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Temporal optimization for affordable and resilient Passivhaus dwellings in the social housing sector

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journal contribution
posted on 06.01.2020, 11:12 by Joe Forde, Christina Hopfe, Rob McLeod, Ralph Evins
Scarcity of affordable energy efficient dwellings is a defining characteristic of the global housing crisis. In many countries this problem has been exacerbated by single objective cost-models which favour the homogeneous development of market tenures at the expense of delivering high-quality affordable homes. Despite the obvious environmental and fuel-poverty alleviation benefits of advanced energy performance standards, such as Passivhaus, they are often dismissed as an affordable housing solution due to elevated build-cost premiums. The present work attempts to reconcile this housing affordability – energy performance nexus by establishing a novel decision support framework for Passivhaus design using genetic multiobjective optimization. The use of constrained genetic algorithms coupled to the Passive House Planning Package software is shown to produce cost optimal designs which are fully compliant with the Passivhaus standard. The findings also reveal that the precise choice of Passivhaus certification criteria has significant impacts on overheating risks using future probabilistic climate data. This means that the design implications of using either the peak heating load or annual heating demand certification criteria must be temporally evaluated to ensure resilient whole-life design outcomes. In a typical UK context, the findings show that affordable Passivhaus dwelling construction costs can be reduced by up to £366/m2 (or 22% of build cost). Use of this evidence-based decision support tool could thereby enable local authorities and developers to make better-informed decisions in relation to cost optimal trade-offs between achieving advanced energy performance standards and the viability of large affordable housing developments.

Funding

Engineering and Physical Sciences Research Council (EPSRC) support for the London-Loughborough (LoLo) Centre for Doctoral Research in Energy Demand (grant EP/H009612/1)

History

School

  • Architecture, Building and Civil Engineering

Published in

Applied Energy

Volume

261

Publisher

Elsevier

Version

VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an open access article under the CC BY license (http://creativecommons.org/licenses/BY/4.0/).

Acceptance date

14/12/2019

Publication date

2020-01-06

Copyright date

2020

ISSN

0306-2619

Language

en

Depositor

Mr Joe Forde. Deposit date: 20 December 2019

Article number

114383