Abstract
The inertia of a power grid plays a significant role in maintaining the stability of a system. If the inertia is large enough, stable operating conditions can be maintained during small scale events. As the percentage of power supplied by renewable energy sources increases, the value of inertia in a system will decrease. Therefore, it has become necessary to accurately estimate the inertia in the system. Traditional methods of estimating the inertia make use of fault conditions to allow for the dynamics in the system to be accurately observable. However, this is not optimal as fault conditions are infrequent and undesirable. The method detailed makes use of modal information which can be obtained via synchrophasor measurements to estimate the inertia during steady-state conditions. The results show that while the estimation is not accurate for individual buses, the values calculated for regional and system inertias are more accurate.
Original language | English |
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Title of host publication | 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 |
Publisher | IEEE Computer Society |
Pages | 1-5 |
Number of pages | 5 |
ISBN (Electronic) | 9781538622124 |
DOIs | |
Publication status | Published - 2018 Jan 29 |
Event | 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 - Chicago, United States Duration: 2017 Jul 16 → 2017 Jul 20 |
Publication series
Name | IEEE Power and Energy Society General Meeting |
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Volume | 2018-January |
ISSN (Print) | 1944-9925 |
ISSN (Electronic) | 1944-9933 |
Other
Other | 2017 IEEE Power and Energy Society General Meeting, PESGM 2017 |
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Country/Territory | United States |
City | Chicago |
Period | 17/7/16 → 17/7/20 |
Bibliographical note
Publisher Copyright:© 2017 IEEE.
Keywords
- Modal Information
- Neural Networks
- Parameter Estimation
- Wide Area Measurements
ASJC Scopus subject areas
- Energy Engineering and Power Technology
- Nuclear Energy and Engineering
- Renewable Energy, Sustainability and the Environment
- Electrical and Electronic Engineering