π Education
Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016β2020) π, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014β2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010β2014) βοΈ. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.
πΌ Experience
Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation π. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023β2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 π¬. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.
π Awards and Honors
Dr. Qiuβs research excellence has been acknowledged through various accolades π
. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community π.
π¬ Research Focus
Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications π€. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change π. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.
π Conclusion
Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering π¬. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community π. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions β‘.
π Publications
A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hubΒ β Applied Energy (Under review, 2025) π Link
Enhanced Meta Reinforcement Learning for Resilient Transient StabilizationΒ β IEEE Transactions on Power Systems (Under review, 2025) π Link
Machine learning-based economic model predictive control for energy hubs with variable energy efficienciesΒ β Energy (First round revision, 2024) π Link
A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy SystemsΒ β Proceedings of the IEEE (Under review, 2025) π Link
Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region AggregationΒ β IEEE Transactions on Smart Grid (First round revision, 2024) π Link
A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution NetworksΒ β IEEE Transactions on Power Systems (Under review, 2024) π Link
Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load ManagementΒ β IEEE Internet of Things Journal (Under review, 2024) π Link
Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management StrategyΒ β Energy (Under review, 2024) π Link
Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement LearningΒ β IEEE Transactions on Network Science and Engineering (Under review, 2024) π Link