文章摘要
基于高维随机矩阵的系统状态评估方法研究
Research on Method of System Condition Assessment Base on Large Dimensional Random Matrices
投稿时间:2017-02-06  修订日期:2017-09-11
DOI:
中文关键词: 高维随机矩阵  马尔琴科-帕斯图定理  单环定理  状态评估
英文关键词: large dimensional random matrices  Marchenko-Pastur law  single-ring law  condition assessment
基金项目:面向电能贸易结算的电子式互感器计量运行态势多维度分析及风险评估研究
作者单位E-mail
程含渺 国网江苏省电力公司电力科学研究院 690918372@qq.com 
李红斌 华中科技大学  
徐晴 国网江苏省电力公司电力科学研究院  
纪峰 国网江苏省电力公司电力科学研究院  
陈刚 国网江苏省电力公司电力科学研究院  
田正其 国网江苏省电力公司电力科学研究院  
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中文摘要:
      介绍了高维随机矩阵数学基础,重点是马尔琴科-帕斯图定理和单环定理。阐述了高维随机矩阵应用于状态评估的一般性方法,包括适用性条件、矩阵构造方法以及状态评估指标,讨论了单环定理的具体编程步骤。举例了两个应用场景,分别是电力设备状态评估和电网运行状态评估。仿真结果表明,高维随机矩阵可用于评估系统状态,通过状态评估指标能有效反映出电力设备的健康状态和电网运行的故障状态。
英文摘要:
      Mathematics foundation is introduced, and the key points are Marchenko-Pastur Law and Single-ring Law. General method of applying large dimensional random matrices theory to condition assessment is conducted, including application condition, matrices construction method, and assessment indexes; and the specific programing steps of single-ring law are also discussed. Finally, two application scenarios are taken as examples, respectively are electrical equipment condition assessment and power gird condition assessment. The simulation results indicate that large dimensional random matrices theory is able to be applied to assess the status of a complex system, the health status of electrical equipment and the fault operation status of power grids shall be reflected through the assessment indexes.
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