All Outputs (10)

Blockchain and Artificial Intelligence Technologies for Smart Energy Systems (2023)
Book
Sun, H., Hua, W., & You, M. (2023). Blockchain and Artificial Intelligence Technologies for Smart Energy Systems. New York: CRC. https://doi.org/10.1201/9781003170440

Present energy systems are undergoing a radical transformation, driven by the urgent need to address the climate change crisis. At the same time, we are witnessing the sharp growth of energy data and a revolution of advanced technologies, with artifi... Read More about Blockchain and Artificial Intelligence Technologies for Smart Energy Systems.

A Blockchain Based Peer-to-Peer Trading Framework Integrating Energy and Carbon Markets (2020)
Journal Article
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, Article 115539. https://doi.org/10.1016/j.apenergy.2020.115539

Prosumers are active participants in future energy systems who produce and consume energy. However, the emerging role of prosumers brings challenges of tracing carbon emissions behaviours and formulating pricing scheme targeting on individual prosump... Read More about A Blockchain Based Peer-to-Peer Trading Framework Integrating Energy and Carbon Markets.

Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field (2019)
Presentation / Conference Contribution
Hua, W., You, M., & Sun, H. (2019). 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) ; proceedings (204-209). https://doi.org/10.1109/iccchinaw.2019.8849941

Energy hub scheduling plays a vital role in optimally integrating multiple energy vectors, e.g., electricity and gas, to meet both heat and electricity demand. A scalable scheduling model is needed to adapt to various energy sources and operating con... Read More about Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field.

Stackelberg Game-theoretic Model for Low Carbon Energy Market Scheduling (2019)
Journal Article
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. https://doi.org/10.1049/iet-stg.2018.0109

Excessive carbon emissions have posed a threat to sustainable development. An appropriate market-based low carbon policy becomes the essence of regulating strategy for reducing carbon emissions in the energy sector. This study proposes a Stackelberg... Read More about Stackelberg Game-theoretic Model for Low Carbon Energy Market Scheduling.

A Blockchain-Based Peer-to-Peer Trading Scheme Coupling Energy and Carbon Markets (2019)
Presentation / Conference Contribution
Hua, W., & Sun, H. (2019). A Blockchain-Based Peer-to-Peer Trading Scheme Coupling Energy and Carbon Markets. In 2019 International Conference on Smart Energy Systems and Technologies (SEST) ; proceedings. https://doi.org/10.1109/sest.2019.8849111

Climate change enforces the integration of distributed renewable energy sources and development of carbon price scheme. Whilst the energy is traded among distributed prosumers, the carbon responsibilities and corresponding allowances trading need to... Read More about A Blockchain-Based Peer-to-Peer Trading Scheme Coupling Energy and Carbon Markets.

Stackelberg Game-Theoretic Strategies for Virtual Power Plant and Associated Market Scheduling Under Smart Grid Communication Environment (2018)
Presentation / Conference Contribution
Hua, W., Sun, H., Xiao, H., & Pei, W. (2018). 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) (1-6). https://doi.org/10.1109/smartgridcomm.2018.8587583

In order to schedule the virtual power plant and corresponding energy market operation, a two-scenario Stackelberg game-theoretic model is proposed to describe interactions between market operator and VPP operator. During market operation, the market... Read More about Stackelberg Game-Theoretic Strategies for Virtual Power Plant and Associated Market Scheduling Under Smart Grid Communication Environment.

Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets (2018)
Journal Article
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. https://doi.org/10.12720/sgce.7.4.231-239

In order to alleviate the effects of greenhouse gas emissions, the environmental and economic dispatch (EED) is formulated as multiobjective optimization problem (MOP) solved by multiobjective immune algorithm (MOIA). Building on this model, the virt... Read More about Stochastic environmental and economic dispatch of power systems with virtual power plant in energy and reserve markets.

Energy Hub Scheduling Method with Voltage Stability Considerations (2018)
Presentation / Conference Contribution
You, M. Y., Hua, W., Shahbazi, M., & Sun, H. (2018). Energy Hub Scheduling Method with Voltage Stability Considerations. In 2018 IEEE/CIC International Conference on Communications in China (ICCC Workshops), 6-18 August 2018, Beijing, China (196-200). https://doi.org/10.1109/iccchinaw.2018.8674468

Energy Hub is expected to be one of the most effective methods to address the integrated system with multiple energy carriers. In this work, an Energy Hub scheduling method is proposed, which could not only meet various energy load demands but also a... Read More about Energy Hub Scheduling Method with Voltage Stability Considerations.

Multiobjective optimization for carbon market scheduling based on behavior learning (2017)
Presentation / Conference Contribution
Li, D., Hua, W., Sun, H., & Chiu, W. (2017). Multiobjective optimization for carbon market scheduling based on behavior learning. . https://doi.org/10.1016/j.egypro.2017.12.581

With advances of smart grid, the responsibility of carbon emission reduction can be fairly allocated to each participant in power networks through bidirectional communications. This paper proposes a hierarchical carbon market scheduling model to effe... Read More about Multiobjective optimization for carbon market scheduling based on behavior learning.

Unit Commitment in Achieving Low Carbon Smart Grid Environment with Virtual Power Plant (2017)
Presentation / Conference Contribution
Hua, W., Li, D., Sun, H., & Matthews, P. (2017). Unit Commitment in Achieving Low Carbon Smart Grid Environment with Virtual Power Plant. In 2017 IEEE International Smart Cities Conference (ISC2) : 14-17 September 2017, Wuxi, China ; proceedings (1-6). https://doi.org/10.1109/isc2.2017.8090810

This paper proposes a novel unit commitment (UC) model under smart grid (SG) environment, which intends to strike a balance pursuing minimum carbon emissions for policy maker, minimum costs for generators and minimum payment bills for consumers. This... Read More about Unit Commitment in Achieving Low Carbon Smart Grid Environment with Virtual Power Plant.