires modernising electricity demand forecasting processes. Improved grid planning seeks to develop updated methodologies to generate net demand cases in scenarios of energy uncertainty, relying on advanced artificial intelligence techniques and new analysis and calculation tools based on deep learning.

Description of the challenge

Through our PERSEO Start-up programme, we seek digital solutions that enable us to model new demand and generation scenarios in the grid, with self-consumption, storage and access flexibility, to forecast their operation and then plan their investments to guarantee the grid’s capacity, assuming a reasonable demand for electricity distribution on a five to ten year horizon.

These scenarios should take into account the evolution and geolocation of:

Current electricity demand and generation and self-consumption
Electrical storage (domestic, industrial, utilities, BESS, etc.)
New emerging demands (short term): electric mobility, heating and cooling, decarbonisation of current industrial processes, etc.
New demands in the medium and long term: digital electrification, new consumption and generation associated with technological developments and/or emerging business models (e.g. artificial intelligence, e-fuels, green hydrogen, etc.).

Solutions that do the following will be assessed favourably:

Propose automatic learning methods or algorithms to generate and validate medium/long-term scenarios to plan network needs based on forecasted demands with different levels of granularity, foreseeing that the data from the real network operation will, in turn, allow feeding into the information system to use predictive models.
Apply these algorithms to current simulations, based on historical data, and to simulations with predictive models, including parameterisation based on existing and public economic, industrial, sustainability, administrative factors as well as others.
Analyse the additional geo-referenced network capacity needed at different levels of granularity, as well as the best use of existing capacity with the available flexibility.
Identify other relevant data that is not being captured, in addition to the grid’s current state of digitisation, ranging from smart meters to the control of primary and secondary substations (LV transformer substations).
Quantify the necessary investments in the distribution network in the different scenarios and their probability in terms of necessary infrastructures and their cost, introducing a cost–benefit type evaluation or analysis.

The prize

The prize will consist of signing a collaboration and testing agreement with PERSEO or any other company in the group, which will assume the costs of those activities and provide the winner with the technical support they need, as well as a real environment and data to test the solution with, giving access to equipment, teams, infrastructures, high-tech sites and shared workspaces. The winning project will be developed in collaboration with technical specialists from Iberdrola España's Networks area.

In addition, they will be directly included in the process of joining the Global Smart Grids Innovation Hub, as an additional collaborator that will be able to benefit from the services, activities and resources made available in the GSGI Hub.

If the trial or proof of concept is successful, Iberdrola España may offer the participant the opportunity to scale the solution up by adopting it through commercial agreements. PERSEO may also consider investing in the participating company and/or in the winning solution of the challenge.

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