A joint data and knowledge-driven method for power system disturbance localisation

IF 2 4区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Iet Generation Transmission & Distribution Pub Date : 2024-12-05 DOI:10.1049/gtd2.13331
Zikang Li, Jiyang Tian, Hao Liu
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Abstract

Accurate and fast disturbance localisation is critical for taking timely controls to prevent power system instability. With the increased complexity of systems, the physical model-based disturbance localisation is challenging to achieve good performance due to model deficiency. Phasor measurement unit (PMU)-based approaches are developed but their performance has been significantly affected by the number of PMUs. To this end, this article proposes a joint data and knowledge-driven disturbance localisation method. A spatiotemporal graph convolutional network is proposed to effectively capture the spatiotemporal dependence with a limited number of PMU measurements. By integrating the physical constraints of disturbance type-topology information and localisation cost characteristics, a composite constraint loss function is proposed that embed physical knowledge into the data-driven method. This leads to the development of the disturbance localisation method and allows quick identification, improved localisation accuracy, and interpretability of the algorithm. Simulation results carried out on the IEEE 39-bus system and IEEE 118-bus system verify the effectiveness and robustness of the proposed method.

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电力系统扰动定位的数据与知识联合驱动方法
准确、快速的扰动定位是及时控制电力系统不稳定的关键。随着系统复杂性的增加,基于物理模型的干扰定位由于模型的不足而难以获得良好的性能。基于相量测量单元(PMU)的方法得到了发展,但其性能受到PMU数量的显著影响。为此,本文提出了一种数据和知识驱动的扰动联合定位方法。提出了一种时空图卷积网络,利用有限数量的PMU测量值有效捕获时空相关性。通过整合扰动类型拓扑信息和定位代价特征的物理约束,提出了一种将物理知识嵌入到数据驱动方法中的复合约束损失函数。这导致了干扰定位方法的发展,并允许快速识别,提高定位精度和算法的可解释性。在IEEE 39总线系统和IEEE 118总线系统上的仿真结果验证了该方法的有效性和鲁棒性。
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来源期刊
Iet Generation Transmission & Distribution
Iet Generation Transmission & Distribution 工程技术-工程:电子与电气
CiteScore
6.10
自引率
12.00%
发文量
301
审稿时长
5.4 months
期刊介绍: IET Generation, Transmission & Distribution is intended as a forum for the publication and discussion of current practice and future developments in electric power generation, transmission and distribution. Practical papers in which examples of good present practice can be described and disseminated are particularly sought. Papers of high technical merit relying on mathematical arguments and computation will be considered, but authors are asked to relegate, as far as possible, the details of analysis to an appendix. The scope of IET Generation, Transmission & Distribution includes the following: Design of transmission and distribution systems Operation and control of power generation Power system management, planning and economics Power system operation, protection and control Power system measurement and modelling Computer applications and computational intelligence in power flexible AC or DC transmission systems Special Issues. Current Call for papers: Next Generation of Synchrophasor-based Power System Monitoring, Operation and Control - https://digital-library.theiet.org/files/IET_GTD_CFP_NGSPSMOC.pdf
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