DECISION SUPPORT TOOL FOR THE DEVELOPMENT OF POWER DISTRIBUTION NETWORKS BASED ON AI PLANNING

Sandra Castellanos (1, 2, 3) , Marie-Cécile Alvarez-Herault (4) , Philippe Lalanda (1, 3)

1 LIG - Laboratoire d'Informatique de Grenoble
2 G2Elab-EP - G2Elab-Electronique de puissance
3 M-PSI - Multimodal Perception and Sociable Interaction
4 G2ELab - Laboratoire de Génie Electrique de Grenoble

Long-term planning of interconnected electrical distribution networks consists in imagining the evolution of the existing network towards a target network, respecting the objectives and constraints set by the DSO, according to national and local energy evolution scenarios and with a time horizon of several decades. At present, there is no tool that can automatically and optimally propose target networks, as well as the annual intermediate networks that would allow reaching them. Automated planning (AI planning), a sub-field of Artificial Intelligence, is a model-based approach to action selection. The objective of this paper is a first attempt of a decision support tool for DSOs, based on AI planning and electrical computations, to help them finding the aforementioned intermediate networks.

Domaines: Sciences de l'ingénieur [physics]

Sandra Castellanos, Marie-Cécile Alvarez-Herault, Philippe Lalanda. DECISION SUPPORT TOOL FOR THE DEVELOPMENT OF POWER DISTRIBUTION NETWORKS BASED ON AI PLANNING. 27th International Conference on Electricity Distribution (CIRED 2023), Jun 2023, ROME, Italy. ⟨hal-04287537⟩