Anca Daniela Hansen

Anca Daniela Hansen is an Associate Professor in the Department of Wind and Energy Systems at the Technical University of Denmark (DTU), specializing in renewable energy systems with contributions to UN Sustainable Development Goals for clean energy. Her work bridges academic research and industry applications in wind power integration and grid stability.

Her research spans Wind Energy, Power Systems Engineering, Hybrid Power Systems, and Grid Integration of Renewables, focusing on control strategies for wind turbines, voltage stability, and market participation of hybrid power plants. Key interests include ancillary services provision, reactive power management, and multi-technology system integration for high renewable penetration scenarios.

Recent publications reveal strong trends in hybrid power plant optimization, real-time control systems, and probabilistic grid stability assessment under wind variability. Her work addresses critical gaps in market mechanisms for reserve services, energy management system design, and multi-vendor compatibility in utility-scale renewable installations.

Scientific awards include:

• World's Top 2% Scientist (2024)
• World's Top 2% Scientist (2022)

She supervises PhD students on projects including 'Robust Control and Stability of Multi-vendor & Multi-technology Hybrid Power Plants' (Celna, A.), 'Optimization and Control of Wind, Solar and Storage in Hybrid Power Plants' (Zhu, R.), and 'Wind Power Plant Support for Weather Dependent Active Distribution Networks' (Baviskar, A. U.). Her research is funded through IEA Wind Task 41 (Distributed Wind), industry collaborations, and DTU internal grants focusing on robust adaptive control systems.

As a core member of DTU's Wind Energy Systems Division, she leads international collaborations with 22 research projects spanning grid integration challenges, participates in conference organization (Wind Energy Science Conference 2019), and contributes to open datasets like the DTU 7k Bus Active Distribution Network for advancing renewable energy modeling.