Predicting the energy performance of retrofit domestic heat pumps

Increasing the uptake of retrofit heat pumps in the UK is essential for the decarbonisation of heat in the residential sector, which will require greater certainty in the ability of heat pumps to deliver cost effective comfort conditions and carbon emissions reductions. Heat pump performance is linked to the quality of design and installation practices, and users need assurances that predicted performance can be achieved. This paper presents a sensitivity analysis of energy prediction for domestic properties against the variation of five key input variables: heat loss coefficient, set point temperature, system coefficient of performance, casual gains and fabric thermal mass. The energy prediction model used was a degree-day based simplified predictor model that explicitly models the impacts of the control regime (fixed time start, night set back or optimum start). This is a feature not typically available for widely adopted steady state energy models. Modelling forecast errors are shown to be highly significant for heat loss coefficient, set point temperature and coefficient of performance, leading to the need for greater accuracy in the accuracy of these input variables. Practical application Selection and operational control of heat pumps differ from traditional heating systems such as gas or oil fired boilers. Correct sizing of heat pumps is much more critical to their operational performance than other systems, and design methods require more certainty in their forecasting of economy and carbon emissions, especially for retrofit applications. This paper indicates the range of input errors that can occur, and the impacts of these on performance forecasts.