Heat pump integration for domestic hot water: Data gaps, modelling limits, and implications for long-term planning
Abstract
Peer-reviewed paper 7-108-26
The energy transition creates significant challenges for long-term planning in the buildings sector, which accounts for around 35% of EU greenhouse gas emissions. Frameworks such as the Energy Performance of Buildings Directive promote electrification and the deployment of heat pumps, yet the representation of domestic hot water (DHW) technologies in long-term energy models remains challenging due to limited data. This paper examines the integration of DHW heat pumps into the OSeMOSYS-based national energy system model, using Portugal as a case study. Key modelling gaps are identified in the DHW demand, technology performance, and economic parameters. National statistics provide aggregated residential energy data, while detailed end-use information and hourly DHW profiles remain scarce. To address these limitations, the modelling framework reconstructs DHW demand from national energy balances, derives stylised demand profiles from literature proxies, and represents heat pump performance using seasonal coefficients of performance (COP). Technology costs, including capital investment, maintenance, and electricity prices, are parameterised using market data and European literature benchmarks. Instead of exploring numerous scenarios, this study quantifies how key modelling assumptions, particularly cost parameters and COP variations, affect heat pump deployment, system costs, and electricity demand. Results show that cost assumptions influence heat pump deployment, while variations in COP affect electricity demand, with implications for grid planning. The outcomes demonstrate that modelling assumptions can lead to substantial variations in system outcomes, even under consistent decarbonisation constraints. The study emphasises the importance of transparency when modelling under data scarcity and illustrates a pragmatic approach to representing DHW heat pumps in national energy system planning models.
© 2026 Hermano Bernardo, Mahamat Habib Bechir, published by European Council for an Energy Efficient Economy (eceee)
This work is licensed under the Creative Commons Attribution 4.0 License.