A Probabilistic Model for Characterising Heat Pump Electrical Demand versus Temperature

The introduction of electric heat pumps as an alternative to gas based systems for space heating offers a potential pathway for reducing the carbon emissions produced to meet domestic heating demand in the UK. The adoption of heat pumps has the potential to significantly re-shape typical domestic load profiles, however uptake within the UK is currently limited and the effects of wide-scale adoption on distribution networks is not well understood. Heat pump demand is highly sensitive to temperature, lessening load profile diversity, but is also influenced by behavioral routine and is therefore not entirely deterministic. This study develops a probabilistic demand model from real customer heat pump data for translating electrical heat pump demand/air temperature relations to account for regional variation. A LV network heat pump penetration study is performed to demonstrate how residential network impact can be assessed using the model.