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Michael Chen

Research Postgraduate – Electrical Power Node

Research Postgraduate – Electrical Power Node in the Department of Engineering


Wenzhi Chen received his Bachelor's (Telecommunications Engineering with Management, joint program) and Master's degree (Computer Technology) from the Beijing University of Posts and Telecommunications (China) in 2017 and 2020. In 2017, he received a first-class Bachelor's degree from Queen Mary, University of London (U.K.). In 2019, he was a short-term visiting student at the Department of Engineering at Durham University (U.K.). Since 2020, he has been with the University of Durham (U.K.) as a recipient of the ERDF program ‘Intensive Industrial Innovation Programme Doctoral’ Scholarship. His recent research interest includes the Internet of Things, Machine Learning for Smart Street Lighting System. He is working with Otaski company to develop intelligent streets lights. 

Research Project

The smart grid has the potential to improve the safety, reliability, and efficiency of the power grid, where information technology plays a crucial role in attaining the key objectives of smart grids. High speed and bidirectional communication infrastructure, advanced data processing, distributed computing technologies are indispensable for power system state estimation, control, optimization, and restoration.

Smart Street Lighting, which is an important part of both smart grid and smart city in recent time, has become increasingly essential in terms of improving energy efficiency and reducing carbon footprint. Two key areas in actualizing smart street lighting are the electrical connection of streetlights and data communication between streetlights.
Data-driven cyber-physical system control for Realising Efficient Smart Street lighting (DRESS) project aims to address these three challenging issues by building a strong and sustainable academic-industrial collaboration between Durham University and Otaski Energy Solutions Ltd. The following three key scientific objectives will be achieved in this project:
a) Develop whole system cyber-physical models integrating cyber systems components (such as communication nodes and networks) into the physical system control loop, in order to improve efficient control of smart street lighting system;
b) Develop data-driven, robust, and lightweight congestion control protocols for their implementation in any wired or wireless communication networks;
c) Test and validate the developed methodologies in a laboratory environment for future roll-out of mature products/services.