Yinliang Xu


Assistant Professor

E-mail : xu.yinliang@sz.tsinghua.edu.cn

Tel & Fax : 86-755-36881066

Title: Assistant Professor
Office:Tower C2, Room1502, Nanshan Intelligent Park 1001 Xueyuan Blvd
Website:http://www.tbsi.edu.cn/index.php?s=/cms/142.html

Biography
Dr. Yinliang Xu is an Assistant Professor with TBSI. He received the B.S. and M.S. degrees in Control Science and Engineeringfrom Harbin Institute of Technology in 2007 and 2009, respectively, and the Ph.D. degrees inElectrical and Computer Engineering, New Mexico State University, USA. He was a Research Assistant at Siemens Corporate Research in 2011 and aResearch Associate, Penn State University in 2013. He was a visiting scholar at Carnegie Mellon University during 2013-2014 and an adjunct faculty at Department of Electrical and Computer Engineering,Carnegie Mellon University,Pittsburgh, PA, USA,during 2015-2018. He was an assistant professor at Sun Yat-sen University in 2013 and was promoted to associate professor in 2017. His research interests include power distribution systems, microgrids, renewable integration, virtual power plant, power system modeling, artificial intelligence,and distributed control and optimization. He is the Principal Investigator for a multitude of projects focused on these topics and funded by the National Science Foundation of China, China Southern power grid, Shenzhen science and Technology Innovation Committee, and Industry.

Research
Research Interests

-Integrated energy systems, energy internet, multi-energy system optimization and control;
-Distributed control and optimization algorithm design and real-timeimplementation;
-Artificial intelligence in smart grids;
-Modeling and controlof smart grid with high penetration of renewable generations.

Research Description
Distributed Control and Optimization in Smart Grids
The ever-growing demand, rising penetration level of renewable generation, and increasing complexity of electric power systems, pose new challenges to control, operation, management and optimization of power grids. Conventional centralized control structure requires a complex communication network with two-way communication links and a powerful central controller to process large amount of data, which reduces overall system reliability and increases its sensitivity to failures, thus it may not be able to operate under the increased number of distributed renewable generation units. Prof. Xu’s group exploresdistributed control strategy that enables easier scalability, simpler communication network, faster distributed data processing, and can facilitate highly efficient information sharing and decision making. Distributed approach is a promising candidate to address the features of modern power grids by providing fast, flexible, reliable and cost-effective solutions.
Artificial Intelligence (AI)in Smart Grids
Power systems keep on increasing on the basis of geographical regions, assets additions, and introduction of new technologies in generation, transmission and distribution of electricity. AI techniques have become popular for solving different problems in power systems like control, planning, scheduling, forecast, etc. These techniques can deal with difficult tasks faced by applications in modern large power systems with even more interconnections installed to meet the increasing load demand and intermittent renewable generation. Prof. Xu’s group focus on the research to perceive full advantages of upcoming AItechnology for improving the efficiency of electricity market investment, distributed control and optimization, efficient system modeling and analysis, particularly power systems with high penetration level of renewable energy resources.
Integrated Energy Systems/Energy Internet/Multi-Energy System Optimization and Control
Electricity, district heating/coolingsystems, natural gas, and electric vehiclesare predominantly planned and operated independently. However, it is increasingly recognized that integrated optimization and control of such systems at multiple spatio-temporal scales can bring significant socioeconomic, operational efficiency, and environmental benefits. Accordingly, the concept of the multi-energy system is gaining considerable attention, Prof. Xu’s group focus on uncovering fundamental gains and potential drawbacksthat emerge from the integrated operation of multiple systems; developing computationally affordable optimization and control methods that maximize the overall social welfare, while acknowledging intrinsic interdependencies and quality-of-service requirements for each provider.

