Distributed adaptive anti-disturbance control for power systems based on multi-agents

被引：0
|
作者：
Shi T. [1 ]
Chen L. [1 ]
Li T. [1 ]
Jin F. [1 ]
机构：
[1] School of Aircraft Engineering, Nanchang Hangkong University, Nanchang
来源：
Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2024年 / 50卷 / 05期
基金：
中国国家自然科学基金;
关键词：
multi-agents; neural network; nonlinear disturbance observer; transient power system; transient stability;
D O I：
10.13700/j.bh.1001-5965.2022.0496
中图分类号：
学科分类号：
摘要：
In response to problems like the inevitable nonlinearities, uncertainties and dynamic external disturbances in multi-machine power systems, a distributed adaptive anti-disturbance control scheme is proposed based on radial basis function neural networks (RBFNN) and nonlinear disturbance observers (NDO) to enhance transient stability and robustness. The unknown nonlinearities of the system are approximated by RBFNN, and NDO are designed based on the output of RBFNNs to estimate the compounded disturbances on-line. A novel distributed adaptive anti-disturbance control scheme for multi-machine power systems is developed with multi-agents' framework, which can receive real-time data measured by communication networks, and control the action of energy storage devices. The speed synchronization of each motor is guaranteed in the presence of external disturbances, and the stability of the closed-loop system is proven based on the Lyapunov stability theory. The simulation results verify the effectiveness of the proposed scheme. © 2024 Beijing University of Aeronautics and Astronautics (BUAA). All rights reserved.
引用
收藏
页码：1685 / 1692
页数：7
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