Advances in Transient Stability-Constrained Optimal Power Flow of Power Systems

Hang Zhang; Yan Xu; Zhao Yang Dong

doi:10.17775/CSEEJPES.2024.07270

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Advances in Transient Stability-Constrained Optimal Power Flow of Power Systems

Special Issue Commemorating the 10<sup>th</sup> Anniversary of CSEE Journal of Power and Energy Systems | 更新时间：2026-10-16

- Advances in Transient Stability-Constrained Optimal Power Flow of Power Systems
- CSEE Journal of Power and Energy Systems Vol. 11, Issue 6, Pages: 2776-2793(2025)
- 作者机构：
  
  1. Center for Power Engineering, School of Electrical and Electronic Engineering, Nanyang Technological University,Singapore
  2. Department of Electrical Engineering, City University of Hong Kong,Hong Kong,SAR,China
- 作者简介：
- 基金信息：
- DOI：10.17775/CSEEJPES.2024.07270
  CLC：
- Published：01 November 2025
- 稿件说明：
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Hang Zhang, Yan Xu, Zhao Yang Dong. Advances in Transient Stability-Constrained Optimal Power Flow of Power Systems[J]. CSEE Journal of Power and Energy Systems, 2025, 11(6): 2776-2793.
DOI：

Hang Zhang, Yan Xu, Zhao Yang Dong. Advances in Transient Stability-Constrained Optimal Power Flow of Power Systems[J]. CSEE Journal of Power and Energy Systems, 2025, 11(6): 2776-2793. DOI： 10.17775/CSEEJPES.2024.07270.

摘要

Abstract

Transient stability-constrained optimal power flow (TSCOPF) optimizes power flow while ensuring stability against potential contingencies. The main challenges faced by TSCOPF are the handling of transient constraints. The differential equations of the dynamic process and the inherent nonlinearity of power systems make modeling and solving them difficult. Currently

four methods are employed in TSCOPF: discretization methods

sequential methods

heuristic methods

and machine learning methods. The paper summarizes the latest literature review of these methods

including transient stability criteria

handling of stability constraints

computation flowcharts

advantages

and limitations. Moreover

as power systems rapidly advance

the discussion focuses on how they adapt to new elements and challenges. In conclusion

the existing research gap and future directions are presented.

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