Abstract
This paper presents potential techniques for automated analysis of various types of data collected in power systems. Diverse recording devices have been widely deployed in modern power systems, and as a result more data have been obtained. It is necessary to extract useful and actionable information from the captured data. This paper focuses on discussing intelligent techniques for automatically analyzing such data, including disturbance classification, fault events correlation, fault type classification, fault cause identification, fault location, generator monitoring and parameter estimation, incipient fault detection, and line parameter estimation.
| Original language | English |
|---|---|
| Title of host publication | 2012 IEEE Power and Energy Society General Meeting, PES 2012 |
| DOIs | |
| State | Published - 2012 |
| Event | 2012 IEEE Power and Energy Society General Meeting, PES 2012 - San Diego, CA, United States Duration: Jul 22 2012 → Jul 26 2012 |
Publication series
| Name | IEEE Power and Energy Society General Meeting |
|---|---|
| ISSN (Print) | 1944-9925 |
| ISSN (Electronic) | 1944-9933 |
Conference
| Conference | 2012 IEEE Power and Energy Society General Meeting, PES 2012 |
|---|---|
| Country/Territory | United States |
| City | San Diego, CA |
| Period | 7/22/12 → 7/26/12 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Disturbance analysis
- Fault location
- Power quality
- Substation automation
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering
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