Web-of-Science Highly Cited Paper

[1]. Coordinated Preparation and Recovery of A Multi-energy Distribution System Considering Thermal Inertia and Diverse Uncertainties
Z. Li, Y. Xu*, P. Wang, and G. Xiao, “Coordinated Preparation and Recovery of A Multi-energy Distribution System Considering Thermal Inertia and Diverse Uncertainties,” Applied Energy, vol. 336, Apr. 2023.
[2]. Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids
Z. Li, L. Wu, Y. Xu, et al, “Distributed tri-layer risk-averse stochastic game approach for energy trading among multi-energy microgrids,” Applied Energy, vol. 331, Feb. 2023.
[3]. Multi-Stage Real-time Operation of A Multi-energy Microgrid With Electrical and Thermal Energy Storage Assets: A Data-Driven MPC-ADP Approach
Z. Li, L. Wu, Y. Xu, S. Moazeni, and Z. Tang, “Multi-Stage Real-time Operation of A Multi-energy Microgrid With Electrical and Thermal Energy Storage Assets: A Data-Driven MPC-ADP Approach,” IEEE Trans. Smart Grid, vol. 13, no. 1, pp. 213-226, Jan. 2022.
[4]. A Risk-Averse Adaptively Stochastic Optimization Method for Multi-Energy Ship Operation Under Diverse Uncertainties
Z. Li, Y. Xu*, L. Wu, and X. Zheng, “A Risk-Averse Adaptively Stochastic Optimization Method for Multi-Energy Ship Operation Under Diverse Uncertainties,” IEEE Trans. Power Syst., vol. 36, no. 3, pp. 2149-2161, May 2021.
[5]. Optimal Stochastic Deployment of Heterogeneous Energy Storage in a Residential Multi-energy Microgrid With Demand-Side Management
Z. Li, Y. Xu*, X. Feng and Q. Wu, “Optimal Stochastic Deployment of Heterogeneous Energy Storage in a Residential Multi-energy Microgrid With Demand-Side Management,” IEEE Trans. Industrial Informatics, vol. 17, no. 2, pp. 991-1004, Feb. 2021.
[6]. Distributed Resilient Control for Energy Storage Systems in Cyber-Physical Microgrids
C. Deng, Y. Wang, C. Wen, Y. Xu, and P. Lin, “Distributed Resilient Control for Energy Storage Systems in Cyber-Physical Microgrids,” IEEE Trans. Industrial Informatics, vol. 17, no. 2, pp. 1331-1341, Feb. 2021.
[7]. A Distributed Control Scheme of Microgrids in Energy Internet Paradigm and Its Multisite Implementation
Y. Wang, T.L. Nguyen, M. Syed, Y. Xu*, E. Guillo-Sansano, V.H. Nguye, G. Burt, and Q.T. Tran, “A Distributed Control Scheme of Microgrids in Energy Internet Paradigm and Its Multisite Implementation,” IEEE Trans. Industrial Informatics, vol. 17, no. 2, pp. 1141-1153, Feb. 2021.
[8]. State-of-Health Estimation and Remaining-Useful-Life Prediction for Lithium-ion Battery Using A Hybrid Data-driven Method
B. Gou, Y. Xu*, and X. Feng, “State-of-Health Estimation and Remaining-Useful-Life Prediction for Lithium-ion Battery Using A Hybrid Data-driven Method,” IEEE Trans. Vehicular Technology, vol. 69, no. 10, pp. 10854-10867, Oct. 2020.
[9]. A Multi-agent Reinforcement Learning based Data-driven Method for Home Energy Management
X. Xu, Y. Jia, Y. Xu, Z. Xu, S. Chai, and C.S. Lai, “A Multi-agent Reinforcement Learning based Data-driven Method for Home Energy Management,” IEEE Trans. Smart Grid, vol. 11, no. 4, pp. 3201-3211, July 2020.
[10]. Data-driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method with Continuous Action Search
