An Approach to Solve Transient Stability-Constrained Optimal Power Flow Problem Using Support Vector Machines

The Transient Stability-Constrained Optimal Power Flow (TSC-OPF) is a challenging optimization problem, and is the subject of several recent researches. This paper proposes a novel approach to solve TSC-OPF. In the proposed framework, Support Vector Machines (SVMs) are used to classify whether an op...

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Bibliographic Details
Published inElectric power components and systems Vol. 45; no. 6; pp. 624 - 632
Main Authors Nguyen-Duc, Huy, Tran-Hoai, Linh, Cao-Duc, Huy
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 03.04.2017
Taylor & Francis Ltd
Subjects
Classification
computational intelligence
Contingency
Optimal Power Flow
Optimization
Power flow
power system dynamics
power system optimization
power system stability
Security
Solvers
Strategy
Support Vector Machines
Systems stability
Vibration
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Summary:The Transient Stability-Constrained Optimal Power Flow (TSC-OPF) is a challenging optimization problem, and is the subject of several recent researches. This paper proposes a novel approach to solve TSC-OPF. In the proposed framework, Support Vector Machines (SVMs) are used to classify whether an operating condition satisfies predefined transient contingencies. A novel classification strategy is proposed to ensure the optimal solution satisfies all considered contingencies with certain security margin. Besides, the weight coefficients of the SVM are used as sensitivity measures in order to help optimization solver find solutions more effectively. The proposed approach is demonstrated for the New England system and the IEEE 300 bus system.
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ISSN:1532-5008
1532-5016
DOI:10.1080/15325008.2017.1292328