Frederic Sulzmann

Background

About Frederic Sulzmann

I am passionate about developing data-driven solutions that accelerate decarbonization and energy system optimization. With experience across academia, and consulting, my work focuses on energy flexibility valuation, storage optimization, and AI-based spot price forecasting. By combining machine learning techniques with technical energy system modeling, I aim to improve the understanding and monetization of flexibility and storage options in evolving energy markets. I develop Python-based models that integrate market dynamics, technical constraints, and operational strategies to support data-driven decision-making. I believe the future of the energy transition depends on leveraging digitalization, automation, and advanced analytics to make sustainability strategies more actionable and impactful. My goal is to work at the intersection of sustainability, energy systems, and digital innovation, contributing to solutions that enable a smarter, more flexible, and net-zero energy future.