A Novel Optimal Power Flow Method Considering Interval Uncertainties Under High Renewable Penetration Based on Security Limits Definition

This paper proposes an optimal power flow method considering interval uncertainties (OPFIU) to enhance the security and economy of power systems with high renewable energy penetration. The OPFIU incorporates bi-level interval power flow (BIPF) equations, security and operation constraints, and active power balance across two extreme renewable output scenarios. Firstly, a dynamic-balance optimization scenario method (DOSM) is proposed to solve the BIPF within the OPFIU. The BIPF involves multiple generators in dynamically balancing the system's active power, thus reducing the conservatism prevalent in existing interval power flow methods. Next, based on the BIPF results, an adaptive security limits definition method (ASLDM) is presented to convert the OPFIU model into a deterministic optimal power flow model, making it more tractable for solution. The ASLDM not only improves the solution efficiency and convergence of existing interval optimization methods, but also provides enhanced reliability in maintaining transmission power within operational limits across a broad spectrum of uncertainty scenarios. Moreover, the ASLDM, unlike robust optimization methods that require convexification of nonlinear AC power flow equations, partially avoids potential issues such as accuracy degradation or solution infeasibility resulting from model simplifications. The Simulation results, compared with robust optimization and chance-constrained programming methods, demonstrate that the proposed ASLDM improves both solution efficiency and convergence in solving the OPFIU problem.

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Publication Details

Journal
IEEE Transactions on Sustainable Energy
Published
2025-08-25
DOI
https://doi.org/10.1109/tste.2025.3602456
Citations
15
Primary Topic
Optimal Power Flow Distribution
Type
article
Field-Weighted Citation Impact
10.96
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article

A Novel Optimal Power Flow Method Considering Interval Uncertainties Under High Renewable Penetration Based on Security Limits Definition

Bin Zhou, Quan Zhou, Lili He, Lipeng Zhu et al.
15 citations
IEEE Transactions on Sustainable Energy
Optimal Power Flow Distribution
10.96
article

A Novel Optimal Power Flow Method Considering Interval Uncertainties Under High Renewable Penetration Based on Security Limits Definition

Bin Zhou, Quan Zhou, Lili He, Lipeng Zhu, Jiayong Li, Zhikang Shuai, Wei Zhang, Cong Zhang, Ke Zhou, Dapeng Wang
article en
15 citations

Abstract

This paper proposes an optimal power flow method considering interval uncertainties (OPFIU) to enhance the security and economy of power systems with high renewable energy penetration. The OPFIU incorporates bi-level interval power flow (BIPF) equations, security and operation constraints, and active power balance across two extreme renewable output scenarios. Firstly, a dynamic-balance optimization scenario method (DOSM) is proposed to solve the BIPF within the OPFIU. The BIPF involves multiple generators in dynamically balancing the system's active power, thus reducing the conservatism prevalent in existing interval power flow methods. Next, based on the BIPF results, an adaptive security limits definition method (ASLDM) is presented to convert the OPFIU model into a deterministic optimal power flow model, making it more tractable for solution. The ASLDM not only improves the solution efficiency and convergence of existing interval optimization methods, but also provides enhanced reliability in maintaining transmission power within operational limits across a broad spectrum of uncertainty scenarios. Moreover, the ASLDM, unlike robust optimization methods that require convexification of nonlinear AC power flow equations, partially avoids potential issues such as accuracy degradation or solution infeasibility resulting from model simplifications. The Simulation results, compared with robust optimization and chance-constrained programming methods, demonstrate that the proposed ASLDM improves both solution efficiency and convergence in solving the OPFIU problem.

IEEE Transactions on Sustainable EnergyVol. 17(2)
Hunan University (CN)
Affordable and clean energy
Openalex Percentile: Top 1%
Optimal Power Flow Distribution
10.96
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