Weiqi Hua

Research output

Research output per year 2014 2022 2023 2024

• 23 Article
• 9 Conference contribution
• 1 Book
• 1 Chapter
• 2 More
  • 1 Editorial
  • 1 Doctoral Thesis

Research output per year

Research output per year

Search results

• 2024

  Assessing long-term future climate change impacts on extreme low wind events for offshore wind turbines in the UK exclusive economic zone

  Abdelaziz, S., Sparrow, S., Hua, W. & Wallom, D., 15 Jan 2024, In: Applied Energy. 354, 18 p., 122218.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Exclusive Economic Zone 100%
  • Offshore wind turbines 92%
  • wind turbine 81%
  • Climate change 81%
  • climate change impact 76%
  11 Downloads (Pure)

• Blockchain-enabled renewable energy certificate trading: A secure and privacy-preserving approach

  Liu, W-J., Chiu, W-Y. & Hua, W., 1 Mar 2024, In: Energy. 290, 13 p., 130110.

  Research output: Contribution to journal › Article › peer-review

  • alternative energy 100%
  • renewable energy source 17%
  • consumer information 13%
  • habitat destruction 10%
  • fee 9%

• Windfall profit-aware stochastic scheduling strategy for industrial virtual power plant with integrated risk-seeking/averse preferences

  Xiao, D., Lin, Z., Chen, H., Hua, W. & Yan, J., 1 Mar 2024, In: Applied Energy. 357, 13 p., 122460.

  Research output: Contribution to journal › Article › peer-review

  • windfall 100%
  • profit 62%
  • Profitability 54%
  • power plant 53%
  • Power plants 50%
• 2023

  A novel deep learning based probabilistic power flow method for Multi-Microgrids distribution system with incomplete network information

  Xiao, H., Pei, W., Wu, L., Ma, L., Ma, T. & Hua, W., 1 Apr 2023, In: Applied Energy. 335, 21 p., 120716.

  Research output: Contribution to journal › Article › peer-review

  • information network 100%
  • distribution system 80%
  • Microgrids 73%
  • Electric power distribution 65%
  • Deep learning 64%

• An Overview of Artificial Intelligence for Electric Vehicle Energy Systems Integration

  Hua, W., Mullen, D., Wahid, A., Sitabkhan, K. & Mason, K., 25 Jan 2023, Artificial Intelligence: ECAI 2023 International Workshops . Springer, Vol. 2. p. 178-185 (Communications in Computer and Information Science; vol. 1948).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Electric vehicles 100%
  • Artificial intelligence 96%
  • Supply chains 27%
  • Electricity 20%

• Blockchain and Artificial Intelligence Technologies for Smart Energy Systems

  Sun, H., Hua, W. & You, M., 4 Oct 2023, 1st ed. Chapman and Hall/CRC. 386 p.

  Research output: Book/Report › Book

  • Blockchain 100%
  • Artificial intelligence 74%
  • Climate change 31%
  • Testbeds 27%
  • Industry 12%

• Blockchain Enabled Decentralized Local Electricity Markets With Flexibility From Heating Sources

  Hua, W., Zhou, Y., Qadrdan, M., Wu, J. & Jenkins, N., Mar 2023, In: IEEE Transactions on Smart Grid. 14, 2, p. 1607-1620 14 p.

  Research output: Contribution to journal › Article › peer-review

  • Blockchain 100%
  • Power markets 88%
  • Electricity 62%
  • Heating 61%
  • Energy balance 22%

• Digital twin based reinforcement learning for extracting network structures and load patterns in planning and operation of distribution systems

  Hua, W., Stephen, B. & C.H. Wallom, D., 15 Jul 2023, In: Applied Energy. 342, 14 p., 121128.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Digital twin 100%
  • distribution system 76%
  • Reinforcement learning 68%
  • reinforcement 67%
  • Convolutional neural networks 62%
  1 Downloads (Pure)

• Extreme Wind Gust Impact on UK Offshore Wind Turbines: Long-Term Return Level Estimation

  Abdelaziz, S., Sparrow, S. N., Hua, W. & Wallom, D., 25 Sept 2023, 2023 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 5 p. 10252611. (IEEE Power & Energy Society General Meeting).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • gust 100%
  • wind turbine 88%
  • wind farm 48%
  • Exclusive Economic Zone 18%
  • return period 14%

• Future Climate Change Impact On Wind Gust For Offshore Wind Turbines Cut-Out Within The UK Exclusive Economic Zone

  Abdelaziz, S., Sparrow, S. N., Hua, W. & Wallom, D., 11 Jul 2023, 2023 IEEE Green Technologies Conference (GreenTech). IEEE, p. 10-14 5 p. 10173830. (IEEE Green Technologies Conference).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Exclusive Economic Zone 100%
  • gust 92%
  • wind turbine 81%
  • climate change impact 76%
  • climate 20%

• Reinforcement learning for electric vehicle applications in power systems: A critical review

  Qiu, D., Wang, Y., Hua, W. & Strbac, G., Mar 2023, In: Renewable and Sustainable Energy Reviews. 173, 22 p., 113052.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Vehicle-to-grid 100%
  • Reinforcement learning 93%
  • Electric vehicles 84%
  • Learning algorithms 30%
  • Renewable energy resources 29%
  28 Downloads (Pure)

• Transactive energy and flexibility provision in multi-microgrids using Stackelberg game

  Hua, W., Xiao, H., Pei, W., Chiu, W-Y., Jiang, J., Sun, H. & Matthews, P., Mar 2023, In: CSEE Journal of Power and Energy Systems. 9, 2, p. 505-515 11 p.

