Prof. Dr. Chenyu Wu | Energy Technologies | Best Researcher Award

Prof. Dr. Chenyu Wu | Energy Technologies | Best Researcher Award

Hohai University, China

Prof. Dr. Chenyu Wu is a distinguished academic and researcher currently serving as a Professor in Jiangsu Province at the College of Energy and Electrical Engineering, Hohai University 🇨🇳. With deep expertise in power systems and electricity markets, he has authored over 20 high-impact SCI (Q1) papers and contributed to two team standards. Prof. Wu has led numerous key national and industrial projects, including those funded by the National Natural Science Foundation and the State Grid Corporation of China. His groundbreaking research has been implemented across various regions, including Jilin, Yunnan, and Myanmar. Recognized for both academic and applied excellence, he has received top-tier honors such as the First Prize of Jiangsu Province Science and Technology Award and the National Innovation and Entrepreneurship Outstanding Postdoctoral Fellow title 🏆.

Publication Profile

🎓Education Background:

Prof. Wu earned his Ph.D. in Electrical Engineering from Southeast University (2015–2019) 🎓, following a B.S. in Electrical Engineering from Hohai University (2011–2015) 📘. His academic training laid the foundation for his advanced contributions to smart grids and integrated energy systems.

💼Professional Experience:

Prof. Wu’s professional journey includes serving as a Senior Engineer at the State Grid (Suzhou) Urban Energy Research Institute (2019–2020) 🏙️. He then transitioned to academia, where he held roles as Associate Professor at Southeast University (2020–2025) and later as a Professor at Hohai University from March 2025 onward. His experience bridges industrial engineering practice and cutting-edge academic research.

🏅Awards and Honors:

Prof. Wu’s excellence has been widely recognized. Notable accolades include the First Prize in Science and Technology of Jiangsu Province (2022) 🥇, the Bronze Award in the China Postdoctoral Innovation and Entrepreneurship Competition (2022) 🥉, and the Outstanding Doctoral Dissertation Award by the China Simulation Society (2020) 📜. He is also among the elite few chosen (<1%) for the Jiangsu “333” talent project and the National Excellent Postdoctoral Fellow title 🌟.

🔬Research Focus:

His core research areas include the optimal operation of integrated energy systems, virtual power plants, active distribution networks, and electricity market bidding strategies ⚡. He integrates concepts from distributed optimization, differential game theory, and reverse engineering to advance clean, efficient energy systems aligned with smart grid development and market transformation.

✅Conclusion:

Prof. Dr. Chenyu Wu stands as a thought leader in the evolving fields of power system optimization and energy economics. His impactful publications, prestigious awards, and active academic involvement testify to his dedication to sustainable energy innovation and system-wide transformation 🌍📈.

📚Top Publications:

A Two-Stage Game Model for Combined Heat and Power Trading MarketIEEE Transactions on Power Systems, 2019 | Cited by: 240+

Energy Trading and Generalized Nash Equilibrium in Combined Heat and Power MarketIEEE Transactions on Power Systems, 2020 | Cited by: 200+

Coordinated Optimal Power Flow for Integrated Active Distribution Network and Virtual Power Plants Using Decentralized AlgorithmIEEE Transactions on Power Systems, 2021 | Cited by: 180+

Competitive Equilibrium Analysis for Renewables Integration in Dynamic Combined Heat and Power Trading MarketIEEE Transactions on Power Systems, 2023 | Cited by: 30+

Model-Free Economic Dispatch for Virtual Power Plants: An Adversarial Safe Reinforcement Learning ApproachIEEE Transactions on Power Systems, 2023 | Cited by: 25+

Combined Economic Dispatch Considering the Time-Delay of District Heating NetworkIEEE Transactions on Sustainable Energy, 2018 | Cited by: 150+

Bi-level Optimization Model for Integrated Energy System Considering the Thermal Comfort of Heat CustomersApplied Energy, 2018 | Cited by: 180+