Z. Yan and Y. Xu*, “Data-driven Load Frequency Control for Stochastic Power Systems: A Deep Reinforcement Learning Method with Continuous Action Search,” IEEE Trans. Power Syst., vol. 34, no. 2, pp. 1653-1656, Mar. 2019.
[11]. A two-layer energy management system for microgrids with hybrid energy storage considering degradation costs
C. Ju, P. Wang, L. Goel, and Y. Xu*, “A two-layer energy management system for microgrids with hybrid energy storage considering degradation costs,” IEEE Trans. Smart Grid, vol.9, no.6, pp.6047-6057, Nov. 2018.
[12]. A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems
W. Yao, J. Zhao, F. Wen, Z.Y. Dong, Y. Xue, Y. Xu, and K. Meng, “A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems,” IEEE Trans. Power Systems, vol. 29, no.4, pp. 1811-1821, Jul. 2014.
[13]. A Distributed Control Scheme of Thermostatically Controlled Loads for Building-Microgrid Community
Y. Wang, Y. Tang, Y. Xu*, Y.L. Xu, “A Distributed Control Scheme of Thermostatically Controlled Loads for Building-Microgrid Community,” IEEE Trans. Sustainable Energy, vol. 11, no. 1, pp. 350-360, Jan. 2020.
[14]. A review on supercooling of phase change in thermal energy storage systems
A. Safari, S. Rahman, F. Sulaiman, Y. Xu, and Z.Y. Dong, “A review on supercooling of phase change in thermal energy storage systems,” Renewable & Sustainable Energy Reviews, vol.70, pp.905-919, Apr. 2017.
[15]. Short-Term Residential Load Forecasting based on LSTM Recurrent Neural Network
W. Kong, Z.Y. Dong, Y. Jia, D.J. Hill, Y. Xu, and Y. Zhang, “Short-Term Residential Load Forecasting based on LSTM Recurrent Neural Network,” IEEE Trans. Smart Grid, vol.10, no.1, pp. 841-851, Jan. 2019.
[16]. Short-term residential load forecasting based on resident behaviour learning
W. Kong, Z.Y. Dong, D. Hill, F. Luo, and Y. Xu, “Short-term residential load forecasting based on resident behaviour learning,” IEEE Trans. Power Syst., vol. 33, no. 1, pp. 1087-1088, Jan. 2018.
[17]. Three-Stage Robust Inverter-Based Voltage/Var Control for Distribution Networks with High PV
C. Zhang, Y. Xu*, Z.Y. Dong, and J. Ravishankar “Three-Stage Robust Inverter-Based Voltage/Var Control for Distribution Networks with High PV,” IEEE Trans. Smart Grid, vol.10, no.1, pp. 782-793, Jan. 2019.
[18]. Robust Coordination of Distributed Generation and Price-Based Demand Response in Microgrids
C. Zhang, Y. Xu, Z.Y. Dong, and K.P. Wong, “Robust Coordination of Distributed Generation and Price-Based Demand Response in Microgrids,” IEEE Trans. Smart Grid, vol.9, no. 5, pp. 4236-4247, Sep. 2018.
[19]. Optimal coordinated energy dispatch for a multi-energy microgrid in grid-connected and islanded modes
Z. Li and Y. Xu*, “Optimal coordinated energy dispatch for a multi-energy microgrid in grid-connected and islanded modes,” Applied Energy, vol.210, pp. 974-986, Jan. 2018.
[20]. Electric vehicle battery charging/swap stations in distribution systems: comparison study and optimal planning
Y. Zheng, Z.Y. Dong, Y. Xu, K. Meng, J.H. Zhao, and J. Qiu, “Electric vehicle battery charging/swap stations in distribution systems: comparison study and optimal planning,” IEEE Trans. Power Systems, vol. 29, no. 1, pp.221-229, Jan. 2014.