Education
Ph.D. in
Electrical and Computer Engineering, New Mexico State University, USA, 1/2010~8/2013
M.S. in Control Science and Engineering, Harbin Institute of Technology, China, 9/2007~12/2009
B.S. in Control Science and Engineering,Harbin Institute of Technology, China, 9/2003~7/2007

Professional Experience
2017-present Assistant Professor, Tsinghua-Berkeley Shenzhen Institute (TBSI), Shenzhen.
2015-2018 Adjunct Faculty, Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA, USA.
2017-2017 Associate Professor, Sun Yat-sen University, Guangdong, China,School of Electronics and Information Technology
2013-2017 Assistant Professor, Sun Yat-sen University, Guangdong, China,SYSU-CMU Joint Institute of Engineering
2013-2014 Visiting Professor, Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA, USA.
2013-2013 Research Associate,Penn State University, State College, PA.
2011-2011 Research Assistant, Siemens Corporate Research, Princeton, NJ

Teaching
Distributed Control and Optimization in Power Systems(2018Fall)
Power SystemsDynamics (2019Spring)
Computational Methods for Electric Power Systems (2019 Spring)

Opening
We are looking for Post Doctors, Ph. D. and Master students with self-motivation and strong interests in power and energy areas which include but NOT limited to:
-Mathematical modeling and optimization
-Power distribution system and microgrids
-Power system modeling, identification, dynamic/static stability, and control
-Big data and artificial intelligence
-Multi-energy system/ multi-energy router system/ energy internet
-Advanced distributed control and optimization techniques
-Electricity market, multi-energy market and economy

Preference will be given to those who have strong mathematical background, good programming skills and are familiar with one or more of the following tools: MATLAB/Simulink, C/C++ ,JAVA, PSCAD, DIgSILENT, OpenDSS, PSS/E, PSLF, MATPOWER, CPLEX, GAMS, AMPL.
Post Docs positions are available, please refer to:http://www.tbsi.edu.cn/index.php?s=/cms/list/27/typeid/191.html

