Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications

Saldaña-González, Antonio E.; Aragüés-Peñalba, Mònica; Gadelha, Vinicius; Sumper, Andreas

doi:10.3390/en19010116

Open AccessReview

Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications

by

Antonio E. Saldaña-González

^*

,

Mònica Aragüés-Peñalba

,

Vinicius Gadelha

and

Andreas Sumper

Centre d’Innovació Tecnològica en Convertidors Estàtics i Accionaments (CITCEA-UPC), Departament d’Enginyeria Elèctrica, Universitat Politècnica de Catalunya ETS d’Enginyeria Industrial de Barcelona, Avinguda Diagonal, 647, Pl. 2, 08028 Barcelona, Spain

^*

Author to whom correspondence should be addressed.

Energies 2026, 19(1), 116; https://doi.org/10.3390/en19010116

Submission received: 7 November 2025 / Revised: 14 December 2025 / Accepted: 22 December 2025 / Published: 25 December 2025

(This article belongs to the Special Issue AI Facilitated Cyber–Physical Energy Systems—Planning, Operation, and Markets)

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Abstract

Active distribution networks (ADNs) are rapidly evolving with the integration of distributed energy resources, flexible loads, and energy storage systems. Traditional planning methods, based on passive upgrades and worst-case scenarios, are no longer adequate for high DER penetration and dynamic system behavior. This review highlights the key evolution needs that will drive the evolution towards a more dynamic and optimized active distribution planning. Furthermore, this work reviews the core elements in ADN planning, covering time horizons, objectives, decision variables, uncertainty approaches, and optimal power flow formulations. This work also reviews recent generative AI models applied to active distribution networks, presenting a structured classification and definitions of each generative AI category.

Keywords: active distribution network planning; generative AI applications; optimization elements; traditional decision variables; flexible sources; emerging assets

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MDPI and ACS Style

Saldaña-González, A.E.; Aragüés-Peñalba, M.; Gadelha, V.; Sumper, A. Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications. Energies 2026, 19, 116. https://doi.org/10.3390/en19010116

AMA Style

Saldaña-González AE, Aragüés-Peñalba M, Gadelha V, Sumper A. Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications. Energies. 2026; 19(1):116. https://doi.org/10.3390/en19010116

Chicago/Turabian Style

Saldaña-González, Antonio E., Mònica Aragüés-Peñalba, Vinicius Gadelha, and Andreas Sumper. 2026. "Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications" Energies 19, no. 1: 116. https://doi.org/10.3390/en19010116

APA Style

Saldaña-González, A. E., Aragüés-Peñalba, M., Gadelha, V., & Sumper, A. (2026). Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications. Energies, 19(1), 116. https://doi.org/10.3390/en19010116

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

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Review of Active Distribution Network Planning: Elements in Optimization Models and Generative AI Applications

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