Imperial College London

DrFeiTeng

Faculty of EngineeringDepartment of Electrical and Electronic Engineering

Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 6178f.teng Website CV

 
 
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Location

 

1113Electrical EngineeringSouth Kensington Campus

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Summary

 

Summary

I am a lecturer in the Department of Electrical and Electronic Engineering, Imperial College London. I am also serving as deputy director of Imperial - Tsinghua Joint Research Centre for Intelligent Power and Energy Systems and holding a visiting position at MINES ParisTech, France.

I graduated with a BEng from Beihang University, China in 2009 and obtained my PhD from Imperial College London in 2015. I worked as a Research Associate at Imperial from 2015 to 2017 and as an Assistant Professor in Smart Grids at MINES ParisTech, France in 2017.

My present research mainly focuses on the cyber-physical modelling, convex optimization and data analytics for the future low carbon energy systems. I have authored more than 30 scientific publications in leading power system journals and conferences. My research has been funded by EPSRC, ESRC, Innovate UK and National Grid ESO.

I received the best paper award in POWER-GEN Europe in 2013 and Chinese Government Award for Outstanding Self-financed Students Abroad in 2015. I am a committee member of CES and CSEE UK Branch, and member of IEA Wind Task 25 WG and EERA JP ESI. I was a guest editor for special issue "Challenges in Future Grid-Interactive Power Converters: Control Strategies, Optimal Operation, and Corrective Actions" in IET Renewable Power Generation and for special issue "Reducing Energy Demand in the Industrial and Manufacturing Sectors" in Energies.

Student Supervision


I am currently supervising four fully-funded PhD students. PhD student positions will be available from Sep 2019 in the areas of Power System Optimisation under Uncertainty, Data-driven System Forecasting and Cyber-physical Modelling of Future Power Systems. To apply for the PhD position, applicants should have a Distinction/First class grade Master’s degree in electrical engineering or a related field, and good communication and technical writing skills. Strong knowledge in optimization, programming and mathematics are desired.

Informal enquiries and requests for additional information can be made to Dr Fei Teng by email at f.teng@imperial.ac.uk.

Applications will be assessed as received and all applicants should follow the standard College application procedure (indicating Dr Fei Teng as supervisor) (http://www3.imperial.ac.uk/pgprospectus/howtoapply).

Research Funding

  1. "False data injection attack against machine-learning based energy forecasting algorithms", European Partners Fund, 2019-2021, PI
  2. “Short-term System Inertia Forecast - A Data-driven Approach”, National Grid ESO, 2019-2020, PI
  3. “Socio-Techno-Economic Pathways for sustainable Urban energy DeveloPment (STEP-UP)”, ESRC-NWO-NSFC, 2019-2022, Co-I
  4. “Holistic Cyber-physical System Modelling for Cyber-security Analysis in Electricity Systems”, EPSRC CDT, 2018-2021, PI
  5. “Agent-based simulation approach to the provision of ancillary service by demand response and distributed storage and generation assets in the future low carbon system”, ESRC DTP, 2018-2021, PI
  6. “V2Street”, Driving Innovation, TSB, 2018-2019, Co-I
  7. “Smart demand”, InterCarnot M.I.N.E.S – TSN, 2018, Co-I

Publications

Journals

Camal S, Teng F, Michiorri A, et al., 2019, Scenario generation of aggregated Wind, Photovoltaics and small Hydro production for power systems applications, Applied Energy, ISSN:0306-2619, Pages:1396-1406

Sun M, Teng F, Zhang X, et al., Data-driven representative day selection for investment decisions: a cost-oriented approach, Ieee Transactions on Power Systems, ISSN:0885-8950

Zhang X, Strbac G, Shah N, et al., 2019, Whole-System Assessment of the Benefits of Integrated Electricity and Heat System, Ieee Transactions on Smart Grid, Vol:10, ISSN:1949-3053, Pages:1132-1145

Badesa L, Teng F, Strbac G, 2019, Simultaneous Scheduling of Multiple Frequency Services in Stochastic Unit Commitment, Ieee Transactions on Power Systems, ISSN:0885-8950, Pages:1-1

Sun M, Wang Y, Teng F, et al., 2019, Clustering-Based Residential Baseline Estimation: A Probabilistic Perspective, Ieee Transactions on Smart Grid, ISSN:1949-3053, Pages:1-1

More Publications