摘要 该文研究孤岛交流微电网二次电压和频率的固定时间精确控制问题,基于多智能体一致性方法,提出考虑状态受限的自适应模糊固定时间二次电压控制器和基于控制障碍函数的二次频率控制器。在多智能体一致性控制中,将每一个分布式电源视为一个非线性智能体,智能体之间通过稀疏网络进行通信。在电压控制器设计中,采用反馈线性化后未知变量的自适应模糊估计提高控制器的自适应能力,并引入新的滑模面使电压控制器在固定时间内收敛。考虑到系统状态受限问题,分别采用障碍Lyapunov函数和控制障碍函数设计电压与频率控制器,使系统状态在预设的约束范围内。频率控制器的设计还考虑了有功功率的精确分配问题,给出了严格的固定时间收敛及稳定性证明。在Matlab/Sim Power System环境下,对微电网负载变化及大干扰下的仿真验证了所提控制器的有效性。
Abstract:Microgrid is one of the most effective and flexible means to manage and control the distributed generation. In microgrid control, the convergence rate of closed-loop system is considered as one of the performance indexes of the control system design. Therefore, it is necessary to analyze the influence of the convergence rate in the control system on the system performance. Finite time convergence can make the error converge to zero in a finite time. However, finite time convergence is related to the initial state of the system. In practical application, because the initial state of the system cannot be obtained in advance, so the specific convergence time cannot be obtained. Meanwhile, the state constrained problem is common in real systems. If the constrained condition does not be met in a system, it will cause the security performance of the system to decline, even may make the whole system unstable. In the microgrid, the physical states such as voltage and frequency are usually constrained to a certain extent. For example, the change of bus voltage should not exceed 10% and the change of frequency should not exceed 2%, otherwise it will seriously affect the stable operation of the system. So, in this paper, based on the multi-agent consensus method, an adaptive fuzzy practical fixed time secondary voltage controller considering state constraints and the secondary frequency controller based on control barrier function are proposed. First of all, the microgrid is regarded as a distributed multi-agent system, and each agents communicate with each other through a sparse network. To solve the deviation problem caused by droop control, based on the multi-agent consensus protocol, secondary control is used to adjust the output voltage, frequency and active power. Secondly feedback linearization is applied to the microgrid system, for the system uncertainty and internal disturbance, adaptive fuzzy estimation is designed to improve the adaptive ability of the controller. A new sliding surface is introduced to design the voltage controller, which makes it converge in practical fixed time, so as to accelerate the convergence speed of the system. The fixed time convergence does not depend on the initial state of the system, but only depends on the parameters of the designed controller, which is conducive to the calculation of convergence time. Finally, considering the problem of system state constraints, the barrier Lyapunov function is used to design the voltage controller, so that the system voltage is constrained within the preset range. The fixed time frequency controller is designed based on cooperative control method of consensus protocol and the control barrier function, and the accurate sharing of active power is realized. The following conclusions can be drawn from the simulation analysis: In the case of load variation, impedance line fault and large disturbance, the proposed controller makes the voltage and frequency follow the reference input quickly and accurately in a fixed time, and the adaptive fuzzy system has a good approximation effect on the system uncertainty and internal disturbance. Compared with the traditional secondary control, the maximum errors of voltage and frequency are within the preset constraint range using the proposed controller, which have the ability of state constraint and strong robustness, at the same time the stability of the system is improved.
吴忠强, 程洪强. 考虑状态受限的微电网二次电压与频率固定时间控制[J]. 电工技术学报, 2023, 38(15): 4107-4119.
Wu Zhongqiang, Cheng Hongqiang. Fixed-Time Secondary Voltage and Frequency Control for Microgrid Considering State-Constrained. Transactions of China Electrotechnical Society, 2023, 38(15): 4107-4119.
