Dr Weiqi Hua PhD, MIEEE,MIET

Dr Weiqi Hua

Department of Electronic, Electrical and Systems Engineering
Assistant Professor

Contact details

Email
w.hua@bham.ac.uk
View my research portal
Address
Department of Electronic Electrical and Systems Engineering
University of Birmingham
Edgbaston
Birmingham
B15 2TT
UK

Dr Weiqi Hua is an Assistant Professor with the Department of Electronic, Electrical and Systems Engineering at the University of Birmingham (U.K.) since 2023. He took postdoctoral positions at the University of Oxford (U.K.) and Cardiff University (U.K.). He received his Ph.D. degree from the University of Durham (U.K.) in 2020, co-funded by Hyundai Motor Company and Durham Research Doctoral Scholarship.

He was the visiting researcher to the Hellenic Telecommunications Organisation (OTE), Greece in 2019, and visiting researcher to the Chinese Academy of Sciences, China in 2018 and 2019. His research interests include:
i) energy system modelling and optimisation,
ii) renewable energy integration,
iii) digitalisation, digital twin, and machine learning for energy system analytics,
iv) energy policy and economics, and
v) Local energy markets and peer-to-peer energy trading.

Dr Hua is an Editorial Board Member of Applied Energy, and Editorial Board Member of Oxford Open Energy. He served as the Lead Guest Editor for the Special Issue on the topic of Blockchain based local energy market in IET Smart Grid, Guest Editor for the Special Issue on the topic of digitalisation of energy systems in Oxford Open Energy, and Guest Editor for the Special Issue on the topic of energy-water nexus in Water.

He was a technical program committee (TPC) member for IEEE SmartGridComm 2020, and TPC member for IEEE International Smart Cities Conference 2021. He has been appointed as the sessional chair for CEN2023 Applied Energy Symposium, sessional chair for IEEE SmartGridComm 2018, and sessional chair for IEEE International Smart Cities Conference 2017. He has edited a book with CRC press: ‘Blockchain and Artificial Intelligence Technologies for Smart Energy Systems’, and published a chapter for IntechOpen book: ‘Microgrids and Local Energy Systems’.

Dr Hua has undertaken research projects collaborating with academia and industries, including:
i) EPSRC Analytical Middleware for Informed Distribution Networks (AMIDiNe),
ii) BEIS Heat Pump Ready Programme,
iii) EPSRC Maximising flexibility through multi-scale integration of energy system (MISSION),
iv) Integrated heating and cooling networks with heat-sharing-enabled smart prosumers,
v) Virtual Power Plant for Interoperable and Smart isLANDS (VPP4ISLANDS),
vi) EU ERDF Solid Wall Insulation innovation (SWIi), and
vii) Horizon 2020 Testing and Evaluating Sophisticated information and communication Technologies for enaBling scalablE smart griD Deployment (TESTBED).

Qualifications

  • PhD in Engineering, University of Durham, 2020.
  • MSc in New and Renewable Energy, University of Durham, 2017

Biography

Dr Weiqi Hua is an Assistant Professor with the Department of Electronic, Electrical and Systems Engineering at the University of Birmingham (U.K.) since 2023. He took postdoctoral positions at the University of Oxford (U.K.) and Cardiff University (U.K.). He received his Ph.D. degree from the University of Durham (U.K.) in 2020, co-funded by Hyundai Motor Company and Durham Research Doctoral Scholarship, with the thesis title of ‘Smart Grid Enabling Low Carbon Future Power Systems Towards Prosumers Era’.

He was the visiting researcher to the Hellenic Telecommunications Organisation (OTE), Greece in 2019, and visiting researcher to the Chinese Academy of Sciences, China in 2018 and 2019. His research interests include:
i) energy system modelling and optimisation,
ii) renewable energy integration,
iii) digitalisation, digital twin, and machine learning for energy system analytics,
iv) energy policy and economics, and
v) Local energy markets and peer-to-peer energy trading.

