IDENTICAL project: Increasing distribution network hosting capacity by means of an innovative application of a smart transformer (with OLTC) combined with electric distribution digital twins
The IDENTICAL (Integral Development of Electrical Network Twins with Innovative Computation and Algorithms) project aims to revolutionize the monitoring and control of electricity distribution networks by developing a comprehensive Digital Twin that addresses current limitations in Low Voltage (LV) and Medium Voltage (MV) networks. While many advancements in grid management have been tested in ideal "living-lab" environments, real-world networks often suffer from significant gaps in topological data and smart meter measurements. The project focuses on three key technological challenges: creating an exact Digital Twin of MV/LV secondary substations (SS), developing an approximate and evolutionary Digital Twin for LV networks using data-driven strategies, and designing algorithms for the efficient operation of smart transformers. Ultimately, IDENTICAL seeks to bridge the gap between current network conditions and smart grid capabilities, providing tools that enhance energy transition goals, operational efficiency, and planning across diverse industries, including electro-intensive sectors.
Authors
- Esther Romero-Ramos (ORCID: https://orcid.org/0000-0002-1873-2723)
- José Antonio Rosendo Macías (ORCID: https://orcid.org/0000-0002-0494-9307)
- Antonio de la Villa Jaén (ORCID: https://orcid.org/0000-0001-6934-1004)
- Ricardo Carmona‐Galán (ORCID: https://orcid.org/0000-0002-4230-3988)
- R.J. Moran
- I. Fernández (ORCID: https://orcid.org/0000-0002-6274-289X)
- Lenin Del Rio Amador (ORCID: https://orcid.org/0000-0003-4043-472X)
- Alena Ulasenka
- Jon Kobeaga
Institutions
- Ayuntamiento de Sevilla (ES)
- Azienda Unita' Sanitaria Locale di Parma (IT)
- Marie Curie (GB)
- Universidad de Sevilla (ES)
Publication Details
- Journal
- IET conference proceedings.
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1049/icp.2025.1627
- Primary Topic
- Power Systems and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.00