Abstract

The transition to renewable energy sources requires that larger shares of heating production should come from heat pumps both on individual level and in district heating networks. The efficiency of heat pumps is highly dependent on the temperature lift. Therefore, it is key to assess the possibilities of low-temperature heating in buildings. This paper proposes a data-driven methodology to analyse and benchmark the performance of radiator heating systems, by estimating parameters for the building’s envelope and heating system using Modelica with ModestPy. The methodology requires little a-priori knowledge and common data sources and provide valuable insights on the potentials of lowered operating temperatures. The methodology was tested on a newly renovated office building in Copenhagen and was able to consistently estimate characteristics of the envelope and capacity of the heating system. By using information on the actual capacity of the heating system, the methodology demonstrated the potential for lowering the heating supply temperatures, thereby reducing heat pump electricity consumption with 9 %.

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