Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150726
Title: A convexification approach for small-signal stability constrained optimal power flow
Authors: Pareek, Parikshit
Nguyen, Hung Dinh
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2021
Source: Pareek, P. & Nguyen, H. D. (2021). A convexification approach for small-signal stability constrained optimal power flow. IEEE Transactions On Control of Network Systems. https://dx.doi.org/10.1109/TCNS.2021.3090205
Project: 2019-T1-001-119 (RG 79/19)
EMA-EP004- EKJGC-0003
Journal: IEEE Transactions on Control of Network Systems 
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.
URI: https://hdl.handle.net/10356/150726
ISSN: 2325-5870
DOI: 10.1109/TCNS.2021.3090205
Rights: © 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCNS.2021.3090205.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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