Multifractal and AI Approaches for Coherent and Resilient Energy Networks in Urban Territories – FRACNET-CITY
Urban areas increasingly face the challenge of integrating renewable energy sources while simultaneously managing the demands of high population density, land spare and resilience to extreme climate events. Traditional urban planning methods often lack the capacity to fully address the intricate, multiscale interconnections within urban systems, such as those between built-up areas, district energy networks, and the impacts of extreme weather events on energy infrastructure. This project Fracnet-city aims to introduce a novel, multiscale framework that leverages multifractal analysis and Artificial Intelligence (AI) to tackle these challenges.
The primary objective is to develop a multifractal-inspired approach for urban planning of physical networks that utilizes AI-driven geospatial analysis and simulation. By applying multifractal analyses, the project will examine and optimize urban layouts, energy distribution networks, in a way that promotes spare land use, renewable energy integration, and increases resilience to extreme weather events. The framework will also include adaptive tools capable of responses to urban dynamics, such as shifts in energy demand, population growth, and climatic changes.
By a collaborative effort between research teams in France and Switzerland, the project brings together expertise in multifractal networks, photovoltaic integration, urban planning, and AI. Through case studies in selected urban areas in France and Switzerland, the project aims to demonstrate the practical application of its framework, showing a more coherent and efficient use of urban space, increased renewable energy integration and improved resilience to extreme climate change. The expected outcomes are an adaptive planning model of urban networks grounded in multifractal and AI principles, comprehensive AI-driven tools for urban planning, and actionable insights for urban territories facing similar challenges globally.
Project coordination
Nicolas Retiere (Laboratoire de Génie Electrique de Grenoble)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
G2Elab Laboratoire de Génie Electrique de Grenoble
Lucerne University of Applied Sciences and Arts
Swiss Federal Laboratories for Materials Science and Technology
LOCIE LabOratoire proCédés énergIe bâtimEnt
ThéMA THEORISER ET MODELISER POUR AMENAGER - UMR 6049
Help of the ANR 519,162 euros
Beginning and duration of the scientific project:
January 2026
- 48 Months