Planning for the future

The report argues that grid capacity is a strategic asset for attracting AI and data centre investment in Europe. It recommends anticipatory grid planning, the creation of priority AI zones outside major cities like London and Paris, joint spatial planning with clean energy developers, and the adoption of flexible grid connection contracts to reduce deployment queues.

• Grid capacity has evolved into a critical resource and a primary attraction for major investors in Europe's data centre sector. To maintain competitiveness in the global AI race, European grid planners must adopt more anticipatory and forward-looking planning practices, as the rapid development of AI requires energy infrastructure capable of accommodating data centre expansion.
• Governments and regulators should treat power grids as strategic infrastructure for economic growth. National grid development plans need to account for AI, electrification, flexibility, and digitalisation to attract high-value industries, particularly since data centre investment cycles are significantly shorter than those of grid infrastructure.
• To manage grid congestion, governments can implement priority AI zones by directing projects toward areas with better grid availability, such as locations outside of capital cities. This approach is currently being tested in concentrated hubs including London and Paris.
• Long-term optimization can be achieved through joint spatial planning between data centre investors, clean power developers, and grid operators. Placing high electricity demand nodes near clean energy supply reduces the need for grid investment and allows data centres to lower costs via near-site Power Purchase Agreements (PPAs).
• Short-term deployment of data centres can be accelerated through smarter connection deals, such as non-firm or phased grid connection options, which reduce queues and improve infrastructure utilization. Furthermore, pilot projects on data centre flexibility could unlock capacity in constrained areas and lower balancing costs, though this requires further research and development funding.
• The implementation of these strategic recommendations depends on the availability of high-quality data. Necessary datasets include data centre demand profiles, investment prospects, locations, utilisation scenarios, demand-side connection queues, and grid capacity maps.

APA

Ember (2025). Planning for the future. https://ember-energy.org/chapter/conclusion/

Chicago

Ember. Planning for the future. 2025. https://ember-energy.org/chapter/conclusion/.

Wikipedia

{{cite report |author=Ember |title=Planning for the future |date=19 June 2025 |url=https://ember-energy.org/chapter/conclusion/ |access-date=17 August 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{ember2025planning, author = {{Ember}}, title = {{Planning for the future}}, institution = {Ember}, year = {2025}, month = jun, url = {https://ember-energy.org/chapter/conclusion/}, urldate = {2026-08-17}, note = {Indexed by Climate Insights Directory} }