Buildings are required to be more and more energy efficient, in order to comply with restrictive requirements of building regulations and energy certifications. Optimisation algorithms have shown to be effective in identifying good solutions for the design of efficient building services. In this article Evolutionary Neural Network Design (ENN-Design) has been adopted to drive the design of a typical façade module for an office building. This application is significant, since façades play a major role in the definition of the energy performance of buildings. Both single-objective and multi-objective optimisations have been carried out. The aim of the article is to introduce an innovative approach for improving the performance of building envelopes by means of a reasonable amount of calculation time.

Optimised design of energy efficient building façades via Evolutionary Neural Networks

M Borrotti;
2011

Abstract

Buildings are required to be more and more energy efficient, in order to comply with restrictive requirements of building regulations and energy certifications. Optimisation algorithms have shown to be effective in identifying good solutions for the design of efficient building services. In this article Evolutionary Neural Network Design (ENN-Design) has been adopted to drive the design of a typical façade module for an office building. This application is significant, since façades play a major role in the definition of the energy performance of buildings. Both single-objective and multi-objective optimisations have been carried out. The aim of the article is to introduce an innovative approach for improving the performance of building envelopes by means of a reasonable amount of calculation time.
2011
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
Energy efficient buildings
Energy optimisation
Multi-objective optimisation
Neural networks
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/252819
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 71
  • ???jsp.display-item.citation.isi??? ND
social impact