  Research output: Contribution to journal › Article › peer-review

  • distribution system 100%
  • energy market 80%
  • energy 58%
  • energy balance 57%
  • demand 39%
• 2022

  Application of Distributed Ledger Technology in Distribution Networks

  Zhou, Y., Manea, A., Hua, W., Wu, J., Zhou, W., Yu, J. & Rahman, S., Dec 2022, In: Proceedings of the IEEE. 110, 12, p. 1963-1975 13 p.

  Research output: Contribution to journal › Article › peer-review

  • Electric power distribution 100%
  • Planning 46%
  • Distributed power generation 37%
  • Information management 34%
  • Electric vehicles 33%

• Applications of blockchain and artificial intelligence technologies for enabling prosumers in smart grids: A review

  Hua, W., Chen, Y., Qadrdan, M., Jiang, J., Sun, H. & Wu, J., Jun 2022, In: Renewable and Sustainable Energy Reviews. 161, 13 p., 112308.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Blockchain 100%
  • Smart power grids 82%
  • Artificial intelligence 74%
  • Renewable energy resources 34%
  • Flexible structures 25%
  36 Downloads (Pure)

• Blockchain technologies empowering peer‐to‐peer trading in multi‐energy systems: From advanced technologies towards applications

  Hua, W., Luo, F., Du, L., Chen, S., Kim, T., Morstyn, T., Robu, V. & Zhou, Y., Aug 2022, In: IET Smart Grid. 5, 4, p. 219-222 4 p.

  Research output: Contribution to journal › Editorial › peer-review

  Open Access

  File
  14 Downloads (Pure)

• Consumer-centric decarbonization framework using Stackelberg game and Blockchain

  Hua, W., Jiang, J., Sun, H., Teng, F. & Strbac, G., 1 Mar 2022, In: Applied Energy. 309, 14 p., 118384.

  Research output: Contribution to journal › Article › peer-review

  • Decarbonization 100%
  • Blockchain 81%
  • carbon emission 70%
  • Carbon 53%
  • policy 42%

• Cost-efficient decarbonization of local energy systems by whole-system based design optimization

  Jing, R., Hua, W., Lin, J., Lin, J., Zhao, Y., Zhou, Y. & Wu, J., 15 Nov 2022, In: Applied Energy. 326, 14 p., 119921.

  Research output: Contribution to journal › Article › peer-review

  Open Access

  File

  • Decarbonization 100%
  • cost 36%
  • energy 34%
  • Costs 26%
  • building technology 11%
  17 Downloads (Pure)

• Data-driven prosumer-centric energy scheduling using convolutional neural networks

  Hua, W., Jiang, J., Sun, H., Tonello, A. M., Qadrdan, M. & Wu, J., 15 Feb 2022, In: Applied Energy. 308, 14 p., 118361.

  Research output: Contribution to journal › Article › peer-review

  • Convolutional neural networks 100%
  • price dynamics 97%
  • Scheduling 75%
  • elasticity 54%
  • energy 53%

• Planning integrated energy systems coupling V2G as a flexible storage

  Wei, H., Zhang, Y., Wang, Y., Hua, W., Jing, R. & Zhou, Y., 15 Jan 2022, In: Energy. 239, 16 p., 122215.

  Research output: Contribution to journal › Article › peer-review

  • electric vehicle 100%
  • planning 82%
  • energy 65%
  • tariff 24%
  • planning system 22%

• Reinforcement learning for active distribution network planning based on Monte Carlo tree search

  Zhang, X., Hua, W., Liu, Y., Duan, J., Tang, Z. & Liu, J., Jun 2022, In: International Journal of Electrical Power and Energy Systems. 138, 10 p., 107885.

