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Modelling the contribution of domestic heat pumps to delivering UK energy policy objectives

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journal contribution
posted on 2013-08-30, 11:13 authored by David Braun, Paul Rowley
The UK Government has ambitious targets for CO2 emissions reductions, particularly for the domestic housing stock. One technology that is expected to contribute significantly is heat pumps, both air and ground source. However, recent field trial results suggest that heat pumps in the UK are not delivering to performance expectations. This paper looks at the implications of these results for the UK housing stock’s future CO2 emissions. The English Housing Condition Survey dataset is used as the basis for a Monte Carlo simulation in order to model CO2 emissions and energy consumption for the whole of English housing stock out to 2050. The results suggest that, given the current UK electricity grid CO2 emission factor, in the short term poor heat pump performance could lead to a rise in emissions where natural gas boilers are displaced. In the longer term, heat pumps can realise emissions reductions when installed at high penetration levels when combined with a grid decarbonisation strategy. Until grid decarbonisation occurs, an alternative phased strategy is proposed that includes phased replacement of resistive electric heating, first in households in fuel poverty and then the remainder of properties with this heating type. Following this phased strategy, real emissions savings are possible along with a potential reduction in fuel poverty.

History

School

  • Mechanical, Electrical and Manufacturing Engineering

Citation

BRAUN, D. and ROWLEY, P., 2013. Modelling the contribution of domestic heat pumps to delivering UK energy policy objectives. Applied Sciences, 3 (2), pp. 338 - 354.

Publisher

MDPI © the authors

Version

  • VoR (Version of Record)

Publication date

2013

Notes

This article was published in the journal, Applied Sciences [MDPI © the authors]. It is also available at: http://dx.doi.org/10.3390/app3020338

ISSN

2076-3417

Language

  • en