Calculation of Theoretical Line Loss of Full-Voltage Power Grid Based on Multi-Source Data Fusion

Fang, Jicheng; Jiong, Ye; Jiang, Wei; Shangxing, Ye; Xie, Yingjie; Lu, Haiqing; Da-wei, Dong; Zhen, Jianfeng

doi:10.1145/3448734.3450869

Cited by 1 publication

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The method of data fusion can improve the accuracy of diagnosis. [16] fuses the data of Micro-PMU and SCADA, and proposes a distribution network state estimation algorithm based on the least squares method of dynamic variable weights to achieve high-precision state estimation, and the effectiveness of the algorithm is verified by tests; [17] A hybrid dynamic estimation algorithm for PMU and SCADA measurements is proposed, and experimental studies show that the hybrid method can improve the estimation to a certain extent; in [18], the slow sampling rate SCADA data and the high sampling rate PMU are fused to the dynamic state of the power system In the estimator, the dynamic tracking of the power system is realized, and the test results prove its availability; [19] uses the fusion method to make the PMU fill the missing SCADA data, and establish a multi-time scale data set for multi-time scale state estimation.…”

Section: Introductionmentioning

confidence: 99%

Power grid fault diagnosis method based on alarm information and PMU fusion

liu¹,

Zheng²,

Zhang³

et al. 2023

Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022)

View full text Add to dashboard Cite

With the rapid development of smart grid technology, more and more attention has been paid to the stability of the power grid. When the power grid fails, the dispatch center will receive various types of data, including the PMU data collected by the PMU (Power Management Unit) device used by the Wide Area Monitoring System (WAMS) and the data collected by the Supervisory Control System for Data Acquisition and Control (SCADA). Alarm information data, they describe the same grid fault from different dimensions. At present, the power grid fault diagnosis based on PMU data and alarm information texts has been fully studied, but the information source is single, and it is difficult to ensure the accuracy of the diagnosis results when complex faults and multiple faults occur in the power grid. This paper starts with the information source of power grid fault diagnosis and develops a power grid fault diagnosis method that integrates the dual data sources of PMU and alarm information: 1. effectively connect alarm message text and PMU based on fault events. 2. complete the fusion of PMU and alarm information to improve the scope and accuracy of power grid fault diagnosis. Finally, the simulation fault data is used to test. The experimental results show that the accuracy of fault diagnosis of dual data source fusion is higher than that of single data.

show abstract