  Research output: Contribution to journal › Article › peer-review

  • reinforcement 100%
  • learning 83%
  • planning 63%
  • distribution 36%
  • bus 18%
• 2021

  Blockchain smart contracts for grid connection management in achieving net zero energy systems

  Hua, W., Jing, R., Zhou, Y., Zhang, X., Jiang, J. & Sun, H., 2 Dec 2021, Sustainable Energy Solutions for a Post-COVID Recovery towards a Better Future: Part I. Yan, J. (ed.). Scanditale AB, 4 p. 210. (Energy Proceedings; vol. 18).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  File

  • contract 100%
  • renewable energy source 79%
  • carbon 58%
  • energy 50%
  • fee 40%
  7 Downloads (Pure)

• Electricity Storage in Local Energy Systems

  Seward, W., Hua, W. & Qadrdan, M., 15 Dec 2021, Microgrids and Local Energy Systems. Jenkins, N. (ed.). IntechOpen

  Research output: Chapter in Book/Report/Conference proceeding › Chapter

  • electricity 100%
  • battery 64%
  • energy 55%
  • price 41%
  • fossil 27%
• 2020

  A blockchain based peer-to-peer trading framework integrating energy and carbon markets

  Hua, W., Jiang, J., Sun, H. & Wu, J., Dec 2020, In: Applied Energy. 279, 115539.

  Research output: Contribution to journal › Article › peer-review

  • energy market 100%
  • Blockchain 86%
  • Carbon 56%
  • carbon emission 55%
  • market 53%

• Smart grid enabling low carbon future power systems towards prosumers era

  Hua, W., 8 Oct 2020

  Research output: Thesis › Doctoral Thesis

  • smart grid 100%
  • renewable energy source 77%
  • carbon emission 66%
  • thesis 47%
  • communication policy 38%

• Stackelberg game-theoretic model for low carbon energy market scheduling

  Hua, W., 1 Feb 2020, In: IET Smart Grid.

  Research output: Contribution to journal › Article › peer-review
• 2019

  A Blockchain-Based Peer-to-Peer Trading Scheme Coupling Energy and Carbon Markets

  Hua, W. & Sun, H., 11 Sept 2019, 2019 International Conference on Smart Energy Systems and Technologies (SEST). IEEE, p. 1-6 6 p. 8849111

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • energy market 100%
  • market 53%
  • carbon 42%
  • energy 18%
  • renewable energy source 14%

• A seasonal forecast scheme for the Inner Mongolia spring drought part-II: a logical reasoning evidence-based method for spring predictions

  Gao, T., Wulan, W., Yu, X., Yang, Z., Gao, J., Hua, W., Yang, P. & Si, Y., 2019, In: Theoretical and Applied Climatology.

  Research output: Contribution to journal › Article › peer-review

• Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field

  Hua, W., You, M. & Sun, H., 13 Aug 2019, 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops). IEEE, p. 204-209 6 p. 8849941

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Reinforcement learning 100%
  • Elasticity 92%
  • Carbon 75%
  • Scheduling 68%
  • Electricity 24%

• Stackelberg game-theoretic model for low carbon energy market scheduling

  Hua, W., Li, D., Sun, H. & Matthews, P., 7 Oct 2019, In: IET Smart Grid. 3, 1, p. 31 41 p.

  Research output: Contribution to journal › Article › peer-review

  • energy market 100%
  • carbon 42%
  • carbon emission 37%
  • social welfare 25%
  • policy 22%
• 2018

  Energy Hub Scheduling Method with Voltage Stability Considerations

  You, M., Hua, W., Shahbazi, M. & Sun, H., Aug 2018, 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Stackelberg Game-Theoretic Strategies for Virtual Power Plant and Associated Market Scheduling Under Smart Grid Communication Environment

  Hua, W., Sun, H., Xiao, H. & Pei, W., Oct 2018, 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets

  Hua, W., Li, D., Sun, H., Matthews, P. & Meng, F., 2018, In: International Journal of Smart Grid and Clean Energy. 7, 4, p. 231 239 p.

  Research output: Contribution to journal › Article › peer-review

  • Distributed power generation 100%
  • Power plants 80%
  • Economics 63%
  • Gas emissions 50%
  • Greenhouse gases 49%
• 2017

  Multiobjective optimization for carbon market scheduling based on behavior learning

  Li, D., Hua, W., Sun, H. & Chiu, W-Y., Dec 2017, In: Energy Procedia. 142, p. 2089 2094 p.

  Research output: Contribution to journal › Article › peer-review

• Unit commitment in achieving low carbon smart grid environment with virtual power plant

  Hua, W., Li, D., Sun, H. & Matthews, P., Sept 2017, 2017 International Smart Cities Conference (ISC2).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
• 2015

  Effects of bisphenol A, an environmental endocrine disruptor, on the endogenous hormones of plants

  Wang, S., Wang, L., Hua, W., Zhou, M., Wang, Q., Zhou, Q. & Huang, X., Nov 2015, In: Environmental Science and Pollution Research.

  Research output: Contribution to journal › Article › peer-review
• 2014

  Photosynthesis, chlorophyll fluorescence characteristics, and chlorophyll content of soybean seedlings under combined stress of bisphenol A and cadmium: Combined effects of bisphenol A and cadmium on soybean

  Hu, H., Wang, L., Wang, Q., Jiao, L., Hua, W., Zhou, Q. & Huang, X., Nov 2014, In: Environmental Toxicology and Chemistry.

  Research output: Contribution to journal › Article › peer-review