Dr. Yinliang Xu is an Associate 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.
Ph.D. inElectrical 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
7/2020---present Associate Professor, Tsinghua-Berkeley Shenzhen Institute (TBSI), Shenzhen International Graduate School, Tsinghua University.
9/2017---6/2020 Assistant Professor, Tsinghua-Berkeley Shenzhen Institute (TBSI), Tsinghua University.
9/2015---08/2018 Adjunct Faculty, Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA, USA.
11/2013---2017/08 Associate Professor, SYSU-CMU Joint Institute of Engineering, School of Electronics and Information
Technology Sun Yat-sen University, China
11/2013---08/2014 Visiting Professor, Carnegie Mellon University, Electrical and Computer Engineering, Pittsburgh, PA.
07/2013~10/2013 Research Associate, Penn State University, State College, PA.
05/2011~08/2011 Research Assistant, Siemens Corporate Research, Princeton, NJ.
Senior member of IEEE<br>06/2019~Now IEEE ACCESS (SCI IF: 3.745), Associate Editor <br>03/2020~Now CSEE Journal of Power and Energy Systems (SCI, IF: 3.115), Associate Editor <br>07/2020~Now IET Generation, Transmission & Distribution (IF: SCI 2.862), Associate Editor <br>09/2020~Now IET Renewable Power Generation (SCI, IF: 3.894), Associate Editor <br>08/2020~Now IET Smart Grid, Associate Editor<br>05/2011~08/2011 Research Assistant, Siemens Corporate Research, Princeton, NJ.
学术兼职PROFESSIONAL AFFILIATIONS AND ACTIVITIES
兼职情况AFFILIATIONS AND ACTIVITIES
Power systems optimization, microgrids, renewable energy integration, virtual power plant, artificial intelligence, big data and learning, distributed control and optimization.
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.
Shenzhen Natural Science Foundation, Virtual power plant coordination with the active distribution network in the energy internet environment, 2021/11/01-2024/10/31;
Natural Science Foundation of Guangdong Province, Integrated Energy Operation and trading strategy based on Blockchain, 2021/01/01-2023/12/31;
China Southern Power Grid Scientific Project，Cloud-cluster-end coordinated virtual powerplant optimal operation research, 2021/06/01-2022/12/31;
China Southern Power Grid Scientific Project，Coordinated benefits based distribution network expansion project decision making model and strategy research, 2021/06/01～2022/12/31;
China Southern Power Grid Scientific Project, Power System Optimal Dispatch Based on Source-Network-Load-Storage Coordination,” 08/2017-7/2020;
China Southern Power Grid Scientific Project, Virtual Power Plant and Distribution Network Interaction in Electric Energy and Ancillary Market, 06/2018-9/2020.
研究及教学领域RESEARCH AND TEACHING AREAS
研究领域及专长RESEARCH INTEREST AND EXPERTISE
Shenzhen Natural Science Foundation, Virtual power plant coordination with the active distribution network in the energy
internet environment, 2021/11/01-2024/10/31;
Natural Science Foundation of Guangdong Province, Integrated Energy Operation and trading strategy based on
China Southern Power Grid Scientific Project，Cloud-cluster-end coordinated virtual powerplant optimal operation
China Southern Power Grid Scientific Project，Coordinated benefits based distribution network expansion project decision
making model and strategy research, 2021/06/01～2022/12/31;
China Southern Power Grid Scientific Project, Power System Optimal Dispatch Based on Source-Network-Load-Storage
China Southern Power Grid Scientific Project, Virtual Power Plant and Distribution Network Interaction in Electric Energy
and Ancillary Market, 06/2018-9/2020.
荣誉和奖项HONORS & AWARDS
L. Yang, Y. Xu, Z. Xu, and H. Sun, “Stochastic dispatch for power and gas systems under uncertainties in gas network,”
2020 IEEE Power & Energy Society General Meeting, August 2-6, 2020, Montreal, Canada. (Corresponding author, Best
Distributed control and optimization of power systems, 3 credit, 48 class hours
Computational methods for power systems, 3 credit, 48 class hour
硕士生&博士生指导MASTER'S & PHD ADVISING
成就（包括出版物、专利、特邀报告、演讲等）ACHIEVEMENTS (INCL. PUBLICATIONS,PATENTS, INVITED TALKS, LECTURES, ETC.)
