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arXiv · 1911.12001

A Convexification Approach for Small-Signal Stability Constrained Optimal Power Flow

Parikshit Pareek·Hung D. Nguyen
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Abstract

In this paper, a novel convexification approach for Small-Signal Stability Constraint Optimal Power Flow (SSSC-OPF) has been presented that does not rely on eigenvalue analysis. The proposed methodology is based on the sufficient condition for the small-signal stability, developed as a Bilinear Matrix Inequality (BMI), and uses network structure-preserving Differential Algebraic Equation (DAE) modeling of the power system. The proposed formulation is based on Semi-definite Programming (SDP) and objective penalization that has been proposed for feasible solution recovery, making the method computationally efficient for large-scale systems. A vector-norm based objective penalty function has also been proposed for feasible solution recovery while working over large and dense BMIs with matrix variables. An effectiveness study carried out on WECC 9-bus, New England 39-bus, and IEEE 118-bus test systems show that the proposed method is capable of achieving a stable equilibrium point without inflicting a high stability-induced additional cost.

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Parikshit Pareek, Hung D. Nguyen. 2021-09-16. A Convexification Approach for Small-Signal Stability Constrained Optimal Power Flow. https://doi.org/10.1109/tcns.2021.3090205

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