PHD candidate
Naud Loomans
- Eindhoven University of Technology
- +31 6 15249535
- n.loomans@tue.nl
- Work package 10: Integral models
- Agent-based renewable energy models

Working on agent-based energy transition models I explore and analyze robust pathways to accelerate the energy transition. The models enable me to take a broad perspective to transition pathways, from technologically and economically feasible scenarios towards socially preferred transitions. We do this by adding transition theories, market behavior and human preferences to the analysis of net-zero energy systems.
More specifically I am focussend on the interlinkages between different societal and technological domains within the energy transition, such as sector-coupling and ‘smart energy systems’. Some transition pathways will lead to tremendously costly lock-in effects while other will accelerate coinciding technologies. To get a grip on the numerous dynamics within the energy and mobility transition a comprehensive system overview is required. Agent-based socio-technical energy transition models are for me a tool to structure these dynamics, combine them in a single system overview, and find out how they affect each other.
The models are not just a tool for me to understand the system myself, they also help explaining transition dynamics to others (see this clip). I think this way of explaining energy transition trade-offs, no-regret options and other intervention points in an interactive and appealing way to policy makers or domain experts is our best shot at reaching NEON’s ultimate goal: to accelerate the energy and mobility transition.
As I am responsible for a comprehensive system overview of the model and scenario output I will need to keep in close collaboration to all other workpackages. Especially my fellow PhD’s working on specific model components in Work Package 10 of course. But also the technological domain experts from work packages 1-6, and the social research in work packages 7 – 9. From my innovation sciences background I especially look forward to the possibilities of including psychological or social drivers for change into our models.