Feng (Fred) Wei, Ph.D.

Research Interests: 

Smart grid and renewable energy

• Deep learning and its application to smart grids

• Modelling and control of battery energy storage system 

• Health prognosis and degradation prediction in smart grids

• Power quality assessment and improvement

Power electronics control and application

• Wireless charging technology and V2G development

• Modern motor drive

Electric power for internet of things (IoT)

• Digital twin 

Bio:

Fred Wei received Bachelor of Engineering (B.Eng) with honor in School of Electrical Engineering from Wuhan University, Wuhan, China and completed his Doctor of Philosophy (Ph.D.) degree at  School of Electric and Electronic Engineering from Nanyang Technological University, Singapore. 

Prior to joining the School of EEE at Singapore Polytechnic, he was with Singapore Institute of Technology (SIT) from 2017 to 2020 as an instructor. From 2015 to 2017, he spent 3 years working as a research fellow in BEARS Research Center of University of California, Berkeley where he was a technical leader and project manager developing a real-time health prognosis and condition monitoring system of a stand-alone smart grid. From 2013 to 2014, he spent two years working in Rolls-Royce lab as a research associate where his research topic was the shaft vibration study of airplane start engine and marine propeller.  He serves as a session chair for ECCE ( Annual Energy Conversion Congress and Exposition) Aisa 2021. He is an associate editor of “Sustainability” Journal (IF: 3.889, ISSN 2071-1050) .

Fred's research efforts have been supported in part by over SGD $4M in research funding, with Fred serving as the principal investigator (PI) on over $3M research grants. He worked as a PI or collaborator in 6 projects where he has strong connection and collaboration with industry partners including Rolls-Royce, Singapore Power Group, Siemens and so on. His research interests include smart-grid and renewable energy, power electronics control and application, electric power for IoT and real-time hardware-in-loop simulation.