Publications (Journal Paper)
B1 Y. Xu, W. Zhang,and W. Liu,Smart Grids:Clouds, Communications, Open Source, and Automation, Chapter 14 a consensus-based fully distributed load management algorithm for smart grid, CRC Press, 2014.
J51.I. Khan, Y. Xu*, S. Kar, M. Chow, et. al, “Compressive Sensing and Morphology Singular Entropy-Based Real-time Secondary Voltage Control of Multi-area Power Systems” IEEE Transactions on Industrial Informatics, (In revision, SCI, IF: 5.43).
J50. Y. Xu*, H. Sun, and W. Gu, “A Novel Discounted Min-consensus Algorithm forOptimal Electrical Power Trading in Grid-ConnectedDC Microgrids” IEEE Transactions on Industrial Electronics (In revision, SCI, IF:7.07).
J49.Y. Xu*, Z. Yi, J. Hu, M. Chow, “Distributed Approach for Economic Dispatch in an Integrated Energy System,” IEEE Transactions on Industrial Informatics, (In revision, SCI, IF: 5.43).
J48. Y. Xu*, H Sun, Q. Guo, and Z. Fei, “Distributed Discrete Robust Secondary Cooperative Control for Islanded Microgrids,” IEEE Trans. Smart Grid, 2017. (Accepted, SCI, IF: 6.645)
J47. W. Zhang and Y. Xu*, “Distributed Optimal Control for Multiple Microgrids in a Distribution Network,” IEEE Trans. Smart Grid, 2017. (Accepted, SCI, IF: 6.645)
J46.Y. Xu, W. Zhang*, M. Chow, H. Sun, and J. Peng,“A Distributed Model-Free Controller for Enhancingthe Power System Frequency Transient Stability” IEEE Transactions on Industrial Informatics (SCI, IF: 5.43, Accepted).
J45. J. Hu, Y. Shan, Y. Xu, J. Guerrero,“A coordinated control of hybrid ac/dc microgrids with PV-wind-battery under variable generation and load conditions,”International Journal of Electrical Power & Energy Systems, vol. 104,pp.583-592, 2019.
J44. H. Qiu, W. Gu, Y. Xu and B. Zhao, "Multi-Time-Scale Rolling Optimal Dispatch for AC/DC Hybrid Microgrids With Day-Ahead Distributionally Robust Scheduling," IEEE Trans. Sustain. Energy.doi: 10.1109/TSTE.2018.2868548.
J43. H. Qiu, W. Gu, Y. Xu, Z. Wu, S. Zhou and J. Wang, "Interval-partitioned uncertainty constrained robust dispatch for ac/dc hybrid microgrids with uncontrollable renewable generators," IEEE Trans. Smart Grid.doi: 10.1109/TSG.2018.2865621.
J42. H. Qiu, W. Gu, J. Pan, B. Xu, Y. Xu, M. Fan, Z. Wu, “Multi-interval-uncertainty constrained robust dispatch for AC/DC hybrid microgrids with dynamic energy storage degradation,” Applied Energy, vol. 228, pp. 205-214, Oct. 2018.
J41. Y. Xu*, “Optimal control based energy management of multiple energy storage systems in a microgrid" IEEE Access,2017 (SCI, IF:3.244, Accepted).
J40. Z. Deng,Y. Xu*, and H Sun, “Distributed, Bounded and Finite-time Convergence Secondary Frequency Control in an Autonomous Microgrid,” IEEE Trans. Smart Grid, 2017. (Accepted, SCI, IF: 6.645)
J39. J. Hu, Y. Xu, K. Cheng, and J. Guerrero, “A model predictive control strategy of PV-battery microgrid under variable power generations and load conditions,” Applied Energy, 2018. (Accepted, SCI, IF:7.182)
J38. S. Shi, Z. Fei, T. Wang and Y. Xu, "Filtering for Switched T-S Fuzzy Systems With Persistent Dwell Time," IEEE Trans. Cybernetics, 2018. doi: 10.1109/TCYB.2018.2816982
J37. Y. Xu*, H Sun, W. Gu, Y. Xu, Z. Li, “Optimal distributed control for secondary frequency and voltage regulation in an islanded microgrid”IEEE Transactions on Industrial Informatics (SCI, IF: 6.764, Accepted).
J36G. Lou, W. Gu, Y. Xu, W. Jin and X. Du, "Stability Robustness for Secondary Voltage Control in Autonomous Microgrids With Consideration of Communication Delays," IEEE Transactions on Power Systems, 2017 (SCI, IF:5.68, Accepted).
J35. I. Khan, Y. Xu*, V. Bhattacharjee, H Sun, et. al., “Distributed Optimal Reactive Power Control of Power Systems”IEEE Access, 2017 (SCI, IF:3.244, Accepted).
