PowerFactory-Python based assessment of frequency and transient stability in power systems dominated by power electronic interfaced generation

Conference Paper (2018)
Author(s)

Jorge Mola Jimenez (Student TU Delft)

Jose L. Rueda (TU Delft - Intelligent Electrical Power Grids)

A.D. Perilla Guerra (TU Delft - Intelligent Electrical Power Grids)

Da Wang (TU Delft - Intelligent Electrical Power Grids)

Peter Palensky (TU Delft - Intelligent Electrical Power Grids)

Mart van der van der Meijden (TenneT TSO B.V.)

Research Group
Intelligent Electrical Power Grids
Copyright
© 2018 Jorge Mola Jimenez, José L. Rueda, A.D. Perilla Guerra, D. Wang, P. Palensky, M.A.M.M. van der Meijden
DOI related publication
https://doi.org/10.1109/MSCPES.2018.8405403
More Info
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Publication Year
2018
Language
English
Copyright
© 2018 Jorge Mola Jimenez, José L. Rueda, A.D. Perilla Guerra, D. Wang, P. Palensky, M.A.M.M. van der Meijden
Research Group
Intelligent Electrical Power Grids
Pages (from-to)
1-6
ISBN (print)
978-1-5386-4103-3
ISBN (electronic)
978-1-5386-4105-7
Reuse Rights

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Abstract

The deployment of variable renewable energy based power plants is increasing all over the world, however, unlike conventional power plants these are mostly connected to the grid via power electronic interfaces. High penetration of power electronic interfaced generation (PEIG) has an important impact on the inertia of the system, which is of major concern for frequency and large disturbance rotor angle (transient) stability. Therefore, it is desirable to study the effectiveness of widely used approaches to assess the stability of a system with high penetration of PEIG. This paper concerns with the modelling and control aspects of a power system for the evaluation of the most widely used metrics (indicators) to assess the dynamics of the power system related to frequency and rotor angle stability. The functionalities of Python are used to automate the generation of operational scenarios, the execution of time domain simulations, and the extraction of signal records to compute the aforesaid indicators. The paper also provides a discussion about possible improvements in the application of these indicators in monitoring tasks.

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