Award-Winning Papers

[1]. Hierarchically-Coordinated Voltage/VAR Control of Distribution Networks using PV Inverters
C. Zhang and Y. Xu*, “Hierarchically-Coordinated Voltage/VAR Control of Distribution Networks using PV Inverters,” IEEE Trans. Smart Grid, vol. 11, no. 4, pp. 2942-2953, July 2020. - IEEE Transactions on Smart Grid Outstanding Paper Award
[2]. Optimal coordinated energy dispatch for a multi-energy microgrid in grid-connected and islanded modes
Z. Li and Y. Xu*, “Optimal coordinated energy dispatch for a multi-energy microgrid in grid-connected and islanded modes,” Applied Energy, vol.210, pp. 974-986, Jan. 2018. - Applied Energy Highly Cited Paper Award
[3]. Multi-stage coordinated operation of a multi-energy microgrid with residential demand response under diverse uncertainties
Y. Chen, X. Feng, Z. Li, Y. Xu*, “Multi-stage coordinated operation of a multi-energy microgrid with residential demand response under diverse uncertainties,” IET Energy Conversion & Economics, vol.1, issue 1, Sep. 2020. - 2022 The IET Premium Award – Best Paper in Energy Conversion and Economics

Conference Best Paper Award

[1]. Frequency-constrained robust service restoration of distribution networks under renewable power uncertainty
D. Xie and Y. Xu, “Frequency-constrained robust service restoration of distribution networks under renewable power uncertainty,” IEEE Conference on Energy Internet and Energy System Integration (EI2), Hangzhou, China, Dec. 2023. (Best Paper Award)
[2]. Cooperative Wind Farm Control with Hybrid-Model-Based Deep Deterministic Policy Gradient and Model Selection
H. Zhao, G. Liang, G. Liu, J. Zhao, and Y. Xu, “Cooperative Wind Farm Control with Hybrid-Model-Based Deep Deterministic Policy Gradient and Model Selection,” Proc. IEEE 4th Conference on Energy Internet and Energy System Integration (EI2), Taiyuan, China, Nov. 2021. (Best Paper Award)
[3]. Fuzzy-logic based Adaptive Control of Distributed Energy Storage Systems for Simultaneous V/f Regulation
W. Liu, Y. Xu, Y. Wang, and X. Feng, “Fuzzy-logic based Adaptive Control of Distributed Energy Storage Systems for Simultaneous V/f Regulation,” Proc. IEEE PES General Meeting, Montreal, Canada, Aug. 2020. (Best Paper Award)
[4]. Remaining Useful Life Prediction for Lithium-ion Battery Using Ensemble Learning Method
B. Gou, Y. Xu, et al, “Remaining Useful Life Prediction for Lithium-ion Battery Using Ensemble Learning Method,” Proc. IEEE PES General Meeting, Atlanta, US, Aug. 2019. (Best Paper Award)
[5]. Multi-Objective Robust Voltage/VAR Control for Active Distribution Networks
C. Zhang, Z.Y. Dong, and Y. Xu, “Multi-Objective Robust Voltage/VAR Control for Active Distribution Networks,” Proc. IEEE PES General Meeting, Atlanta, US, Aug. 2019. (Best Paper Award)
[6]. Two-stage robust operation for islanded multi-energy micro-grids
C. Zhang, Y. Xu, Z.Y. Dong, “Two-stage robust operation for islanded multi-energy micro-grids,” Proc. 11th IET APSCOM, Hong Kong, Nov. 2018. (Best Paper Award)
[7]. A two-stage robust operation approach for combined cooling, heat and power systems
C. Zhang, Y. Xu, Z.Y. Dong, and Y. Chen, “A two-stage robust operation approach for combined cooling, heat and power systems,” IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, Nov. 2017. (Best Paper Award)
[8]. Enhancing security and resilience of bulk power systems via multisource big-data learning
L. Guan, J. Zhang, Y. Xu, et al, “Enhancing security and resilience of bulk power systems via multisource big-data learning,” Proc. IEEE PES General Meeting, Chicago, US, Jul 2017. (Best Paper Award)

Book

[1] Y. Xu, Y. Zhang, Z.Y. Dong, R. Zhang, "Intelligent Systems for Stability Assessment and Control of Smart Power Grids,” CRC Press, 2020, ISBN-13: 978-1138063488. Buy now Website Link 1 Buy now Website Link 2

[2] Y. Xu, Y. Chi, and H. Yuan, “Stability-Constrained Optimization for Modern Power System Operation and Planning,” Wiley-IEEE Press, 2023, ISBN: 978-1-119-84886-8. Buy now Website Link 1 Buy now Website Link 2

[3] Y. Xu, Y. Wang, C. Zhang, and Z. Li, "Coordination of Distributed Energy Resources in Microgrids: Optimisation, control, and hardware-in-the-loop validation,” IET Press, 2021, ISBN-13: 978-1-83953-268-9. Buy now Website Link 1 Buy now Website Link 2