Li Chaoshun
·Paper Publications
- [11] Chaoshun Li*, Yifeng Mao, Jianzhong Zhou, Nan Zhang, Xueli An. Design of a fuzzy-PID controller for a nonlinear hydraulic turbine governing system by using a novel gravitational search algorithm based on Cauchy mutation and mass weighting. Applied Soft Computing, 2017, 52: 290-305.
- [12] Wenxiao Wang, Chaoshun Li*, Xiang Liao, Hui Qin. Study on unit commitment problem considering pumped storage and renewable energy via a novel binary artificial sheep algorithm. Applied Energy, 2017, 187: 612–626.
- [13] Chaoshun Li*, Nan Zhang, Xinjie Lai, Jianzhong Zhou, Yanhe Xu. Design of a fractional order PID controller for a pumped storage unit using a gravitational search algorithm based on the Cauchy and Gaussian mutation. Information Sciences, 2017, 396: 162–181.
- [14] Chaoshun Li*, Yifeng Mao, Jiandong Yang, et al. A nonlinear generalized predictive control for pumped storage unit. Renewable Energy, 2017, 114:945-959 .
- [15] Chaoshun Li*, Zhou J, Chang L, et al. T-S fuzzy model identification based on a novel hyper-plane-shaped membership function. IEEE Transactions on Fuzzy Systems, 2017, 25 (5), 1364-1370.
- [16] Wen Zou, Chaoshun Li*, Nan Zhang. A T-S Fuzzy Model Identification Approach based on a Modified Inter Type-2 FRCM Algorithm. IEEE Transactions on Fuzzy Systems, 2018, 26(3): 1104 – 1113 .
- [17] Chaoshun Li*, Zhengguang Xiao, Xin Xia*, Wen Zou, Chu Zhang. A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting. Applied Energy, 2018,215:131–144.
- [18] Chaoshun Li*, Wenxiao Wang, Deshu Chen. Multi-objective complementary scheduling of Hydro-Thermal-RE power system via a multi-objective hybrid grey wolf optimizer. Energy, 2019, 171: 241-255.
- [19] Xinjie Lai, Chaoshun Li*, Jianzhong Zhou, Nan Zhang. Multi-objective optimization of the closure law of guide vanes for pumped storage units. Renewable Energy, 2019, 139:302-312 .
- [20] Wen Zou, Chaoshun Li*, Pengfei Chen. An Inter Type-2 FCR Algorithm Based T-S Fuzzy Model for Short-term Wind Power Interval Prediction. IEEE Transactions on Industrial Informatics, 2019, 15(9): 4934 – 4943.