AI-Driven Energy Management Systems for Flexible Power Consumption

This Professional Doctorate (PD) research addresses the urgent problem of electricity grid congestion in the Netherlands, caused by the growing use of renewable energy and the electrification of homes and businesses. To ensure a reliable and sustainable energy system, smarter and more flexible ways to manage energy demand and supply are needed.

The PD project is part of FlexLab, a collaborative innovation lab that brings together grid operators, technology companies, and academic partners. Within this environment, the focus is on the design, engineering, and integration of advanced, AI-driven Energy Management Systems (EMS) that can adapt to real-world challenges. This work is centered in Work Package 3 (WP3), where the process of integrating cutting-edge forecasting and optimization technologies—developed in other parts of FlexLab—and ensuring seamless operation in practical settings is led.

The PD involves developing and refining EMS prototypes through hands-on testing in real-life pilot projects with partners such as AIMZ, Simpl.Energy, and Vitens. Close collaboration with industry stakeholders enables iterative improvements, resulting in systems that are technically robust, user-friendly, explainable, and ready for broader adoption. Emphasis is placed on open-source development and knowledge sharing to ensure solutions benefit the wider energy sector.

Overall, this PD aims to bridge the gap between academic research and industry needs by delivering EMS solutions that help reduce grid congestion, support the energy transition, and are ready for use in practice. The approach ensures continuous feedback and improvement, enabling the energy system to become more efficient, flexible, and future-proof.