A power grid topology detection method based on edge graph attention neural network

IF 3.3 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Electric Power Systems Research Pub Date : 2024-11-19 DOI:10.1016/j.epsr.2024.111219

Chunxia Zhao , Xueping Li , Yao Cai

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引用次数: 0

Abstract

Against the backdrop of growing power demand and market liberalization, operators optimize power transmission and system load balance through network reconfiguration by switching lines. However, the complex node connections and dynamic load variations exceed the capabilities of traditional algorithms, and data noise may cause detection errors, affecting grid dispatch and stability. To address this issue, a solution is proposed based on the Edge Graph Attention Neural Network (EGAT) model, providing an in-depth analysis of the reconfigured grid structure. The model employs a multi-head attention mechanism to integrate node and edge features from different layers, enhancing feature fusion and extracting critical topological information, thereby improving the accuracy and robustness of grid topology detection after reconfiguration. The method was tested on IEEE 14-bus, IEEE 39-bus, and IEEE 118-bus systems, achieving detection accuracies of 92.30 %, 90.14 %, and 87.25 %, respectively, significantly outperforming other neural network methods. However, the complexity of the model may result in additional computational overhead.

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基于边缘图关注神经网络的电网拓扑检测方法

在电力需求增长和市场自由化的背景下，运营商通过切换线路重新配置网络来优化电力传输和系统负载平衡。然而，复杂的节点连接和动态负荷变化超出了传统算法的能力范围，而且数据噪声可能导致检测错误，影响电网调度和稳定性。针对这一问题，我们提出了一种基于边缘图注意力神经网络（EGAT）模型的解决方案，对重新配置后的电网结构进行深入分析。该模型采用多头关注机制，整合不同层的节点和边缘特征，加强特征融合，提取关键拓扑信息，从而提高重构后电网拓扑检测的准确性和鲁棒性。该方法在 IEEE 14 总线、IEEE 39 总线和 IEEE 118 总线系统上进行了测试，检测精度分别达到 92.30%、90.14% 和 87.25%，明显优于其他神经网络方法。然而，模型的复杂性可能会导致额外的计算开销。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Electric Power Systems Research 工程技术-工程：电子与电气

CiteScore

7.50

自引率

17.90%

发文量

963

审稿时长

3.8 months

期刊介绍： Electric Power Systems Research is an international medium for the publication of original papers concerned with the generation, transmission, distribution and utilization of electrical energy. The journal aims at presenting important results of work in this field, whether in the form of applied research, development of new procedures or components, orginal application of existing knowledge or new designapproaches. The scope of Electric Power Systems Research is broad, encompassing all aspects of electric power systems. The following list of topics is not intended to be exhaustive, but rather to indicate topics that fall within the journal purview. • Generation techniques ranging from advances in conventional electromechanical methods, through nuclear power generation, to renewable energy generation. • Transmission, spanning the broad area from UHV (ac and dc) to network operation and protection, line routing and design. • Substation work: equipment design, protection and control systems. • Distribution techniques, equipment development, and smart grids. • The utilization area from energy efficiency to distributed load levelling techniques. • Systems studies including control techniques, planning, optimization methods, stability, security assessment and insulation coordination.