All Outputs (4)

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 Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems (2020)
Journal Article
You, M., Zhang, X., Zheng, G., Jiang, J., & Sun, H. (2020). A Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems. IEEE Access, 8, 88651-88663. https://doi.org/10.1109/access.2020.2992906

In Smart Grid, the integration of Information and Communications Technology (ICT) systems and power systems has enabled real-time services and distributed controls, while the fusion of technologies necessitates a profound and versatile platform for t... Read More about A Versatile Software Defined Smart Grid Testbed: Artificial Intelligence Enhanced Real-Time Co-Evaluation of ICT Systems and Power Systems.

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, December). Real-Time Price Elasticity Reinforcement Learning for Low Carbon Energy Hub Scheduling Based on Conditional Random Field. Presented at 2019 IEEE/CIC International Conference on Communications Workshops in China (ICCC Workshops)., Changchun, China

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.

Effective Rate Analysis in Weibull Fading Channels (2016)
Journal Article
You, M., Sun, H., Jiang, J., & Zhang, J. (2016). Effective Rate Analysis in Weibull Fading Channels. IEEE Wireless Communications Letters, 5(4), 340-343. https://doi.org/10.1109/lwc.2016.2558179

Recently the theory of effective rate has attracted much attention, since it can take the delay aspect into account when performing channel capacity analysis.Weibull fading model is a flexible and practical model for describing fading channels in bot... Read More about Effective Rate Analysis in Weibull Fading Channels.