J34 Z. Li, M. Li*, Y. Xu, H. Huang, and S.Misra. “Finite-time Stability and Stabilization of Semi-Markovian Jump Systems with Time Delay,” International Journal of Robust and Nonlinear Control. Accepted and in press, 2017(SCI&EI IF:3.393)
J33. Y. Xu* and H. Sun, "Distributed Finite-Time Convergence Control of an Islanded Low-Voltage AC Microgrid," IEEE Transactions on Power Systems, 2017 (SCI, IF:5.68, Accepted).
J32. Y Xu*, H. Sun, H. Liu, Q. Fu, “Distributed solution to DC optimal power flow with congestion management,” International Journal of Electrical Power & Energy Systems, Volume 95, 2018, pp. 73-82, 2017. (SCI, IF:3.289).
J31. I. Khan, Y. Xu*, S Kar, H Sun, “Compressive Sensing-based Optimal Reactive Power Control of a Multi-area Power System”IEEE Access, 2017, vol. 5, pp.23576 - 23588,2017 (SCI, IF:3.244).
J30. Z. Li, Q. Guo, H. Sun, J. Wang, Y. Xu and M. Fan, "A Distributed Transmission-Distribution-Coupled Static Voltage Stability Assessment Method Considering Distributed Generation," IEEE Transactions on Power System, 2017. (Accepted, SCI, IF: 5.68).
Before joining TBSI
J29.Y. Xu, Z. Li*, J. Zhao, and J. Zhang, “Distributed robust control strategy of grid-connected inverters for energy storage system’s state-of-charge balancing,” IEEE Transactions on Smart Grid, 2017. (Accepted, SCI, IF: 6.645)
J28. M. H. Amini, P. McNamara, P. Weng, O. Karabasoglu and Y. Xu, "Hierarchical electric vehicle charging aggregator strategy using Dantzig-Wolfe decomposition," IEEE Design & Test, (Accepted, SCI, IF: 1.366)
J27. Z. Li, Y. Xu*, Z. Fei, H. Huang, and S. Misra, “Stability Analysis and Stabilization of Markovian Jump Systems with Time-varying Delay and Uncertain Transition Information,” International Journal of Robust and Nonlinear Control, 2017. (Accepted, SCI, IF: 3.393)
J26.Z. Deng, Y. Xu*, Wei Gu, Z. Fei, “Finite-time convergence robust control of battery energy storage system to mitigate wind power fluctuations,” International Journal of Electrical Power & Energy Systems, vol. 91, pp. 144-154, 2017. (SCI, IF: 3.289)
J25. Y. Xu*, “Robust Finite-Time Control for Autonomous Operation of anInverter-Based Microgrid,” IEEE Transactions on Industrial Informatics, vol. 13, no. 5, pp. 2717 - 2725, 2017. (SCI, IF:6.764, Accepted)
J24. Y. Xu*, Z. Li, J. Zhang, Z. Fei and W. Liu. "Real-Time Compressive Sensing based Control Strategy for a Multi-area Power System," IEEE Transactions on Smart Grid, 2016(Accepted, SCI, IF: 6.645).
J23. Y. Xu*, J. Hu, W. Gu, W. Su and W. Liu. "Real-Time Distributed Control of Battery Energy Storage Systems for Security Constrained DC-OPF," IEEE Transactions on Smart Grid, 2016 (Accepted, SCI, IF: 6.645).
J22. Y. Xu*, Z. Yang, W. Gu, and Z. Deng. "Robust Real-time Distributed Optimal Control Based Energy Management in a Smart Grid," IEEE Transactions on Smart Grid, vol.8, no. 4, pp.1568-1579, 2017. (SCI, IF: 6.645).
J21. J. Yang, Y. Xu, and Z. Yang, "Regulating the Collective Charging Load of Electric Taxi Fleet via Real Time Pricing"IEEE Transactions on Power System, vol.32, no. 5, pp.3694-3703, 2017. (SCI, IF: 5.68).
J20. J. Zhang, S. Lin, H. Liu, Y. Chen, Y. Xu, “A small-population based parallel differentialevolution algorithm for short-term hydrothermal scheduling problem considering powerflow constraints,” Energy, 123, pp. 538~554, 2017. (SCI, IF: 4.52)
J19. Z. Fei, C. Guan, Z, Li, and Y. Xu, "New Results on Finite Frequency H-infinity Performance forDiscrete Linear Time Delay Systems," International Journal of Systems Science, vol.48, no. 7, pp.1548-1555, 2017.(SCI, IF: 2.285).
J18. G. Lou, W. Gu, Y. Xu, W. Liu and M. Chen. "Distributed MPC-based Secondary Voltage Control Scheme for Autonomous Droop-Controlled Microgrids," IEEE Transactions on Sustainable Energy,vol.8, no. 2, pp.792-804, 2017. (SCI, IF: 4.909).
