Modeling of small-signal stability margin constrained optimal power flow

• A novel SSSM constrained optimal power flow model is proposed. • The analytical representation of the SSSM sensitivities is newly derived. • A joint solution approach is developed to effectively solve the SSSMC-OPF model. • The conflicting relationship between generation cost and SSSM is revealed. This paper presents a novel small-signal stability margin (SSSM) constrained optimal power flow model for generation dispatch to minimize the generation cost while retaining adequate SSSM. The SSSM constraint is described in terms of the total active load variation between an initial operating point and the critical point, which is located on the dynamic performance boundary of small-signal stability. From the existing SSSM model, where the steady-state equation and the small-signal stability equation are taken into account, a modified SSSM model is proposed to reduce the computational requirement. The sensitivity representation of SSSM with respect to operating parameters is newly derived, which makes it possible for the SSSM and steady-state optimization problems to be jointly solved. A joint solution approach is proposed to solve the small-signal stability margin constrained optimal power flow (SSSMC-OPF) model. Simulation results show that the proposed approach can effectively minimize the generation cost subject to retaining a certain level of SSSM. For an 8-machine 24-bus system and a modified practical 68-machine 2395-bus system, the generation costs of SSSMC-OPF are increased by 5.28% and 2.73%, respectively, but the SSSMs are improved by 45% and 14.41%, respectively, compared to the optimal power flow.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2024-10-31
DOI
https://doi.org/10.1016/j.ijepes.2024.110338
Citations
1
Primary Topic
Power System Optimization and Stability
Type
article
Field-Weighted Citation Impact
0.21

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article

Modeling of small-signal stability margin constrained optimal power flow

Jun Liang, Venkata Dinavahi, Zheng Huang, Fushuan Wen et al.
1 citations
International Journal of Electrical Power & Energy Systems
Power System Optimization and Stability
0.21
article

Modeling of small-signal stability margin constrained optimal power flow

Jun Liang, Venkata Dinavahi, Zheng Huang, Fushuan Wen, Kewen Wang, Yi Wang
article en
1 citations

Abstract

• A novel SSSM constrained optimal power flow model is proposed. • The analytical representation of the SSSM sensitivities is newly derived. • A joint solution approach is developed to effectively solve the SSSMC-OPF model. • The conflicting relationship between generation cost and SSSM is revealed. This paper presents a novel small-signal stability margin (SSSM) constrained optimal power flow model for generation dispatch to minimize the generation cost while retaining adequate SSSM. The SSSM constraint is described in terms of the total active load variation between an initial operating point and the critical point, which is located on the dynamic performance boundary of small-signal stability. From the existing SSSM model, where the steady-state equation and the small-signal stability equation are taken into account, a modified SSSM model is proposed to reduce the computational requirement. The sensitivity representation of SSSM with respect to operating parameters is newly derived, which makes it possible for the SSSM and steady-state optimization problems to be jointly solved. A joint solution approach is proposed to solve the small-signal stability margin constrained optimal power flow (SSSMC-OPF) model. Simulation results show that the proposed approach can effectively minimize the generation cost subject to retaining a certain level of SSSM. For an 8-machine 24-bus system and a modified practical 68-machine 2395-bus system, the generation costs of SSSMC-OPF are increased by 5.28% and 2.73%, respectively, but the SSSMs are improved by 45% and 14.41%, respectively, compared to the optimal power flow.

International Journal of Electrical Power & Energy SystemsVol. 162
University of Alberta (CA), Zhengzhou University (CN), Zhejiang University (CN), Cardiff University (GB)
National Natural Science Foundation of China, China Postdoctoral Science Foundation
Affordable and clean energy
Openalex Percentile: Top 47%
Power System Optimization and Stability
0.21
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