The Dutch energy system is undergoing fundamental change. The electrification of mobility, industry, and the built environment is driving up demand for electricity, while the supply is shifting toward weather-dependent, decentralized sources. Grid congestion is already limiting the expansion and sustainability efforts of households and businesses in large parts of the country; energy is relatively expensive in the Netherlands; and geopolitical tensions call for greater independence and resilience. As a result, reliability, affordability, and sustainability are under pressure.
This energy transition is complex and cannot be achieved overnight. The Netherlands and Europe still rely in part on other countries for fossil fuels and critical raw materials, which makes us vulnerable to supply shocks and price fluctuations. High energy prices and grid congestion undermine the competitive position of Dutch and European companies and hinder investments in sustainability.
AI in Energy and Sustainability
The energy sector relies on physical systems, and the laws of nature determine how they behave. Every decision has an immediate, measurable impact on energy consumption, grid stability, and emissions. AI plays a role throughout the entire energy value chain: in system optimization and balancing, in engaging flexible end users, and in planning, implementing, and maintaining infrastructure more quickly. Generic language models do not control such physical systems. This requires energy-specific physical and world models, trained on a shared data and computational foundation: hybrid physics-ML models and digital twins—virtual replicas in which you can safely test an intervention first.
For more generic tasks, such as reporting, knowledge management, smart maintenance, and permitting, the sector is already using language models, though limited metering and data sharing still hinder their application. Sustainability also applies to AI itself: grid-responsive, energy-efficient computing power and AI that maps the circularity of energy assets. The major breakthroughs lie further ahead: autonomous grid optimization, self-learning energy systems, and AI-driven material discovery.
Vision
AIC4NL’s Energy & Sustainability division connects grid operators, energy companies, energy communities, AI scale-ups, research institutions, and government agencies. Together, we bring AI from research and development into practical application within the energy system. The goal is an energy supply that is sustainable, affordable, and independent, and that keeps our economy competitive. Security, explainability, and sovereignty are prerequisites for this.
“We are working toward an energy system that largely regulates itself: AI that continuously balances supply, demand, and storage. That future won’t happen on its own. We are building it now, drawing on our knowledge of both the energy system and AI, and with everyone who wants to participate.”
Marcel Postema, Practice Leader for Energy and Sustainability
