Loughborough University
Browse
BS19_Paper_Draft_v.7.pdf (788.34 kB)

Can multi-objective optimisation achieve more resilient outcomes in the UK's social housing sector?

Download (788.34 kB)
conference contribution
posted on 2019-07-01, 12:14 authored by Joe Forde, Christina Hopfe, Rob McLeod, Ralph Evins
The housing crisis within the UK continues with growing private housing rental prices and increasing levels of homelessness. This situation has been driven by the homogeneous development of housing tenures under-supplying in-demand social and affordable homes. Previous work has seen the implementation of multi-objective optimisation within a broad range of building performance simulation software. The present work is novel in the implementation of a multi-objective decision support framework within software used for compliance with the low energy Passivhaus standard. This use of evidence-based decision support could enable local authorities to make better informed decision in relation to large development seeking Passivhaus compliance. Results indicate that different optimal solutions are present depending on the criteria used to meet the standard. This means that it is important to select early in the design process either the heating load, or annual heating demand criteria if optimisation techniques are to be applied based on the Passivhaus certification criteria to the design.

History

School

  • Architecture, Building and Civil Engineering

Published in

Building Simulation 2019

Citation

FORDE, J. ... et al., 2019. Can multi-objective optimisation achieve more resilient outcomes in the UK's social housing sector? Presented at the 16th IBPSA International Conference & Exhibition Building Simulation 2019, Rome, 2-4th Sept.

Publisher

IBPSA

Version

  • AM (Accepted Manuscript)

Acceptance date

2019-05-06

Publication date

2019

Language

  • en

Location

Rome, Italy

Usage metrics

    Loughborough Publications

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC