Finite‐time H∞${{H}_\infty }$ fault detection for large‐scale power system via Markov jumping mechanism

Author:

Wang Xunting1,Xu Bin1,Ding Jinjin1,Ren Chengcheng2ORCID,Zhang Qian2ORCID

Affiliation:

1. Electric Power Research Institute State Grid Anhui Electric Power Co., Ltd Hefei China

2. School of Electrical Engineering and Automation Anhui University Hefei China

Abstract

AbstractThis paper investigates the finite‐time fault detection problem for large‐scale power systems via the Markov jumping mechanism subject to unknown disturbances. The novel power system is described by a large‐scale system model, and the residual dynamic properties of unknown input signals and fault signals, including unknown disturbances and modelling errors, are obtained by reconstructing the system. Then, the energy norm indicators of the residual disturbance signal and fault signal are, respectively, selected to reflect their suppression effect on disturbance and sensitivity to faults. Moreover, the design of a fault detection observer is formulated as an optimisation problem. Based on Lyapunov theory and linear matrix inequalities (LMI), sufficient conditions for the designed fault detection observer solutions are given, and an optimisation design method is provided. Finally, the simulation results show that the optimised observer can detect the fault signal effectively and can contain the effect of unknown disturbances on the residuals within a given range when a fault occurs.

Funder

China Postdoctoral Science Foundation

Publisher

Institution of Engineering and Technology (IET)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3