基于全局滑模的自适应电力系统混沌容错控制

doi:10.19595/j.cnki.1000-6753.tces.221660

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摘要当电力系统参数变动或遭受扰动后,系统极易进入局部混沌振荡状态,局部的功角振荡可能会演化为大范围的系统振荡,最终可能造成系统解列等严重后果。因此,抑制电力系统的局部混沌振荡状态具有重要意义。为抑制七阶系统的混沌状态,增强系统的抗扰能力,采用扩张观测器对系统发电机侧与负荷侧的系统项进行观测,设计了基于全局滑模的容错控制器。该文考虑了发电机侧遭受扰动与负荷侧控制器故障的情况。为减少系统在扰动下的最大偏差与稳态误差,并补偿控制器故障导致的输出幅值损失,设计了基于全局滑模的自适应容错控制器。仿真结果表明,当系统分别遭受传输故障、阶跃扰动及控制器故障时,系统在基于自适应全局滑模的容错控制器的作用下均能有效收敛至目标轨道。

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关键词 ：电力系统, 混沌, 全局滑模, 自适应, 扩张观测器

Abstract：When the power system suffers from external disturbance or the parameters change in a certain range, the power Angle of the system may appear disordered oscillation in a certain range, that is, the system enters a chaotic state. At present, in order to suppress the chaotic state of power system, controllers using various principles have been designed, but the disturbance and controller failure are rarely considered in the design process. To solve this problem, this paper proposes an adaptive fault-tolerant control strategy based on global sliding mode, which makes the system more stable under the action of the controller.
Firstly, according to the characteristics of the seven-dimensional system, the dynamic characteristics of the system under the change of key parameters P₀ and Q₀ are obtained by using the bifurcation diagram and phase diagram. After analysis, it can be seen that when P₀ changes from small to large, the system presents a transition phenomenon from periodic to chaotic state, and when Q₀ changes from small to large, the system presents a transition phenomenon from chaotic to periodic state. Through the analysis of chaotic characteristics, the chaotic state parameters of the system are obtained.
Secondly, in order to solve the problem that the controller could not timely obtain the changes of system items due to the disturbance, an observer was designed to observe the operation characteristics of the synchronous generator rotor and input the observation results to the input end of the controller. This paper proposes a Fault-tolerant control (FTC) strategy based on global sliding mode extended observer. In order to further reduce the fluctuation of the system under the disturbance and consider the possible failure, the method of combining fixed gain and adaptive gain is adopted in the controller. A strategy of adaptive fault-tolerant control (AFTC) based on global sliding mode observer is proposed.
The simulation results show that, under the action of FTC, the state variables of the system converge to the fixed orbit, and the output of the extended observer approximates the system term in finite time. When the system suffers from transmission faults, the stable deviations of δ_m and δ_L from the current orbit and the target orbit are 0.04 and -0.07 under the action of DSMC. Under the action of FTC and AFTC, the maximum deviation of δ_m and δ_L from the target orbit is 0.022 and 0.009, and -0.038 and -0.037, respectively. When the system is subjected to step perturbation, under the action of DSMC, the stability deviation of δ_m to the target orbit after two perturbations is 0.06 and 0.35, respectively. Under the action of FTC and AFTC, δ_m rapidly converges to the original target orbit after deviating from the original orbit, and the maximum deviation from the target orbit is 0.22 and 0.05, respectively. When the system suffers from controller failure, the stability deviation of δ_L to the target orbit is -0.20 under the action of DSMC. Under the action of FTC, the stability deviation of δ_L to the target orbit is -0.16. Under the action of AFTC, δ_L converges to the vicinity of the target orbit again, and the maximum deviation of δ_L to the target orbit is -0.11, and the stability deviation is -0.013.
By analyzing the simulation results, it can be found that all the designed controllers can eliminate the chaotic state of the system, and when the system is subjected to step disturbance, transmission fault and controller fault, the maximum offset and steady-state error of the system are small under the control of AFTC.

Key words： Power system chaos global sliding mode adaptive extended state observer

收稿日期: 2022-08-30

PACS:

TM712

基金资助:国家自然科学基金资助项目（61803233）

通讯作者: 杨洋男,1995年生,硕士,研究方向电力系统运行与控制。E-mail：2534019091@qq.com

作者简介: 于永进男,1980年生,副教授,硕士生导师,研究方向为电力系统运行与控制。E-mail：yaydjto@163.com

引用本文:

于永进, 杨洋. 基于全局滑模的自适应电力系统混沌容错控制[J]. 电工技术学报, 2023, 38(23): 6332-6344. Yu Yongjin, Yang Yang. Chaos Fault-Tolerant Control of Adaptive Power System Based on Global Sliding Mode. Transactions of China Electrotechnical Society, 2023, 38(23): 6332-6344.

