Long-term Power Grid Planning via Answer Set Programming

Fuente: arXiv
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Auteurs principaux: Ielo, Antonio, Doria, Francesco, Castellanos-Paez, Sandra, Maratea, Marco, Percassi, Francesco, Vallati, Mauro
Format: Preprint
Publié: 2026
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author Ielo, Antonio
Doria, Francesco
Castellanos-Paez, Sandra
Maratea, Marco
Percassi, Francesco
Vallati, Mauro
author_facet Ielo, Antonio
Doria, Francesco
Castellanos-Paez, Sandra
Maratea, Marco
Percassi, Francesco
Vallati, Mauro
contents The Power grid is a critical infrastructure underpinning all aspects of modern society and its services. Maintaining its effectiveness requires continuous adaptations. In particular, addressing sustainability targets, demand patterns, and urbanisation trends requires implementing changes to the network. Actual developments can potentially span over a decade, with supply continuity and service quality that must be preserved throughout by ensuring conformance to several topological and combinatorial invariants. Long-term power grid planning deals with the above process, and although planning languages could be a natural choice, the kind of properties and invariants needed are cumbersome to express in such languages; on the contrary, they can be elegantly and succinctly encoded in Answer Set Programming (ASP). In this paper, we propose the first approach to automate and optimise the long-term power grid planning process using ASP. Experimental evaluations conducted on synthetic and real-world grid data confirm the expressive power of the proposed ASP-based approach and demonstrate its effectiveness.
format Preprint
id arxiv_https___arxiv_org_abs_2605_20172
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Long-term Power Grid Planning via Answer Set Programming
Ielo, Antonio
Doria, Francesco
Castellanos-Paez, Sandra
Maratea, Marco
Percassi, Francesco
Vallati, Mauro
Logic in Computer Science
Artificial Intelligence
The Power grid is a critical infrastructure underpinning all aspects of modern society and its services. Maintaining its effectiveness requires continuous adaptations. In particular, addressing sustainability targets, demand patterns, and urbanisation trends requires implementing changes to the network. Actual developments can potentially span over a decade, with supply continuity and service quality that must be preserved throughout by ensuring conformance to several topological and combinatorial invariants. Long-term power grid planning deals with the above process, and although planning languages could be a natural choice, the kind of properties and invariants needed are cumbersome to express in such languages; on the contrary, they can be elegantly and succinctly encoded in Answer Set Programming (ASP). In this paper, we propose the first approach to automate and optimise the long-term power grid planning process using ASP. Experimental evaluations conducted on synthetic and real-world grid data confirm the expressive power of the proposed ASP-based approach and demonstrate its effectiveness.
title Long-term Power Grid Planning via Answer Set Programming
topic Logic in Computer Science
Artificial Intelligence
url https://arxiv.org/abs/2605.20172