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Autori principali: Larroux, Ginevra, Jacobs, Matthieu, Jia, Keyu, Sossan, Fabrizio, Paolone, Mario
Natura: Preprint
Pubblicazione: 2026
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Accesso online:https://arxiv.org/abs/2603.04189
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author Larroux, Ginevra
Jacobs, Matthieu
Jia, Keyu
Sossan, Fabrizio
Paolone, Mario
author_facet Larroux, Ginevra
Jacobs, Matthieu
Jia, Keyu
Sossan, Fabrizio
Paolone, Mario
contents This work presents a general framework for the operationally driven optimal siting and sizing of battery energy storage systems in power transmission networks, aimed at enhancing their resource adequacy. The approach considers multi-period planning horizons, enforces network constraints at high temporal resolution, and targets large-scale meshed systems. The resulting computationally complex mixed-integer non-linear programming problem is reformulated as a mixed-integer second-order cone programming problem and solved via Generalized Benders Decomposition, with feasibility cuts enabling congestion management and voltage regulation under binding network limits. A tailored heuristic recovers an alternating-current power-flow-feasible operating point from the relaxed solution. The proposed formulation is parallelizable, yielding excellent computational performance, while featuring rigorous guarantees of convergence.
format Preprint
id arxiv_https___arxiv_org_abs_2603_04189
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Enhancing Power Systems Transmission Adequacy via Optimal BESS Siting and Sizing using Benders Decomposition with Feasibility Cuts
Larroux, Ginevra
Jacobs, Matthieu
Jia, Keyu
Sossan, Fabrizio
Paolone, Mario
Systems and Control
This work presents a general framework for the operationally driven optimal siting and sizing of battery energy storage systems in power transmission networks, aimed at enhancing their resource adequacy. The approach considers multi-period planning horizons, enforces network constraints at high temporal resolution, and targets large-scale meshed systems. The resulting computationally complex mixed-integer non-linear programming problem is reformulated as a mixed-integer second-order cone programming problem and solved via Generalized Benders Decomposition, with feasibility cuts enabling congestion management and voltage regulation under binding network limits. A tailored heuristic recovers an alternating-current power-flow-feasible operating point from the relaxed solution. The proposed formulation is parallelizable, yielding excellent computational performance, while featuring rigorous guarantees of convergence.
title Enhancing Power Systems Transmission Adequacy via Optimal BESS Siting and Sizing using Benders Decomposition with Feasibility Cuts
topic Systems and Control
url https://arxiv.org/abs/2603.04189