Jian Sun | Smart Grid Control | Best Researcher Award

Assoc. Prof. Dr. Jian Sun | Smart Grid Control | Best Researcher Award

Associate Professor, Southwest University, China

Jian Sun is an Associate Professor in the School of Electronic and Information Engineering at Southwest University, Chongqing, China. With a strong academic and research background in automation and electrical engineering, his work focuses on control systems, reinforcement learning, and grid frequency regulation. Over the years, he has made significant contributions to the field through his publications and innovative approaches to tackling complex power grid challenges. 📚🔬

Publication Profile

ORCID

Education

Jian Sun earned his Ph.D. in Automation from Chongqing University in December 2014. He also completed a visiting Ph.D. program at the University of Wisconsin-Madison, USA, in 2014, specializing in Electrical and Computer Engineering. Prior to his doctoral studies, he obtained a Master’s degree in Automation and a Bachelor’s degree in the same field from Chongqing University. 🎓🌍

Experience

Jian Sun has extensive academic and research experience, currently serving as an Associate Professor at Southwest University. His expertise spans areas like frequency regulation in power systems, energy storage systems, and adaptive control techniques. He has published numerous papers in prestigious journals and has contributed to several interdisciplinary research projects. His work often combines advanced reinforcement learning techniques with cyber-physical systems. 💼🔧

Awards and Honors

Throughout his career, Jian Sun has received recognition for his outstanding research and contributions to the field. His work has been widely cited and appreciated by both academic and industry professionals. He continues to push the boundaries of research in smart grids, energy management, and reinforcement learning. 🏆📈

Research Focus

Jian Sun’s research focuses on developing adaptive and resilient control strategies for smart grids, particularly in the context of frequency regulation. His work includes the integration of Vehicle-to-Grid (V2G) technologies, reinforcement learning for DoS attack resilience, and advanced control systems for energy-efficient power grids. He aims to improve the stability and security of power systems in the face of cyber threats and dynamic load conditions. ⚡🧠

Conclusion

Jian Sun’s academic journey and research have contributed to advancements in smart grid technology, power system regulation, and control theory. His continued dedication to addressing critical challenges in energy systems positions him as a leading figure in his field. His research aims to make power systems smarter, more efficient, and resilient to emerging threats. 🌐🔋

Publications 

Load Forecasting for Commercial Buildings Using BiLSTM–Transformer Network and Cyber–Physical Cognitive Control Systems
Published Year: 2024
Journal: Symmetry
Cited by: Crossref

An Adaptive V2G Capacity-Based Frequency Regulation Scheme With Integral Reinforcement Learning Against DoS Attacks
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Cooperative Grid Frequency Control Under Asymmetric V2G Capacity via Switched Integral Reinforcement Learning
Published Year: 2024
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Resilient Frequency Regulation for DoS Attack Intensity Adaptation via Predictive Reinforcement V2G Control Learning
Published Year: 2024
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

Safe Online Integral Reinforcement Learning for Control Systems via Controller Decomposition
Published Year: 2023
Journal: Arabian Journal for Science and Engineering
Cited by: Crossref

A DoS Attack-Resilient Grid Frequency Regulation Scheme via Adaptive V2G Capacity-Based Integral Sliding Mode Control
Published Year: 2023
Journal: IEEE Transactions on Smart Grid
Cited by: Crossref

A DoS Attack Intensity-Aware Adaptive Critic Design of Frequency Regulation for EV-Integrated Power Grids
Published Year: 2023
Journal: International Journal of Electrical Power & Energy Systems
Cited by: Crossref

Structural Scheduling of Transient Control Under Energy Storage Systems by Sparse-Promoting Reinforcement Learning
Published Year: 2022
Journal: IEEE Transactions on Industrial Informatics
Cited by: Crossref

A Sparse Neural Network-Based Control Structure Optimization Game under DoS Attacks for DES Frequency Regulation of Power Grid
Published Year: 2019
Journal: Applied Sciences
Cited by: Crossref

A Stable Distributed Neural Controller for Physically Coupled Networked Discrete-Time System via Online Reinforcement Learning
Published Year: 2018
Journal: Complexity
Cited by: Crossref

Frequency Regulation of Power Systems with Self-Triggered Control under the Consideration of Communication Costs
Published Year: 2017
Journal: Applied Sciences
Cited by: Crossref