Dr Hua is an Editorial Board Member of Applied Energy, and Editorial Board Member of Oxford Open Energy. He served as the Lead Guest Editor for the Special Issue on the topic of Blockchain based local energy market in IET Smart Grid, Guest Editor for the Special Issue on the topic of digitalisation of energy systems in Oxford Open Energy, and Guest Editor for the Special Issue on the topic of energy-water nexus in Water.

He was a technical program committee (TPC) member for IEEE SmartGridComm 2020, and TPC member for IEEE International Smart Cities Conference 2021. He has been appointed as the sessional chair for CEN2023 Applied Energy Symposium, sessional chair for IEEE SmartGridComm 2018, and sessional chair for IEEE International Smart Cities Conference 2017. He has edited a book with CRC press: ‘Blockchain and Artificial Intelligence Technologies for Smart Energy Systems’, and published a chapter for IntechOpen book: ‘Microgrids and Local Energy Systems’.

Dr Hua has undertaken research projects collaborating with academia and industries, including:
i) EPSRC Analytical Middleware for Informed Distribution Networks (AMIDiNe),
ii) BEIS Heat Pump Ready Programme,
iii) EPSRC Maximising flexibility through multi-scale integration of energy system (MISSION),
iv) Integrated heating and cooling networks with heat-sharing-enabled smart prosumers,
v) Virtual Power Plant for Interoperable and Smart isLANDS (VPP4ISLANDS),
vi) EU ERDF Solid Wall Insulation innovation (SWIi), and
vii) Horizon 2020 Testing and Evaluating Sophisticated information and communication Technologies for enaBling scalablE smart griD Deployment (TESTBED).

Postgraduate supervision

Dr Hua is interested in supervising doctoral research students in the following areas:

  • Energy system modelling and optimisation.
  • Renewable energy integration.
  • Digitalisation, digital twin, and machine learning for energy system analytics.
  • Energy policy and economics.
  • Local energy markets and peer-to-peer energy trading.

There is a UK funded PhD Scholarship in the field of digitalisation of energy systems

Dr Hua is also interested in supporting PhD applications with other funding sources, e.g., industries, university, or self-funded.

For general doctoral research enquiries, please email: dr@contacts.bham.ac.uk  or call +44 (0)121 414 5005

Research

  • Energy system modelling and optimisation.
  • Renewable energy integration.
  • Digitalisation, digital twin, and machine learning for energy system analytics.
  • Energy policy and economics.
  • Local energy markets and peer-to-peer energy trading.

Other activities

  • Editorial Board Member of Applied Energy.
  • Editorial Board Member of Oxford Open Energy.
  • Guest Editor for Special Issue "Digitalisation and Digital Twins for Low Carbon Energy Systems" in  Oxford Open Energy.
  • Guest Editor (Lead) for Special Issue "Blockchain Technologies Empowering Peer-to-Peer Trading in Multi-Energy Systems: From Advanced Technologies Towards Applications" in IET Smart Grid.
  • Guest Editor for Special Issue "Low-Carbon, Zero-Carbon and Negative-Carbon Wastewater Treatment Technology and Operation Strategies" in Water.
  • Technical Program Committee (TPC) Member of IEEE SmartGridComm 2020.
  • TPC Member of IEEE International Smart Cities Conference 2021, Track 1: Smart Transportation.
  • Chair on the Session of Intelligent Energy Uses and Energy Efficiency, CEN2023 Applied Energy Symposium, Ningbo, China.
  • Chair on the Session of Operation and Integration of Electric Vehicles in Smart Grid, IEEE SmartGridComm 2018, Aalborg, Denmark.
  • Chair on the Session of Smart Energy Systems, IEEE International Smart Cities Conference 2017, Wuxi, China.
  • Reviewer for Journals: IEEE Transactions on Smart Grid, IEEE Transactions on Power Systems, IEEE Transactions on Industrial Informatics, IEEE Transactions on Sustainable Energy, IEEE Transactions on Energy Markets, Policy and Regulation, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Access, Energy, Applied Energy, Renewable and Sustainable Energy Reviews, IET Renewable Power Generation, IET Generation, Transmission & Distribution, Applied Sciences, Sustainability, International Journal of Energy Research, Sustainable Energy, Grids and Networks, Energy and AI, Advances in Applied Energy, CSEE Journal of Power and Energy Systems, Journal of Cleaner Production, Mathematics, Sustainable Energy Technologies and Assessments, Frontiers in Energy, Sustainability, World Electric Vehicle Journal, Electronics, Sensors, EURASIP Journal on Wireless Communications and Networking, Journal of Risk and Financial Management, Engineering Reports, Complexity.

