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Regular Paper | Open Access

Impact of Converter Losses in Optimal Power Flow for Hybrid AC-DC Networks Based on Power Routers

Vinicius Gadelha( )Andreas SumperEduard Bullich-Massagué
Centre d’Innovació Tec-nològica en Convertidors Estàtics i Accionaments (CITCEA), inside the Departament d’Enginyeria Elèctrica, Universitat Politècnica de Catalunya. ETS d’Enginyeria Industrial de Barcelona, Barcelona 08028, Spain
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Abstract

The increasing prevalence of distributed energy resources and storage systems requires the future power grid to be flexible, reliable, and capable of seamlessly interfacing with multiple networks. To meet these requirements, authors have proposed a highly controllable network design based on power routers, named the power router grid. A convex Optimal Power Flow (OPF) specifically designed for use on power router grids has recently been developed. This paper enhances this formulation by introducing a set of linear constraints that describe the internal losses of power routers based on a modular multilevel converter model. Additionally, the OPF formulation is expanded in order to consider AC and DC network integration. An investigation of the effects of converter losses in the power router grid operation revealed that power router losses accounted for between 18.2% and 25.6% of the total losses. Furthermore, a comparative analysis between the power router grid and a traditional network assessed whether the power router grid's benefits outweigh the added converter losses. Results indicate that, despite the added converter losses, the power router grid is more efficient than a traditional network in most scenarios, particularly when loads with low power factors are considered.

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CSEE Journal of Power and Energy Systems
Pages 813-824

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Cite this article:
Gadelha V, Sumper A, Bullich-Massagué E. Impact of Converter Losses in Optimal Power Flow for Hybrid AC-DC Networks Based on Power Routers. CSEE Journal of Power and Energy Systems, 2026, 12(2): 813-824. https://doi.org/10.17775/CSEEJPES.2024.05650

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Received: 25 July 2024
Revised: 03 December 2024
Accepted: 14 January 2025
Published: 16 May 2025
© 2024 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).