Backstepping Control Based Coordinated Control of Aggregated Thermostatically Controlled Load and Generator Excitation

被引：0
|
作者：
Yu Y. [1 ]
Lu J. [1 ]
Xie R. [1 ]
Mi Z. [2 ]
Jia Y. [2 ]
Zhang R. [3 ]
机构：
[1] Key Laboratory of Distributed Energy Storage and Microgrid of Hebei Province (North China Electric Power University), Baoding
[2] State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources (North China Electric Power University), Baoding
[3] State Grid Shijiazhuang Electric Power Supply Company, Shijiazhuang
来源：
Dianli Xitong Zidonghua/Automation of Electric Power Systems | 2019年 / 43卷 / 16期
关键词：
Aggregated thermostatically controlled loads (TCLs); Backstepping control; Coordinated controller; Generator excitation; Multi-index control;
D O I：
10.7500/AEPS20181126001
中图分类号：
学科分类号：
摘要：
Coordinated control of thermostatically controlled loads (TCLs) with energy storage characteristic and generator excitation enables to achieve multi-index regulation of power angle, frequency and voltage in power system. Firstly, the descriptions of bi-linear aggregated TCLs model and generator excitation model are integrated to derive an overall mathematical model. Then, based on backstepping control theory, the control strategy coordinated aggregated TCLs with generator excitation is proposed, and the stability of the controller is proved in theory. In allusion to the problem of "calculation explosion" in the design of the controller, a hyperbolic tangent based nonlinear differential tracker is devised to estimate the differential reference value of excitation voltage that reduces the calculation work. Finally, the control algorithm is verified by various cases, and the simulation results show that power angle, frequency and voltage of the system enable to track their references rapidly and correctly with the aid of the proposed coordinated controller. In comparison with the power system stabilizer in traditional excitation control, dynamic responses of state parameters through the controller are improved effectively and the stability of the system is enhanced with the participation of TCLs. © 2019 Automation of Electric Power Systems Press.
引用
收藏
页码：101 / 108and124
相关论文
共 26 条
  • [1] Cen B., Huang Y., Liao Q., Et al., Low frequency load shedding strategy based on frequency influence factors, Automation of Electric Power Systems, 40, 11, pp. 61-67, (2016)
  • [2] Su J., Guo Y., Liu M., Et al., Temperature control load control strategy and probability model for emergency load shedding measures, Power System Technology, 42, 3, pp. 911-918, (2018)
  • [3] Shen Y., Li Y., Gao C., Et al., Application of demand response in ancillary service market, Automation of Electric Power Systems, 41, 22, pp. 151-161, (2017)
  • [4] Yu Y., Mi Z., Zheng X., Et al., Accommodation of curtailed wind power by electric water heaters based on a new hybrid prediction approach, Journal of Modern Power Systems and Clean Energy, 7, 3, pp. 525-537, (2019)
  • [5] Wang K., Yao J., Yao L., Et al., Survey of research on flexible loads scheduling technologies, Automation of Electric Power Systems, 38, 20, pp. 127-135, (2014)
  • [6] Rabl A., Parameter estimation in buildings: methods for dynamic analysis of measured energy use, Journal of Solar Energy Engineering, 110, 1, pp. 52-66, (1988)
  • [7] Malhame R., Chong C.Y., Electric load model synthesis by diffusion approximation of a high-order hybrid-states to stochastic system, IEEE Transactions on Automatic Control, 30, 9, pp. 854-860, (1985)
  • [8] Liu M., Liang W., Zhang Y., Et al., Numerical inverse Laplace transform solving method of thermostatically controlled load group's Fokker-Planck equation aggregation model, Power System Protection and Control, 45, 23, pp. 17-23, (2017)
  • [9] Mathieu J.L., Koch S., Callaway D.S., State estimation and control of electric loads to manage real-time energy imbalance, IEEE Transactions on Power Systems, 28, 1, pp. 430-440, (2013)
  • [10] Wang L., Yang Q., Yan W., Residential thermostatically controlled appliances for smoothing tie line power based on multiple state-queueing model, IEEE Control and Decision Conference, (2017)
123