Speaking Engagements

  • "Digital Analytics for Informed Distribution Networks", MSc in Energy Systems, University of Oxford, UK, 2023.
  • "Virtual Power Plants: Trends and Opportunities", Alibaba Group, China, 2023.
  • "Digitalisation and Digital Twin for Energy Systems", IEE, Chinese Academy of Science, China 2023.
  • "Pathway to the Net Zero GB Energy System", School of Energy and Power Engineering, Beihang University, China, 2022.
  • "Local Energy Market and Peer-to-Peer Energy Trading", School of Energy and Power Engineering, Chongqing University, China, 2022.
  • "Renewable Energy, Blockchain, Artificial Intelligence enabling Future Energy Systems'', Eton College, Science Society, 2022.
  • "Peer-to-Peer Energy Trading: Barriers and Opportunities", Dutch Seminar on Digital Energy, Centrum Wiskunde & Informatica (CWI) Amsterdam, Netherlands, 2022.
  • "Peer-to-Peer Energy Trading", MSc in Energy Systems, the University of Oxford, 2022.
  • "A Blockchain Based Peer-to-Peer Trading Scheme Coupling Energy and Carbon Markets",  Department of Engineering Research Day, University of Durham, 2019.
  • "Scientific Innovation and Regulatory Support in Achieving Low Carbon Energy Systems", UK Summer School, China University of Geosciences, 2019.
  • ''Energy Market Transitions Towards Prosumers Era'', Institute of Electrical Engineering, Chinese academy of sciences, 2018
  • "Carbon Emissions Reduction Technologies for Future Energy Systems", Department of Engineering Research Day, University of Durham, 2017.

