Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/189540
Title: Long wave radiation exchange for urban scale modeling within a co-simulation environment
Authors: Miller, Clayton Carl 
Thomas, Daren
Kampf, Jerome
Schlueter, Arno
Keywords: Urban-scale simulation
Co-simulation
Long Wave Radiation Exchange
Issue Date: 9-Sep-2015
Citation: Miller, Clayton Carl, Thomas, Daren, Kampf, Jerome, Schlueter, Arno (2015-09-09). Long wave radiation exchange for urban scale modeling within a co-simulation environment. CISBAT 2015. ScholarBank@NUS Repository.
Abstract: This paper describes the implementation of long wave radiation (LWR) exchange as part of a co-simulation process of an urban scale simulation program, CitySim, and a building scale program, EnergyPlus. This coupling process was achieved through the use of functional mockup units (FMU) to exchange various weather, load, and environmental information between the two simulation engines. LWR is an important factor to exchange between the programs as CitySim has more advanced capabilities for radiation exchange calculations from a set of urban buildings and EnergyPlus has a more advanced building heating and cooling load calculation engine. The LWR exchange between surfaces is computed in CitySim by a linearization of the longwave energy balance at each surface around an average between the surface and its environmental temperatures. The environmental temperature for each surface is determined using the simplified radiation algorithm neglecting inter-reflections and is aggregated into a single, global environmental radiant temperature (Tenv). The LWR exchange process is implemented in EnergyPlus by CitySim sharing the variables Tenv and henv that are then used to calculate radiation gain or loss through the envelope as well as influence on the conductances of the surfaces. This approach overrides the conventional EnergyPlus ground, sky and air radiation calculations. Solo and coupled simulations are performed on a set of four scenarios and result in up to a 36% discrepancy in heating and 11% in cooling load calculations amongst solo and coupled simulations.
Source Title: CISBAT 2015
URI: https://scholarbank.nus.edu.sg/handle/10635/189540
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