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[1] 赵光宙, 齐冬莲. 混沌控制理论及其应用[J]. 电工技术学报, 2001, 16(5): 77-82.
Zhao Guangzhou, Qi Donglian.Chaotic control theory and applications[J]. Transactions of China Electrote-chnical Society, 2001, 16(5): 77-82.
[2] 王宝华, 杨成梧, 张强. 电力系统分岔与混沌研究综述[J]. 电工技术学报, 2005, 20(7): 1-10.
Wang Baohua, Yang Chengwu, Zhang Qiang.Summary of bifurcation and chaos research in electric power system[J]. Transactions of China Electro-technical Society, 2005, 20(7): 1-10.
[3] Kumar A, Anwar M N, Kumar S.Sliding mode controller design for frequency regulation in an interconnected power system[J]. Protection and Control of Modern Power Systems, 2021, 6(1): 6.
[4] 许德智, 黄泊珉, 杨玮林. 神经网络自适应的永磁直线同步电机超扭曲终端滑模控制[J]. 电力系统保护与控制, 2021, 49(13): 64-71.
Xu Dezhi, Huang Bomin, Yang Weilin.Neural network adaptive super twist terminal sliding mode control for a permanent magnet linear synchronous mtor[J]. Power System Protection and Control, 2021, 49(13): 64-71.
[5] 于永进, 王家斌, 王艳. 基于自适应全局滑模的电力系统混沌振荡控制[J]. 电力系统保护与控制, 2019, 47(16): 43-49.
Yu Yongjin, Wang Jiabin, Wang Yan.Chaotic oscillation control in power system based on adaptive total sliding mode[J]. Power System Protection and Control, 2019, 47(16): 43-49.
[6] Ma Caoyuan, Wang Faxin, Li Zhijie, et al.Adaptive fixed-time fast terminal sliding mode control for chaotic oscillation in power system[J]. Mathematical Problems in Engineering, 2018, 2018: 1-10.
[7] 倪骏康, 刘崇新, 庞霞. 电力系统混沌振荡的等效快速终端模糊滑模控制[J]. 物理学报, 2013, 62(19): 190507.
Ni Junkang, Liu Chongxin, Pang Xia.Fuzzy fast terminal sliding mode controller using an equivalent control for chaotic oscillation in power system[J]. Acta Physica Sinica, 2013, 62(19): 190507.
[8] 王家斌, 于永进, 阎振坤, 等. 基于自适应非奇异终端滑模控制的电力系统混沌抑制[J]. 电力系统保护与控制, 2021, 49(7): 120-126.
Wang Jiabin, Yu Yongjin, Yan Zhenkun, et al.Chaotic suppression of a power system based on adaptive non-singular terminal sliding mode control[J]. Power System Protection and Control, 2021, 49(7): 120-126.
[9] 李小腾, 王江彬, 刘崇新, 等. 四阶混沌电力系统的全局快速滑模控制器设计[J]. 科学技术与工程, 2021, 21(24): 10298-10303.
Li Xiaoteng, Wang Jiangbin, Liu Chongxin, et al.Global fast sliding mode controller design for a four-dimensional chaotic power system[J]. Science Technology and Engineering, 2021, 21(24): 10298-10303.
[10] Alrifai M T, Zribi M.Sliding mode control of chaos in a single machine connected to an infinite bus power system[J]. Mathematical Problems in Engineering, 2018, 2018: 1-13.
[11] 王江彬, 刘崇新. 4阶混沌电力系统的协同控制方法[J]. 西安交通大学学报, 2020, 54(1): 26-31.
Wang Jiangbin, Liu Chongxin.Synergetic control method for four-dimensional chaotic power system[J]. Journal of Xi’an Jiaotong University, 2020, 54(1): 26-31.
[12] 杨洋, 于永进, 王云飞. 基于全局滑模时滞的电力系统混沌振荡控制[J]. 电力系统保护与控制, 2021, 49(15): 59-67.
Yang Yang, Yu Yongjin, Wang Yunfei.Power system chaotic oscillation control based on global sliding mode time delay[J]. Power System Protection and Control, 2021, 49(15): 59-67.
[13] Yu Yixin, Jia Hongjie, Li Peng, et al.Power system instability and chaos[J]. Electric Power Systems Research, 2003, 65(3): 187-195.
[14] 王江彬, 刘凌, 刘崇新. 基于扩张状态观测器七阶混沌振荡电力系统的滑模变结构控制[J]. 电工技术学报, 2020, 35(21): 4524-4531.
Wang Jiangbin, Liu Ling, Liu Chongxin.Sliding mode variable structure control for seven-dimensional chaotic power system based on extended state observer[J]. Transactions of China Electrotechnical Society, 2020, 35(21): 4524-4531.
