A Novel Sequential Framework for Transmission Network Expansion Planning: Benders Decomposition Preceding Semidefinite Programming

The transmission network expansion planning (TNEP) problem is inherently complex because of its nonlinear and nonconvex nature, arising from the inclusion of AC power flow constraints, discrete investment decisions, and multiple operating scenarios. These characteristics make the problem computationally challenging, particulary when scaling to larger systems with multistage planning horizons. Addressing this complexity requires advanced methodologies that balance the solution accuracy and computational efficiency. This paper presents a novel two-step framework for TNEP that first applies Benders decomposition to separate investment and operational decisions, followed by semidefinite linearization to reformulate the operational subproblems. The proposed approach enhances the solution quality by ensuring convexity in the subproblems and improves computational efficiency through decomposition. Numerical results for 6- , 10-, and 24-bus test systems demonstrate that the proposed method achieves superior performance compared to existing approaches in terms of solution accuracy and computational efficiency.

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Published
2025-06-29
DOI
https://doi.org/10.1109/powertech59965.2025.11180559
Primary Topic
Advanced MIMO Systems Optimization
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article
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article

A Novel Sequential Framework for Transmission Network Expansion Planning: Benders Decomposition Preceding Semidefinite Programming

Hanane Dagdougui, Dalal Asber, Hussein Suprême, Elmira Fathipasandideh
Advanced MIMO Systems Optimization
article

A Novel Sequential Framework for Transmission Network Expansion Planning: Benders Decomposition Preceding Semidefinite Programming

Hanane Dagdougui, Dalal Asber, Hussein Suprême, Elmira Fathipasandideh
article en

Abstract

The transmission network expansion planning (TNEP) problem is inherently complex because of its nonlinear and nonconvex nature, arising from the inclusion of AC power flow constraints, discrete investment decisions, and multiple operating scenarios. These characteristics make the problem computationally challenging, particulary when scaling to larger systems with multistage planning horizons. Addressing this complexity requires advanced methodologies that balance the solution accuracy and computational efficiency. This paper presents a novel two-step framework for TNEP that first applies Benders decomposition to separate investment and operational decisions, followed by semidefinite linearization to reformulate the operational subproblems. The proposed approach enhances the solution quality by ensuring convexity in the subproblems and improves computational efficiency through decomposition. Numerical results for 6- , 10-, and 24-bus test systems demonstrate that the proposed method achieves superior performance compared to existing approaches in terms of solution accuracy and computational efficiency.

Polytechnique Montréal (CA), Hydro-Québec (CA)
Openalex Percentile: Top 72%
Advanced MIMO Systems Optimization
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