AI in smart grids – shaping a roadmap for Europe

The second draft of the ETIP SNET paper on the potential of AI and GenAI in Europe's smart grids draws on industry input to highlight uncertainties and challenges as well as opportunities ahead.

The paper, which is aimed to serve as a guide for unlocking AI and GenAI potential in Europe’s energy transition with a roadmap for stakeholders, is being developed drawing on the widest input of stakeholders to present a ‘consensus’ view of these evolving technologies.

Following an industry presentation of the first draft in February, the next draft was presented in a webinar on 13 March along with a 50 question poll for participants to clarify and gather further input on various topics to refine the final version of the paper for publication on 4 April.

Presenting the new introduction, Luis Vale Cunha, Chairman of ETIP SNET and Director of European Policies and Projects at Portuguese DSO E-REDES, highlighted uncertainties around the ethical aspects of AI, with the anthropomorphising of AI shifting responsibility from humans.

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There also is the need to distinguish between the ‘new AI’ and the ‘traditional AI’, with their differences in technology readiness and for example a use case such as forecasting being very mature while complex tasks requiring human agency are less mature.

As the newest form of AI, GenAI with its facets for electricity system operation also presents new potentials.

Turning to European policies and regulation, some key points that emerged from the first draft review were the classification of high risk AI systems and the distinction of grid management systems with their impacts on operating the networks.

Other issues of concern were the development pace of AI, the geopolitical landscape for AI, the significant implications of the EU’s AI Act and the compliance implications and obligations of GenAI models and systems.

Regulatory harmonisation across member states and the role of AI in energy system resilience also came under the spotlight.

Roadmap for AI and GenAI implementation

From the paper’s perspective the most challenging and important section is the roadmap for implementation of AI and GenAI solutions.

Key steps identified are investments in research, development and implementation, the development of data infrastructures and platforms, creation of an innovation friendly regulatory environment, promotion of stakeholder collaboration and workforce training and capacity building.

Insights on these will come from the 50 participant poll questions.

“Our aim is that the roadmap is capable of aligning the different stakeholders in the short, medium and long term, and also providing some actionable recommendations to these different groups of stakeholders,” Cunha explained, noting this is where the majority of the drafting effort is being focussed currently.

“Your input is key to a good roadmap and good recommendations coming out of the paper.”

Inputs are invited to any of the chapters of the draft paper, in particular on AI and GenAI technologies, use cases, pilots and projects to make these sections as comprehensive as possible.