Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/11531/104107
Título : Co-optimizing network investment, reconfiguration, and third-party flexibility for congestion management in active distribution networks
Autor : Valarezo Rivera, Orlando Mauricio
Gómez San Román, Tomás
Chaves Ávila, José Pablo
Mancarella, Pierluigi
Fecha de publicación : 1-nov-2025
Resumen : 
This paper introduces a unified optimization model to evaluate three coordinated strategies for congestion management in distribution networks: investment in new assets, distribution network reconfiguration, and the procurement of third-party flexibility. Unlike existing models that consider these strategies in isolation, the proposed approach jointly optimizes capital and operational expenditures, explicitly capturing their trade-offs. This integrated perspective aligns with evolving regulatory frameworks that advocate for the coordination of conventional planning with operational and market-based flexibility. The model is applied across a range of scenarios, including load growth, varying flexibility capacities and costs, and different weightings of representative days. Results indicate that reconfiguration alone may suffice under moderate demand growth, while greater availability of third-party flexibility can defer or substitute costly grid reinforcements. Under higher congestion conditions, the coordinated deployment of all three strategies delivers the most cost-effective and operationally robust outcomes. The analysis further reveals that grid reconfiguration dynamically alters the eligibility of service providers to deliver flexibility, underscoring the importance of incorporating reconfiguration into the design of third-party flexibility mechanisms and distribution network planning. The paper concludes by identifying key implementation challenges and future research directions, including the selection and weighting of representative days, assessment of switching costs, reliability of reconfigured topologies, uncertainty modeling, and the implications of coordinating multiple flexibility mechanisms for congestion management.
Descripción : Artículos en revistas
URI : https:doi.org10.1016j.ijepes.2025.111094
http://hdl.handle.net/11531/104107
ISSN : 0142-0615
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