A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond
A Survey of Power System State Estimation Using Multiple Data Sources: PMUs, SCADA, AMI, and Beyond
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DOI：
10.1109/tsg.2023.3286401
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发表时间：
2024-01
影响因子：
9.6
通讯作者：
Gang Cheng;Yuzhang Lin;A. Abur;A. Gómez-Expósito;Wenchuan Wu
中科院分区：
文献类型：
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作者：
Gang Cheng;Yuzhang Lin;A. Abur;A. Gómez-Expósito;Wenchuan Wu
状态估计对于电力系统的态势感知是必不可少的。传统的SE由从监控和数据采集（SCADA）系统收集的测量值提供。近年来，随着相量测量单元（PMU）、高级计量基础设施（AMI）、智能电子设备（IED）等的部署，可用数据源已大大丰富。多个数据源的集成为增强SE的性能提供了前所未有的机会，但也提出了要解决的主要挑战，包括最佳的多类型传感器共置，多个报告率和计量、不同类型的测量量、测量之间的相关性、在线和历史数据源的集成以及系统和测量的不确定性。本文概述了国家的艺术和研究机会，在这一领域提供了一个全面的文献综述和广泛的讨论。它首先提出的动机和挑战，其次是现有的数据源，在电力系统SE的总结。随后，传输系统（静态和动态）和配电系统SE，现有的方法进行了系统的审查和分类的基础上解决的挑战。还研究了在SE中使用新测量的有趣尝试。最后，本文对剩余的研究空白和未来的研究方向进行了详细的讨论。
State estimation (SE) is indispensable for the situational awareness of power systems. Conventional SE is fed by measurements collected from the supervisory control and data acquisition (SCADA) system. In recent years, available data sources have been greatly enriched with the deployment of phasor measurement units (PMUs), advanced metering infrastructure (AMI), intelligent electronic devices (IEDs), etc. The integration of multiple data sources provides unprecedented opportunities for enhancing the performance of SE, but also presents major challenges to resolve, including optimal multi-type-sensor co-placement, multiple reporting rates and asynchronization, diverse types of measured quantities, correlations between measurements, integration of online and historical data sources, and system and measurement uncertainties. This paper outlines the state of the art and research opportunities in this area by providing a comprehensive literature review and extensive discussions. It starts by presenting the motivations and challenges, followed by a summary of existing data sources for SE in power systems. Subsequently, for both transmission system (static and dynamic) and distribution system SE, existing methods are systematically reviewed and categorized based on the addressed challenges. Interesting attempts of using novel measurements in SE are also studied. Finally, the paper concludes by providing a detailed discussion on the remaining research gaps and future research directions to be explored.