Optimizing Architectural and Structural Aspects of Buildings towards Higher Energy Efficiency

Álvaro Fialho 1 Youssef Hamadi 1, 2, 3 Marc Schoenauer 2, 4
4 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
Abstract : In this on-going work, we aim at contributing to the issue of energy consumption by proposing tools to automatically define some aspects of the architectural and structural design of buildings. Our framework starts with a building design, and automatically optimizes it, providing to the architect many variations that minimize, in different ways, both energy consumption and construction costs. The optimization stage is done by the combination of an energy consumption simulation program, EnergyPlus, with a state-of-the-art multi-objective evolutionary algorithm, Hype. The latter explores the design search space, automatically generating new feasible design solutions, which are then evaluated by the energy simulation software. Preliminary results are presented, in which the proposed framework is used to optimize the orientation angle of a given commercial building and the materials used for the thermal insulation of its walls.
Document type :
Conference papers
Complete list of metadatas

Cited literature [10 references]  Display  Hide  Download

https://hal.inria.fr/inria-00591930
Contributor : Álvaro Fialho <>
Submitted on : Tuesday, May 10, 2011 - 3:07:37 PM
Last modification on : Wednesday, March 27, 2019 - 4:41:27 PM
Long-term archiving on: Friday, November 9, 2012 - 11:02:00 AM

File

wk1303b-fialho.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : inria-00591930, version 1

Collections

Citation

Álvaro Fialho, Youssef Hamadi, Marc Schoenauer. Optimizing Architectural and Structural Aspects of Buildings towards Higher Energy Efficiency. GECCO 2011 Workshop on GreenIT Evolutionary Computation, Jul 2011, Dublin, Ireland. ⟨inria-00591930⟩

Share

Metrics

Record views

484

Files downloads

1196