Abstract
Building energy performance modeling is essential for energy planning, management, and efficiency. This paper presents a space heating model suitable for auto-generating baseline models of existing multifamily buildings. Required data and parameter input are kept within such a level of detail that baseline models can be auto-generated from, and calibrated by, publicly accessible data sources. The proposed modeling framework consists of a thermal network, a typical hydronic radiator heating system, a simulation procedure, and data handling procedures. The thermal network is a lumped and simplified version of the ISO 52016-1:2017 standard. The data handling consists of procedures to acquire and make use of satellite-based solar radiation data, meteorological reanalysis data (air temperature, ground temperature, wind, albedo, and thermal radiation), and pre-processing procedures of boundary conditions to account for impact from shading objects, window blinds, wind- and stack-driven air leakage, and variable exterior surface heat transfer coefficients. The proposed model was compared with simulations conducted with the detailed building energy simulation software IDA ICE. The results show that the proposed model is able to accurately reproduce hourly energy use for space heating, indoor temperature, and operative temperature patterns obtained from the IDA ICE simulations. Thus, the proposed model can be expected to be able to model space heating, provided by hydronic heating systems, of existing buildings to a similar degree of confidence as established simulation software. Compared to IDA ICE, the developed model required one-thousandth of computation time for a full-year simulation of building model consisting of a single thermal zone. The fast computation time enables the use of the developed model for computation time sensitive applications, such as Monte-Carlo-based calibration methods.
Highlights
Building energy performance modeling is essential for energy planning, management, and efficiency
The developed ISO14N model and its procedures were validated by comparing it with simulations conducted with the detailed building energy simulation software IDA ICE
Simulation results from the developed ISO14N model are compared with results from an IDA ICE simulation
Summary
Building energy performance modeling is essential for energy planning, management, and efficiency. To improve energy efficiency of building stocks, knowledge on how each building is currently performing is needed, often referred to as baselines. Energies 2019, 12, 485 depends on aspects such as physical and thermal properties, climate, control and operational schemes, occupants’ presence, and behavior. Information regarding these aspects is often uncertain and scattered, sometimes missing altogether, and establishing the energy performance of buildings can be a tedious task [1,2]. Data-driven models use system behavior as a predictor for system performance
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