[1] 王晴, 刘增, 韩鹏程, 等. 基于变流器输出阻抗的直流微电网下垂并联系统振荡机理与稳定边界分析[J].电工技术学报, 2023, 38(8): 2148-2161. Wang Qing, Liu Zeng, Han Pengcheng, et al.Analysis of oscillation mechanism and stability boundary of droop-controlled parallel converters based on output impedances of individual converters in DC microgrids[J]. Transaction of China Electrotechnical Society, 2023, 38(8): 2148-2161. [2] Golsorkhi M S, Shafiee Q, Lu D, et al.Distributed control of low-voltage resistive AC microgrids[J]. IEEE Transactions on Energy Conversion, 2019, 34: 573-584. [3] 黄文焘, 邰能灵, 刘剑青, 等. 微电网多层级协同反时限保护方案[J]. 电工技术学报, 2021, 36(3): 623-633. Huang Wentao, Tai Nengling, Liu Jianqing, et al.Multi-layer collaborative inverse-time protection schemes for microgrids[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 623-633. [4] Bidram A, Davoudi A.Hierarchical structure of microgrids control system[J]. IEEE Transactions on Smart Grid, 2012, 3(4): 1963-1976. [5] Yu Kai, Ai Qian, Wang Shiyi, et al.Analysis and optimization of droop controller for microgrid system based on small-signal dynamic model[J]. IEEE Transactions on Smart Grid, 2016, 7(2): 695-705. [6] Etemadi A H, Davison E J, Iravani R.A generalized decentralized robust control of islanded microgrids[J]. IEEE Transactions on Power Systems, 2014, 29(6): 3102-3113. [7] Liu Baojin, Wu Teng, Liu Zeng, et al.A small-AC-signal injection-based decentralized secondary frequency control for droop-controlled islanded microgrids[J]. IEEE Transactions on Power Electronics, 2020, 35(11): 11634-11651. [8] Li Qiang, Chen Feixiong, Chen Minyou, et al.Agent-based decentralized control method for islanded microgrids[J]. IEEE Transactions on Smart Grid, 2016, 7(2): 637-649. [9] Wu Xiangyu, Shen Chen, Iravani R.A distributed, cooperative frequency and voltage control for microgrids[J]. IEEE Transactions on Smart Grid, 2018, 9(4): 2764-2776. [10] Das A, Shukla A, Shyam A B, et al.A distributed-controlled harmonic virtual impedance loop for AC microgrids[J]. IEEE Transactions on Industrial Electronics, 2021, 68(5): 3949-3961. [11] Wu Xiangyu, Xu Yin, He Jinghan, et al.Pinning-based hierarchical and distributed cooperative control for AC microgrid clusters[J]. IEEE Transactions on Power Electronics, 2020, 35(9): 9865-9885. [12] Xin Huanhai, Zhang Leiqi, Wang Zhen, et al.Control of island AC microgrids using a fully distributed approach[J]. IEEE Transactions on Smart Grid, 2015, 6(2): 943-945. [13] Amoateng D O, Al Hosani M, Elmoursi M S, et al.Adaptive voltage and frequency control of islanded multi-microgrids[J]. IEEE Transactions on Power Systems, 2018, 33(4): 4454-4465. [14] Dehkordi N M, Sadati N, Hamzeh M.Distributed robust finite-time secondary voltage and frequency control of islanded microgrids[J]. IEEE Transactions on Power Systems, 2017, 32(5): 3648-3659. [15] Pilloni A, Pisano A, Usai E.Robust finite-time frequency and voltage restoration of inverter-based microgrids via sliding-mode cooperative control[J]. IEEE Transactions on Industrial Electronics, 2018, 65(1): 907-917. [16] Zuo Shan, Davoudi A, Song Yongduan, et al.Distributed finite-time voltage and frequency restoration in islanded AC microgrids[J]. IEEE Transactions on Industrial Electronics, 2016, 63(10): 5988-5997. [17] Riverso S, Sarzo F, Ferrari-Trecate G.Plug-and-play voltage and frequency control of islanded microgrids with meshed topology[J]. IEEE Transactions on Smart Grid, 2015, 6(3): 