[15] Wang Jiangbin, Liu Ling, Liu Chongxin, et al.Fixed-time synergetic control for a seven-dimensional chaotic power system model[J]. International Journal of Bifurcation and Chaos, 2019, 29(10): 1950130.
[16] Wang Jiangbin, Liu Ling, Liu Chongxin, et al.Adaptive sliding mode control based on equivalence principle and its application to chaos control in a seven-dimensional power system[J]. Mathematical Problems in Engineering, 2020, 2020: 1-13.
[17] Ni Junkang, Liu Ling, Liu Chongxin, et al.Chattering-free time scale separation sliding mode control design with application to power system chaos suppression[J]. Mathematical Problems in Engineering, 2016, 2016: 1-14.
[18] Rajesh K G, Padiyar K R.Bifurcation analysis of a three node power system with detailed models[J]. International Journal of Electrical Power & Energy Systems, 1999, 21(5): 375-393.
[19] Jia H J, Yu Y X, Li P.Relationship of power system chaos and instability modes[J]. Proceedings of the Chinese Society of Electrical Engineering, 2003, 23(2):1-4.
[20] Jia Hongjie, Yu Yixin, Li Peng, et al.Torus bifurcation and chaos in power systems[C]// Proceedings of International Conference on Power System Technology, Kunming, China, 2002: 1717-1722.
[21] 曹学谦, 葛琼璇, 朱进权, 等. 基于积分滑模的高速磁悬浮列车牵引控制策略[J]. 电工技术学报, 2022, 37(14): 3598-3607.
Cao Xueqian, Ge Qiongxuan, Zhu Jinquan, et al.Traction-system research of high-speed maglev train based on integral sliding mode control[J]. Transactions of China Electrotechnical Society, 2022, 37(14): 3598-3607.
[22] 武志涛, 李帅, 程万胜. 基于扩展滑模扰动观测器的永磁直线同步电机定结构滑模位置跟踪控制[J]. 电工技术学报, 2022, 37(10): 2503-2512.
Wu Zhitao, Li Shuai, Cheng Wansheng.Fixed structure sliding mode position tracking control for permanent magnet linear synchronous motor based on extended sliding mode disturbance observer[J]. Transactions of China Electrotechnical Society, 2022, 37(10): 2503-2512.
[23] 魏惠芳, 王丽梅. 永磁直线同步电机自适应模糊神经网络时变滑模控制[J]. 电工技术学报, 2022, 37(4): 861-869.
Wei Huifang, Wang Limei.Adaptive fuzzy neural network time-varying sliding mode control for permanent magnet linear synchronous motor[J]. Transactions of China Electrotechnical Society, 2022, 37(4): 861-869.
[24] 张康, 王丽梅. 基于反馈线性化的永磁直线同步电机自适应动态滑模控制[J]. 电工技术学报, 2021, 36(19): 4016-4024.
Zhang Kang, Wang Limei.Adaptive dynamic sliding mode control of permanent magnet linear synchronous motor based on feedback linearization[J]. Transactions of China Electrotechnical Society, 2021, 36(19): 4016-4024.
[25] 王勃, 王天擎, 于泳, 等. 感应电机电流环非线性积分滑模控制策略[J]. 电工技术学报, 2021, 36(10): 2039-2048.
Wang Bo, Wang Tianqing, Yu Yong, et al.Nonlinear integral sliding mode control strategy for current loop of induction motor drives[J]. Transactions of China Electrotechnical Society, 2021, 36(10): 2039-2048.
[26] 杨挺, 张璐, 张亚健, 等. 基于信息熵计算模型的电力信息物理系统融合控制方法[J]. 电力系统自动化, 2021, 45(12): 65-74.
Yang Ting, Zhang Lu, Zhang Yajian, et al.Fusion control method for cyber-physical power system based on information entropy calculation model[J]. Automation of Electric Power Systems, 2021, 45(12): 65-74.
[27] 韩京清. 自抗扰控制技术: 估计补偿不确定因素的控制技术[M]. 北京: 国防工业出版社, 2008: 197-198.
[28] Feng Y, Bao S, Yu X, Design method of non-singular terminal sliding mode control systems[J]. Control and Decision, 2002(02):194-198.
[29] 刘壮, 郑雪梅, 冯勇, 等. 全阶无抖振非奇异终端滑模控制方法[J]. 控制工程, 2020, 27(5): 824-829.
Liu Zhuang, Zheng Xuemei, Feng Yong, et al.Full-order chattering free non-singular terminal sliding mode control method[J]. Control Engineering of China, 2020, 27(5): 824-829.