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Title: Online Estimation of Power System Inertia Using Dynamic Regressor Extension and Mixing
Authors: Schiffer, Johannes 
Aristidou, Petros 
Ortega, Romeo 
Major Field of Science: Engineering and Technology
Field Category: ENGINEERING AND TECHNOLOGY;Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Power system stability;Parameter estimation;Power system inertia;Low-inertia systems;Power system dynamics
Issue Date: 1-Nov-2019
Source: IEEE Transactions on Power Systems,2019, vol. 34, no. 6, pp. 4993-5001
Volume: 34
Issue: 6
Start page: 4993
End page: 5001
Journal: IEEE Transactions on Power Systems 
Abstract: The increasing penetration of power-electronic-interfaced devices is expected to have a significant effect on the overall system inertia and a crucial impact on the system dynamics. In future, the reduction of inertia will have drastic consequences on protection and real-time control and will play a crucial role in the system operation. Therefore, in a highly deregulated and uncertain environment, it is necessary for transmission system operators to be able to monitor the system inertia in real time. We address this problem by developing and validating an online inertia estimation algorithm. The estimator is derived using the recently proposed dynamic regressor and mixing procedure. The performance of the estimator is demonstrated via several test cases using the 1013-machine ENTSO-E dynamic model.
ISSN: 0885-8950
DOI: 10.1109/TPWRS.2019.2915249
Rights: © IEEE
Type: Article
Affiliation : University of Leeds 
Brandenburg University of Technology 
French National Centre for Scientific Research 
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