 L. Yang, Y. Xu*, W. Gu, and H. Sun, Distributionally Robust Chance-Constrained Optimal Power-Gas Flow Under Bidirectional Interactions Considering Uncertain Wind Power, IEEE Trans. Smart Grid, vol.12, no.2, pp.1722-1735, 2021.
 X. Chang, Y. Xu*, W. Gu, H. Sun*, M. Chow and Z. Yi, Accelerated Distributed Hybrid Stochastic/Robust Energy Management of Smart Grids, IEEE Transactions on Industrial Informatics, vol. 17, no. 8, pp. 5335-5347, Aug. 2021.
 Z. Yi, Y. Xu*, W. Gu and Z. Fei, Distributed Model Predictive Control Based Secondary Frequency Regulation for a Microgrid with Massive Distributed Resources, IEEE Transactions on Sustainable Energy, vol. 12, no. 2, pp. 1078-1089, April 2021.
 Z. Yi, Y. Xu*, J. Zhou, W. Wu, H. Sun, “Bilevel Programming for Optimal Operation of an Active Distribution Network with Multiple Virtual Power Plants” IEEE Trans. Sustainable Energy, vol. 11, no. 4, pp. 2855-2869, Oct. 2020.
 X. Shi, Y. Xu*, Q. Guo, and H. Sun, A Distributed EV Navigation Strategy Considering the Interaction Between Power System and Traffic Network, IEEE Transactions on Smart Grid. vol. 11, no. 4, pp. 3545-3557, July 2020.
 L. Yang, Y. Xu*, and H. Sun, “A Dynamic Linearization and Convex Relaxation Based Approach for a Natural Gas Optimal Operation Problem.” IEEE Transactions on Smart Grid. vol. 11, no. 2, pp. 1802-1804, March 2020.
 L. Yang, Y. Xu*, H. Sun, and X. Zhao, Two-stage Convexification Based Optimal Electricity-Gas Flow, IEEE Transactions on Smart Grid. vol. 11, no. 2, pp. 1465-1475, March 2020.
 Z. Yi, Y. Xu*, W. Gu and W. Wu, “A multi-time-scale economic scheduling strategy for virtual power plant based on deferrable loads aggregation and disaggregation,” IEEE Trans. Sustainable Energy, vol. 11, no. 3, pp. 1332-1346, July 2020.
 Y. Xu, W. Wu, and J. Zhou*, “A distributed task allocation based on winners-take-all approach for multiple energy storage systems coordination in a microgrid,” IEEE Transactions on Smart Grid. vol. 11, no. 1, pp. 686-695, Jan. 2020.
 Z. Yi, Y. Xu*, Z. Li, “Optimal configuration of distributed heat source to promote the wind power penetration in combined heat and power system,” Journal of Renewable and Sustainable Energy, vol.11, no. 3, pp.1-13.
 Z. Yi, Y. Xu*, J. Hu, M. Chow and H. Sun, Distributed neurodynamic-based approach for economic dispatch in an integrated energy system, IEEE Transactions on Industrial Informatics. vol. 16, no. 4, pp. 2245-2257, April 2020.
 Y. Xu*, H. Sun, and W. Gu, “A novel discounted min-consensus algorithm for optimal electrical power trading in grid-connected DC microgrids” IEEE Transactions on Industrial Electronics, vol. 66, no. 11, pp. 8474-8484, Nov. 2019. (SCI, IF:7.07).
 Y. Xu*, Q. Guo, H Sun, and Z. Fei, “Distributed discrete robust secondary cooperative control for islanded microgrids,” IEEE Trans. Smart Grid, vol. 10, no. 4, pp. 3620-3629, July 2019.
 Y. Xu, W. Zhang*, M. Chow, H. Sun, and J. Peng, “A distributed model-free controller for enhancing the power system frequency transient stability” IEEE Transactions on Industrial Informatics, vol.15, no.3, pp.1361-1371, 2019.
 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, vol. 15, no.1, pp.225-235, 2019.
Yinliang Xu, Wei Zhang, Wenxin Liu and Wen Yu, Distributed Energy Management of Electrical Power System, JOHN
WILEY & SONS, INC.pp:1-235, ISBN: 9781119534884, 2021.
Yinliang Xu, Xiaoying Shi, Hongbin Sun, Electric power trading method, device and storage, issued patent,
出版物与专利PUBLICATIONS & PATENTS
学生和博士后STUDENTS AND POSTDOCS
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