1176-1184. [18] Yan Huaicheng, Zhou Xuping, Zhang Hao, et al.A novel sliding mode estimation for microgrid control with communication time delays[J]. IEEE Transactions on Smart Grid, 2019, 10(2): 1509-1520. [19] Ge Pudong, Dou Xiaobo, Quan Xiangjun, et al.Extended-state-observer-based distributed robust secondary voltage and frequency control for an autonomous microgrid[J]. IEEE Transactions on Sustainable Energy, 2020, 11(1): 195-205. [20] Ge Pudong, Zhu Yue, Green T C, et al.Resilient secondary voltage control of islanded microgrids: an ESKBF-based distributed fast terminal sliding mode control approach[J]. IEEE Transactions on Power Systems, 2021, 36(2): 1059-1070. [21] Dong Xiaogang, Gan Jinqiang, Wu Hao, et al.Self-triggered model predictive control of AC microgrids with physical and communication state constraints[J]. Energies, 2022, 15(3): 1170. [22] Chu Zhongda, Zhang Ning, Teng Fei.Frequency-constrained resilient scheduling of microgrid: a distributionally robust approach[J]. IEEE Tran-sactions on Smart Grid, 2021, 12(6): 4914-4925. [23] 米阳, 蔡杭谊, 宋元元, 等. 基于同步补偿的孤岛微电网无功均分研究[J]. 电工技术学报, 2019, 34(9): 1934-1943. Mi Yang, Cai Hangyi, Song Yuanyuan, et al.Study on reactive power sharing of island microgrid based on synchronous compensation[J]. Transactions of China Electrotechnical Society, 2019, 34(9): 1934-1943. [24] 陈子聪, 王林, 刘建圻, 等. 带输入饱和的不确定非线性系统自适应模糊触发式补偿控制[J]. 控制与决策, 2021, 36(12): 3007-3014. Chen Zicong, Wang Lin, Liu Jianqi, et al.Adaptive fuzzy trigger compensation control for uncertain nonlinear system with input saturation[J]. Control and Decision, 2021, 36(12): 3007-3014. [25] 陈刚, 李志勇, 韦梦立. 孤岛微电网的分布式固定时间二次协调控制[J]. 控制与决策, 2019, 34(1): 205-212. Chen Gang, Li Zhiyong, Wei Mengli.Distributed fixed-time secondary coordination control of islanded microgrids[J]. Control and Decision, 2019, 34(1): 205-212. [26] Chen Ming, Wang Huanqing, Liu Xiaoping.Adaptive practical fixed-time tracking control with prescribed boundary constraints[J]. IEEE Transactions on Circuits and Systems I: Regular Papers, 2021, 68(4): 1716-1726. [27] Zuo Shan, Ali Beg O, Lewis F L, et al.Resilient networked AC microgrids under unbounded cyber attacks[J]. IEEE Transactions on Smart Grid, 2020, 11(5): 3785-3794. [28] 肖湘宁, 王鹏, 陈萌. 基于分布式多代理系统的孤岛微电网二次电压控制策略[J]. 电工技术学报, 2018, 33(8): 1894-1902. Xiao Xiangning, Wang Peng, Chen Meng.Secondary voltage control in an islanded microgrid based on distributed multi-agent system[J]. Transactions of China Electrotechnical Society, 2018, 33(8): 1894-1902. [29] Abhinav S, Schizas I D, Ferrese F, et al.Optimization-based AC microgrid synchronization[J]. IEEE Transactions on Industrial Informatics, 2017, 13(5): 2339-2349. [30] Xu Bin, Shi Zhongke, Sun Fuchun, et al.Barrier Lyapunov function based learning control of hypersonic flight vehicle with AOA constraint and actuator faults[J]. IEEE Transactions on Cybernetics, 2019, 49(3): 1047-1057. [31] Fuentes-Aguilar R Q, Chairez I. Adaptive tracking control of state constraint systems based on differential neural networks: a barrier Lyapunov function approach[J]. IEEE Transactions on Neural Networks and Learning Systems, 2020, 31(12): 5390-5401. [32] 孙伟, 方昭, 杨建平, 等. 考虑随机时变延时的孤岛微电网分布式二次控制[J]. 中国电机工程学报, 2022, 42(3): 864-875. Sun Wei, Fang Zhao, Yang Jianping, et al.Distributed secondary control of islanded microgrid with stochastic time-varying delay[J]. Proceedings of the CSEE, 2022, 42(3): 864-875.