Review of Model Predictive Control for Power System With Large-scale Wind Power Grid-connected

被引:0
|
作者
Ye L. [1 ]
Lu P. [1 ]
Zhao Y. [1 ]
Dai B. [1 ]
Tang Y. [2 ]
机构
[1] College of Information and Electrical Engineering, China Agriculture University, Haidian District, Beijing
[2] State Key Laboratory of Power Gird Safety and Energy Conservation, China Electric Power Research Institute, Haidian District, Beijing
基金
中国国家自然科学基金;
关键词
Feedback correction; Model predictive control (MPC); Rolling optimization; Uncertainty modeling;
D O I
10.13334/j.0258-8013.pcsee.202599
中图分类号
学科分类号
摘要
Model predictive control (MPC) was a state-of- the-art optimization algorithm, which had the advantages of compensating for low prediction accuracy, suppressing disturbance and improving robustness by rolling optimization and feedback correction. In recent years, it has become a research hotspot to deal with uncertainty modeling of system integration of large-scale wind power. A comprehensive review of state- of-the-art and new development of the MPC was introduced in the field of wind power control. In particular, stochastic MPC, distributed MPC and robust MPC had been analyzed in-depth to deal with uncertain modeling problems. Taking wind turbine-wind farm-wind farm cluster and thermal power unit active power and frequency control as an example, the advantages and disadvantages of MPC were fully discussed. Further, the decomposition-coordination strategy and solution efficiency of MPC were reviewed. Finally, several key scientific topics of large-scale wind power integration based on MPC were summarized, and the future research direction of MPC was given. © 2021 Chin. Soc. for Elec. Eng.
引用
收藏
页码:6189 / 6197
页数:8
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