| 基于随机矩阵理论的配电网状态分析与故障定位 |
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| 引用本文：梁宇镔1,张耀宇1,谭家祺1,叶蓓1,关家华1,王聃2,马恒瑞3.基于随机矩阵理论的配电网状态分析与故障定位[J].电网与清洁能源,2021,37(3):65~70 |
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| 基金项目:国家自然科学基金项目（51777142， 51907096）；青海省自然科学基金项目（2019-ZJ-950Q）。 |
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| 中文摘要:随着智能电网的建设和发展，配电网的状态数据量正以指数级速度增长，面对这种发展趋势，传统的以假设和简化为前提的模型法不再适用，而以数据为驱动的随机矩阵理论方法体现出强大的优势。介绍了随机矩阵理论，包括M-P律和单环定理；概述了高维随机矩阵的构建方法以及在实际工程应用中采用滑动时间窗进行数据采样的理论基础；给出了以节点电压幅值为状态量、以单环定理和方差谱半径作为状态评估指标，对电网状态进行分析和故障区域定位的具体思路；以新英格兰10机39节点网络仿真数据为模型，验证了所用方法的有效性。仿真结果表明，高维随机矩阵适用于电网状态的评估，通过单环定理和方差谱半径能有效反映电网的运行状态以及定位电网的故障区域。 |
| 中文关键词:随机矩阵理论 状态分析 单环定理 方差谱半径 故障区域定位 |
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| State Analysis and Fault Location of Distribution Networks Based on Random Matrix Theory |
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| Abstract:With the development of smart grid construction， the state data of distribution networks is increasing at an exponential speed. In the face of this development trend， the traditional model method based on the premise of hypothesis and simplification is no longer applicable， but the data-driven random matrix theory method shows strong advantages. In this paper， the random matrix theory， including m-p law and single ring theorem， is introduced and the methods of constructing high dimensional random matrix and the theoretical basis of using sliding time window for data sampling in the practical engineering application are summarized. The specific idea of analyzing the state of the power grid and locating the fault area is given， in which the nodal voltage amplitude is taken as the state quantity， the single loop theorem and the variance spectrum radius as the state evaluation indexes. The simulation data of the New England 10-machine 39-node network is used as a model to verify the effectiveness of the proposed method. The simulation results show that the high dimensional random matrix is suitable for the evaluation of power grid state and can effectively reflect the operation state of the power grid and locate the fault area through the single loop theorem and variance spectrum radius. |
| keywords:random matrix theory state analysis single ring theorem variance spectral radius fault area location |
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