Distributed frequency control based on two-dimensional cloud model considering response for thermostatically controlled loads

被引:0
|
作者
Xiang L.-J. [1 ]
Chen H. [1 ]
Nie Z.-Y. [1 ]
机构
[1] College of Information Science and Engineering, Huaqiao University, Fujian, Xiamen
来源
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2022年 / 39卷 / 10期
基金
中国国家自然科学基金;
关键词
distributed control; fractional-order PID; multi-area power systems; thermostatically controlled loads; two-dimensional cloud model;
D O I
10.7641/CTA.2022.10938
中图分类号
学科分类号
摘要
In order to improve the frequency stability of power system and fully use the demand-side controllable load resources, the paper proposes a distributed frequency control method based on two-dimensional cloud model considering the response for thermostatically controlled loads. The load frequency control model of multi-area interconnected power systems is established, and a distributed control strategy of thermostatically controlled loads based on Fokker-Planck equations is designed. Meanwhile, the cloud model algorithm and fractional calculus theory are adopted, a distributed fractional-order PID frequency controller based on two-dimensional cloud model is designed. Finally, through control simulation comparison and analysis, it is demonstrated that the proposed integrated control method has better dynamic and steady-state performance in different operation scenarios. The results show that the control method is feasible and effective. © 2022 South China University of Technology. All rights reserved.
引用
收藏
页码:1825 / 1835
页数:10
相关论文
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  • [1] YU Yang, QUAN Li, JIA Yulong, Et al., Improved model predictive control of aggregated thermostatically controlled load for power fluctuation suppression of new energy, Electric Power Automation Equipment, 41, 3, pp. 92-99, (2021)
  • [2] JIA Hongjie, MU Yunfei, HOU Kai, Et al., Morphology evolution and operation regulation of urban energy system from perspective of energy transition, Automation of Electric Power Systems, 45, 16, pp. 49-62, (2021)
  • [3] LI Cuiping, DONG Zhemin, LI Junhui, Et al., Control strategy of voltage regulation for distributed energy storage cluster in distribution network, Automation of Electric Power Systems, 45, 4, pp. 133-141, (2021)
  • [4] CHEN Laijun, WANG Yuyang, ZHENG Tianwen, Et al., Consensus-based distributed control for parallel-connected virtual synchronous generator, Control Theory & Applications, 34, 8, pp. 1084-1091, (2017)
  • [5] TANG Zhen, WANG Bing, LIU Weiyang, Et al., Distributed control of offshore wind turbine group with input delay, Control Theory & Applications, 37, 12, pp. 2581-2590, (2020)
  • [6] ZHANG Yi, LIU Xiangjie, Robust distributed model predictive control for load frequency control of uncertain power systems, Control Theory & Applications, 33, 5, pp. 621-630, (2016)
  • [7] TAN Wen, ZHOU Hong, FU Caifen, Linear active disturbance rejection control for load frequency control of power systems, Control Theory & Applications, 30, 12, pp. 1580-1588, (2013)
  • [8] MI Yang, HAO Xuezhi, LIU Hongye, Et al., Multi-area power system with wind power and energy storage system load frequency control based on sliding model control, Control and Decision, 34, 2, pp. 437-444, (2019)
  • [9] CHEN Shiming, LU Jiasheng, GAO Yanli, Neural network-based distributed adaptive control for power system transient stability, Control and Decision, 36, 6, pp. 1407-1414, (2021)
  • [10] XIONG Linyun, WANG Jie, Study of load frequency control for three-area time-delayed power system, Power System Technology, 42, 3, pp. 894-902, (2018)