Enhancing rotor angle stability of reconfigured transmission networks

Transmission network planners use switching to address a variety of issues, one of which is short circuit currents that exceed the capability of transmission substations. Transmission Switching (TS) can influence rotor angle transient stability (RATS). The alteration of the short-circuit power at points of interconnection of certain generators (POIs) due to switching can cause those generators to lose stability post-clearance of severe network faults. Therefore, it is imperative that RATS be taken into account when adopt switching in transmission networks. In the literature, analyses of generator angle separation only during and after fault incidence are used for predicting RATS issues. This can be quite challenging for network operators in terms of the available time for carrying out mitigating actions. Generation redispatch, among other measures, can be utilized to preserve RATS post-network switching. In previous work, the authors addressed the optimization of transmission network switching using steady state analysis as an inexpensive way to manage increased short circuit currents amid large-scale generation integration in some networks. This paper is the sequel of the previous work where the preservation of RATS amid such switching actions is addressed. An algorithm for preserving RATS after switching is proposed. The algorithm depends on the MATLAB regression learner that identifies the best heuristic technique for a solution with the least root mean square error (RMSE). PSS®E is utilized to run the simulations on a real-size practical extra-high voltage network. The results are then fed to the MATLAB regression learner, which identifies the relation between the impedance seen by each generator and the altered setpoints (e.g., generator dispatch). The algorithm therefore provides sufficient time for network operators to react to expected RATS issues since it anticipates these issues before fault events occur. Additionally, this algorithm enhances the industry-based software used for transient security assessment because it eliminates the need to run all the network contingencies every time if the relation between the impedance and the setpoints is kept within desirable values.

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Publication Details

Journal
Ain Shams Engineering Journal
Published
2025-03-01
DOI
https://doi.org/10.1016/j.asej.2025.103329
Primary Topic
Power System Optimization and Stability
Type
article
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article

Enhancing rotor angle stability of reconfigured transmission networks

Almoataz Y. Abdelaziz, Mahmoud A. Attia, Mohamed Zakaria Kamh, Ahmed Amin
Ain Shams Engineering Journal
Power System Optimization and Stability
article

Enhancing rotor angle stability of reconfigured transmission networks

Almoataz Y. Abdelaziz, Mahmoud A. Attia, Mohamed Zakaria Kamh, Ahmed Amin
article en

Abstract

Transmission network planners use switching to address a variety of issues, one of which is short circuit currents that exceed the capability of transmission substations. Transmission Switching (TS) can influence rotor angle transient stability (RATS). The alteration of the short-circuit power at points of interconnection of certain generators (POIs) due to switching can cause those generators to lose stability post-clearance of severe network faults. Therefore, it is imperative that RATS be taken into account when adopt switching in transmission networks. In the literature, analyses of generator angle separation only during and after fault incidence are used for predicting RATS issues. This can be quite challenging for network operators in terms of the available time for carrying out mitigating actions. Generation redispatch, among other measures, can be utilized to preserve RATS post-network switching. In previous work, the authors addressed the optimization of transmission network switching using steady state analysis as an inexpensive way to manage increased short circuit currents amid large-scale generation integration in some networks. This paper is the sequel of the previous work where the preservation of RATS amid such switching actions is addressed. An algorithm for preserving RATS after switching is proposed. The algorithm depends on the MATLAB regression learner that identifies the best heuristic technique for a solution with the least root mean square error (RMSE). PSS®E is utilized to run the simulations on a real-size practical extra-high voltage network. The results are then fed to the MATLAB regression learner, which identifies the relation between the impedance seen by each generator and the altered setpoints (e.g., generator dispatch). The algorithm therefore provides sufficient time for network operators to react to expected RATS issues since it anticipates these issues before fault events occur. Additionally, this algorithm enhances the industry-based software used for transient security assessment because it eliminates the need to run all the network contingencies every time if the relation between the impedance and the setpoints is kept within desirable values.

Ain Shams Engineering JournalVol. 16(4)
Ain Shams University (EG), Future University in Egypt (EG)
Affordable and clean energy
Openalex Percentile: Top 97%
Power System Optimization and Stability
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