Cyber security and privacy issues in smart grids J Liu, Y Xiao, S Li, W Liang, CLP Chen IEEE Communications Surveys & Tutorials 14 (4), 981-997, 2012 | 713 | 2012 |
Optimal and direct-current vector control of direct-driven PMSG wind turbines S Li, TA Haskew, RP Swatloski, W Gathings IEEE Transactions on power electronics 27 (5), 2325-2337, 2012 | 528 | 2012 |
Using neural networks to estimate wind turbine power generation S Li, DC Wunsch, EA O'Hair, MG Giesselmann IEEE Transactions on energy conversion 16 (3), 276-282, 2001 | 482 | 2001 |
Conventional and novel control designs for direct driven PMSG wind turbines S Li, TA Haskew, L Xu Electric Power Systems Research 80 (3), 328-338, 2010 | 311 | 2010 |
An Optimal and Learning-Based Demand Response and Home Energy Management System D Zhang, S Li, M Sun, Z O'Neill IEEE Transactions on Smart Grid, 2016 | 293 | 2016 |
Dynamic energy management of a microgrid using approximate dynamic programming and deep recurrent neural network learning P Zeng, H Li, H He, S Li IEEE Transactions on Smart Grid 10 (4), 4435-4445, 2018 | 224 | 2018 |
Control of DFIG wind turbine with direct-current vector control configuration S Li, TA Haskew, KA Williams, RP Swatloski IEEE Transactions on sustainable energy 3 (1), 1-11, 2012 | 222 | 2012 |
Control of HVDC light system using conventional and direct current vector control approaches S Li, TA Haskew, L Xu IEEE Transactions on Power Electronics 25 (12), 3106-3118, 2010 | 221 | 2010 |
Control of a Grid-Forming Inverter Based on Sliding-Mode and Mixed Control Z Li, C Zang, P Zeng, H Yu, S Li, J Bian IEEE Transactions on Industrial Electronics 64 (5), 3862-3872, 2017 | 204 | 2017 |
Control of Single-Phase Grid-Connected Inverters with LCL Filters Using Recurrent Neural Network and Conventional Control Methods X Fu, S Li IEEE Transactions on Power Electronics, 2016 | 172 | 2016 |
Comparative analysis of regression and artificial neural network models for wind turbine power curve estimation S Li, DC Wunsch, E O’Hair, MG Giesselmann Journal of Solar Energy Engineering 123 (4), 327-332, 2001 | 172 | 2001 |
Artificial neural networks for control of a grid-connected rectifier/inverter under disturbance, dynamic and power converter switching conditions S Li, M Fairbank, C Johnson, DC Wunsch, E Alonso, JL Proao IEEE transactions on neural networks and learning systems 25 (4), 738-750, 2014 | 171 | 2014 |
Study of battery modeling using mathematical and circuit oriented approaches S Li, B Ke 2011 IEEE Power and Energy Society General Meeting, 1-8, 2011 | 168 | 2011 |
Analysis of decoupled dq vector control in DFIG back-to-back PWM converter S Li, TA Haskew 2007 IEEE Power Engineering Society General Meeting, 1-7, 2007 | 164 | 2007 |
Fully Distributed Hierarchical Control of Parallel Grid-Supporting Inverters in Islanded AC Microgrids Z Li, C Zang, P Zeng, H Yu, S Li IEEE Transactions on Industrial Informatics 14 (2), 679-690, 2018 | 156 | 2018 |
Integrating home energy simulation and dynamic electricity price for demand response study S Li, D Zhang, AB Roget, Z O'Neill IEEE Transactions On Smart Grid 5 (2), 779-788, 2014 | 154 | 2014 |
Training recurrent neural networks with the Levenberg–Marquardt algorithm for optimal control of a grid-connected converter X Fu, S Li, M Fairbank, DC Wunsch, E Alonso IEEE transactions on neural networks and learning systems 26 (9), 1900-1912, 2014 | 141 | 2014 |
Artificial Neural Network for Control and Grid Integration of Residential Solar Photovoltaic Systems Y Sun, S Li, B Lin, X Fu, M Ramezani, I Jaithwa IEEE Transactions on Sustainable Energy 8 (4), 1484-1495, 2017 | 139 | 2017 |
Shading and bypass diode impacts to energy extraction of PV arrays under different converter configurations H Zheng, S Li, R Challoo, J Proano Renewable Energy 68, 58-66, 2014 | 124 | 2014 |
Systems and methods for modeling energy consumption and creating demand response strategies using learning-based approaches S Li, M Sun, D Zhang US Patent 9,817,375, 2017 | 119 | 2017 |