Adaptive memory event-triggered load frequency control for multiarea power systems with non-ideal communication channel

被引：0
作者：
Qian, Wei [1 ,2 ]
Lu, Di [2 ]
Wu, Yanmin [2 ]
机构：
[1] School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo
[2] Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Henan Polytechnic University, Jiaozuo
来源：
Electric Power Systems Research | 2025年 / 245卷
基金：
中国国家自然科学基金;
关键词：
Adaptive memory event-triggered (AMET) mechanism; Load frequency control (LFC); Multiarea power systems; Non-ideal communication channel;
D O I：
10.1016/j.epsr.2025.111596
中图分类号：
学科分类号：
摘要：
This paper deals with the load frequency control (LFC) issue for multi-area power systems with non-ideal communication channel based on adaptive memory event-triggered (AMET) mechanism. Firstly, by considering frequency regulation resources such as wind turbines, solar power generation, and electric vehicles, a novel power system model is established. Secondly, to effectively reduce the utilization of limited network resources form sensor to the controller, an AMET mechanism is proposed, which allows for flexible updating of the event-triggered threshold in accordance with the current sampling information and historical data, so as to improve the data transmission rate at the vertex of system response curve and achieve better control performance. Then, in view of the complexity of the actual communication network environment, a non-ideal communication channel incorporating communication delays and fading measurements, which respectively characterized by Bernoulli random variables and time-varying random processes is embraced in the LFC mathematical model. By the aid of Lyapunov theory, the asymptotic mean-square stability of the LFC system under a given H∞ performance index is proved. Finally, two simulation cases are presented to demonstrate the effectiveness of the proposed control strategy. © 2025
引用
收藏
相关论文
共 39 条
  • [1] Zhang B., Dou C., Yue D., Park J.H., Xie X., Yuan D., Zhang Z., Transmission and decision-making co-design for active support of region frequency regulation through distribution network-side resources, IEEE Trans. Circuits Syst. I. Regul. Pap., 70, 10, pp. 4204-4217, (2023)
  • [2] Lu J., Hu J., Yu J., Cao J., A dynamic demand response control strategy for isolated microgrid with primary frequency regulation, Electr. Power Syst. Res., 224, (2023)
  • [3] Xiahou K.S., Liu Y., Wu Q.H., Robust load frequency control of power systems against random time-delay attacks, IEEE Trans. Smart Grid, 12, 1, pp. 909-911, (2021)
  • [4] Mu C., Tang Y., He H., Improved sliding mode design for load frequency control of power system integrated an adaptive learning strategy, IEEE Trans. Ind. Electron., 64, 8, pp. 6742-6751, (2017)
  • [5] Shan Y., Hu J., Shen B., Distributed secondary frequency control for AC microgrids using load power forecasting based on artificial neural network, IEEE Trans. Ind. Informatics, 20, 2, pp. 1651-1662, (2024)
  • [6] Shangguan X.C., Zhang C.K., He Y., Jin L., Jiang L., Spencer J.W., Wu M., Robust load frequency control for power system considering transmission delay and sampling period, IEEE Trans. Ind. Informatics, 17, 8, pp. 5292-5303, (2021)
  • [7] Zhou J., Jia Y., Yong P., Liu Z., Sun C., Robust deep koopman model predictive load frequency control of interconnected power systems, Electr. Power Syst. Res., 226, (2024)
  • [8] Kim H., Zhu M., Lian J., Distributed robust adaptive frequency control of power systems with dynamic loads, IEEE Trans. Autom. Control, 65, 11, pp. 4887-4894, (2020)
  • [9] Li X., Ye D., Security-based event-triggered fuzzy control for multiarea power systems under cross-layer DoS attacks, IEEE Trans. Circuits Syst. I. Regul. Pap., 70, 7, pp. 2995-3004, (2023)
  • [10] Peng C., Zhang J., Yan H., Adaptive event-triggering H<sub>∞</sub> load frequency control for network-based power systems, IEEE Trans. Ind. Electron., 65, 2, pp. 1685-1694, (2018)
1234