Publications

Journal Article

  • Hua, W., Stephen, B., & Wallom, D. C. (2023). Digital twin based reinforcement learning for extracting network structures and load patterns in planning and operation of distribution systems. Applied Energy, 342, 121128.
  • Hua, W., Chen, Y., Qadrdan, M., Jiang, J., Sun, H., & Wu, J. (2022). Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review. Renewable and Sustainable Energy Reviews, 161, 112308.
  • Hua, W., Zhou, Y., Qadrdan, M., Wu, J., & Jenkins, N. (2022). Blockchain enabled decentralized local electricity markets with flexibility from heating sources. IEEE Transactions on Smart Grid.
  • Hua, W., Jiang, J., Sun, H., Tonello, A. M., Qadrdan, M., & Wu, J. (2022). Data-driven prosumer-centric energy scheduling using convolutional neural networks. Applied Energy, 308, 118361.
  • Hua, W., Jiang, J., Sun, H., Teng, F., & Strbac, G. (2022). Consumer-centric decarbonization framework using Stackelberg game and Blockchain. Applied Energy, 309, 118384.
  • Hua, W., Xiao, H., Pei, W., Chiu, W. Y., Jiang, J., Sun, H., & Matthews, P. (2022). Transactive energy and flexibility provision in multi-microgrids using Stackelberg game. CSEE Journal of Power and Energy Systems.
  • Zhou, Y., Manea, A. N., Hua, W., Wu, J., Zhou, W., Yu, J., & Rahman, S. (2022). Application of distributed ledger technology in distribution networks. Proceedings of the IEEE.
  • Qiu, D., Wang, Y., Hua, W., & Strbac, G. (2023). Reinforcement learning for electric vehicle applications in power systems: A critical review. Renewable and Sustainable Energy Reviews, 173, 113052.
  • Jing, R., Hua, W., Lin, J., Lin, J., Zhao, Y., Zhou, Y., & Wu, J. (2022). Cost-efficient decarbonization of local energy systems by whole-system based design optimization. Applied Energy, 326, 119921.
  • Xiao, H., Pei, W., Wu, L., Ma, L., Ma, T., & Hua, W. (2023). A novel deep learning based probabilistic power flow method for Multi-Microgrids distribution system with incomplete network information. Applied Energy, 335, 120716.
  • Wei, H., Zhang, Y., Wang, Y., Hua, W., Jing, R., & Zhou, Y. (2022). Planning integrated energy systems coupling V2G as a flexible storage. Energy, 239, 122215.
  • Zhang, X., Hua, W., Liu, Y., Duan, J., Tang, Z., & Liu, J. (2022). Reinforcement learning for active distribution network planning based on Monte Carlo tree search. International Journal of Electrical Power & Energy Systems, 138, 107885.
  • Hua, W., Jiang, J., Sun, H., & Wu, J. (2020). A blockchain based peer-to-peer trading framework integrating energy and carbon markets. Applied Energy, 279, 115539.
  • Hua, W., Li, D., Sun, H., & Matthews, P. (2020). Stackelberg game‐theoretic model for low carbon energy market scheduling. IET Smart Grid, 3(1), 31-41.
  • Hua, W., Li, D., Sun, H., Matthews, P., & Meng, F. (2018). Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets. International journal of smart grid and clean energy., 7(4), 231-239.
  • Li, D., Hua, W., Sun, H., & Chiu, W. Y. (2017). Multiobjective optimization for carbon market scheduling based on behavior learning. Energy procedia, 142, 2089-2094.

Edited Book

Sun H., Hua W. & You M., "Blockchain and Artificial Intelligence Technologies for Smart Energy Systems, " Taylor & Francis Group, CRC Press.

Chapter in Book

Seward, W., Hua, W., & Qadrdan, M. (2021). Electricity Storage in Local Energy Systems. Microgrids and Local Energy Systems, 1, 127.

Edited Journal

Hua, W., Luo, F., Du, L., Chen, S., Kim, T., Morstyn, T., ... & Zhou, Y. (2022). Blockchain technologies empowering peer-to-peer trading in multi-energy systems: From advanced technologies towards applications. IET Smart Grid, 5(4), 219-222.

Conference Paper

  • Hua, W., Jing, R., Zhou, Y., Zhang, X., Jiang, J., & Sun, H. (2021). Blockchain Smart Contracts for Grid Connection Management in Achieving Net Zero Energy Systems.
  • Hua, W., & Sun, H. (2019, September). A blockchain-based peer-to-peer trading scheme coupling energy and carbon markets. In 2019 international conference on smart energy systems and technologies (SEST) (pp. 1-6). IEEE.
  • Hua, W., You, M., & Sun, H. (2019, August). Real-time price elasticity reinforcement learning for low carbon energy hub scheduling based on conditional random field. In 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops) (pp. 204-209). IEEE.
  • Hua, W., Sun, H., Xiao, H., & Pei, W. (2018, October). Stackelberg game-theoretic strategies for virtual power plant and associated market scheduling under smart grid communication environment. In 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm) (pp. 1-6). IEEE.
  • Hua, W., Li, D., Sun, H., & Matthews, P. (2017, September). Unit commitment in achieving low carbon smart grid environment with virtual power plant. In 2017 International Smart Cities Conference (ISC2) (pp. 1-6). IEEE.
  • You, M., Hua, W., Shahbazi, M., & Sun, H. (2018, August). Energy hub scheduling method with voltage stability considerations. In 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops) (pp. 196-200). IEEE.

View all publications in research portal