J17. I. Khan, Z. Li, Y. Xu* andW. Gu, "Distributed control algorithm for optimal reactive power control in power grids," International Journal of Electrical Power and Energy Systems, vol. 83, pp 505–513, Dec. 2016.(SCI, IF: 3.289)
J16. W. Liu, W. Gu, Y. Xu, Y. Wang and K. Zhang, “A General Distributed Secondary Control for Multi-Microgrids withboth PQ-controlled and Droop-controlled Distributed Generators,” IET Generation, Transmission & Distribution, vol.11, no.3, pp.707-718, 2017 (SCI, IF: 2.213).
J15. G. Xu, Z. Fei, Z. Li, and Y. Xu, “Improved H_inf Filter Design for Discrete-time Markovian Jump Systems with Time-varying Delay,” Journal of the Franklin Institute, vol.353, no.16, pp.4156-4175, 2016 (SCI, IF: 3.139).
J14. W. Zhang, Y. Xu, S. Li, etc. "A Distributed Dynamic Programming-based Solution for Load Management in Smart Grids," IEEE SystemsJournal,2016 (SCI, IF:3.882, Accepted).
J13. Z. Li, Y. Xu, H. Huang, and S. Misra. “Sparse Control and Compressed Sensing inNetworked Switched Systems”, IET Control Theory & Applications, vol. 10, no. 9, pp. 1078–1087, 2016 (SCI, IF:2.536)
J12. Y. Xu*, W. Zhang, and W. Liu. "Distributed dynamic programming based approach for economic dispatch in smart grids," IEEE Transactions on Industrial Informatics, vol. 11, no. 1, pp. 166-175, Feb. 2015. (SCI, IF: 6.764).
J11. W. Zhang, Y. Xu, W. Liu*, C. Zang, and H. Yu. "Distributed online optimal energy management for smart grids," IEEE Transactions on Industrial Informatics, vol. 11, no. 3, pp. 717-727, June 2015. (SCI, IF: 6.764).
J10. Z. Li, Y. Xu,Z. Fei, and R. Agarwal. “Exponential stability analysis and stabilization of switched delay systems,”Journal of the Franklin Institute, vol. 352, no. 11, pp. 4980–5002, 2015.(SCI, IF: 3.139).
J9. W. Liu, W. Gu*, Y. Xu, S.Xue, M. Chen, B. Zhao, and M. Fan,"Improved average consensus algorithm based distributed cost optimization for loading shedding of autonomous microgrids,"International Journal of Electrical Power & Energy Systems,vol. 73, pp. 89–96, 2015. (SCI, IF: 3.289).
J8. Y. Xu*, W. Zhang, G. Hug, S Kar and Z. Li. "Cooperative control of distributed energy storage systems in a microgrid," IEEE Transactions on Smart Grid, vol. 6, no. 1, pp. 238-248, 2015. (SCI, IF: 6.645).
J7. Y. Xu*. "Optimal distributed charging rate control of plug-in electric vehicles for demand management," IEEE Transactions on Power Systems, vol. 30, no. 3, pp. 1536-1545, 2015. (SCI, IF: 5.68)
J6. Y. Xu*, and Z. Li, "Distributed optimal resource management based on consensus algorithm in a microgrid," IEEE Transactions on Industrial Electronics, vol. 62, no. 4, pp. 2584-2592, 2015. (SCI, IF: 7.168)
J5. Y. Xu, W. Zhang, W. Liu*, et al. "Distributedsubgradient-based coordination of multiple renewable generators in a microgrid," IEEE Transactions on Power Systems, vol.29, no.1, pp.23-33, 2014. (SCI, IF: 5.68)
J4. W. Zhang, Y. Xu, W. Liu*, etc. "Cooperative control of multiple wind turbine generators for load sharing," IEEE Transactions on Smart Grid, vol. 4, no. 2, pp. 806- 815, 2013. (SCI, IF: 6.645)
J3. Y. Xu, W. Zhang, and W. Liu*Frank Ferrese, "Multi-agent based reinforcement learning for optimal reactive power dispatch," IEEE Trans. on Systems, Man, and Cybernetics--Part C: Applications and Reviews, vol. 42, no. 6, pp. 1742-1751, 2012.
J2. Y. Xu and W. Liu*, "Stable multi-agent based load shedding algorithm for power systems," IEEE Transactions on Power Systems, vol. 26, no. 4, pp. 2006-2014, 2011.(SCI, IF:5.68)
J1. Y. Xu and W. Liu*, "Novel multi agent based load restoration algorithm for microgrids," IEEE Transactions on Smart Grid, vol. 2, no. 1, pp. 140-149, 2011. (SCI, IF=6.645)