Journal article · Ahead of Print article
Design and Implementation of a Data-Driven Approach to Visualizing Power Quality
Shanghai Jiao Tong University1
Harvard University2
Shandong University3
Huazhong University of Science and Technology4
Nanyang Technological University5
Electric Power Systems, Center for Electric Power and Energy, Centers, Technical University of Denmark6
Center for Electric Power and Energy, Centers, Technical University of Denmark7
Department of Electrical Engineering, Technical University of Denmark8
Numerous underlying causes of power-quality (PQ) disturbances have enhanced the application of situational awareness to power systems. This application provides an optimal overall response for contingencies. With measurement data acquired by a multi-source PQ monitoring system, we propose an interactive visualization tool for PQ disturbance data based on a geographic information system (GIS).
This tool demonstrates the spatio–temporal distribution of the PQ disturbance events and the cross-correlation between PQ records and environmental factors, leveraging Getis statistics and random matrix theory. A methodology based on entity matching is also introduced to analyze the underlying causes of PQ disturbance events.
Based on real-world data obtained from an actual power system, offline and online PQ data visualization scenarios are provided to verify the effectiveness and robustness of the proposed framework.
| Language: | English |
|---|---|
| Publisher: | IEEE |
| Year: | 2020 |
| Pages: | 4366-4379 |
| ISSN: | 19493053 and 19493061 |
| Types: | Journal article and Ahead of Print article |
| DOI: | 10.1109/TSG.2020.2985767 |
| ORCIDs: | Wu, Qiuwei , 0000-0002-2198-1843 , 0000-0001-5810-7263 , 0000-0001-6904-1458 , 0000-0002-6229-2470 , 0000-0001-5816-8621 and 0000-0002-8024-2688 |
