Coupling of building and vegetation resolving urban microclimate model with a building energy simulation program

The objective of this work is to develop and validate a coupled fast-running Building Energy Modeling/Microclimate model for use in developing site-specific design strategies which minimize energy and water use All the micro-climate variables affecting the building energy consumption, such as solar radiation, long wave radiation, air temperature, wind speed and direction, are taken into account. Differently from previous literature, we propose a fully-dynamic coupling approach, fully surface-specific, coupling EnergyPlus and QES.

Coupling of a building and vegetation resolving urban microclimate Building Energy Model: model with a building energy simulation program 1,3 Department of MECHANICAL ENGINEERING 1 1 1 EnergyPlus , Arash Nemati Hayati , Peter Willemsen , Amanda D. Smith , Robert Stoll , Eric R. Pardyjak Carlo Bianchi 1 University of Utah, Salt Lake City 1 2 THE UNIVERSITY OF UTAH 2 University of Minnesota, Duluth National Renewable Energy Laboratory, Golden, CO • Well-known and supported 3 DOE model with source EnergyPlus Motivation • Buildings account for a substantial share of world energy consumption and of the emissions in urban environments. • Building energy modeling is commonly used by building energy system designers to predict and optimize building energy loads and operational schemes. • Building energy consumption is generally affected by what is inside the building (such as occupants, appliances, HVAC systems, etc.) and by what is outside: the weather conditions the building is exposed to. • Macro-climate conditions influence the regional weather,micro-climate conditions influence the weather directly outside the building. • • • • code availability In-house expertise Model assumes isolated buildings Complex flow around build not accounted for • Weather conditions are employed • Highly idealized boundary conditions. as boundary conditions for internal Highly idealized boundary • Complex flow around build not accounted energy loads calculations. for. conditions • Well-known and supported DOE Results and Discussion Input Data File (.idf) Contains the characteristics of the building (such as sizes, materials, etc.) Weather File (.epw) Contains weather data (including temperature, humidity, solar radiation, etc.) specific to the location of the building model with source code E.R. Pardyjak availability. 8th Comparison of incoming solar radiation between EnergyPlus and QES • Model assumes isolated buildings. ISEH 2018 Coupling Methodology The objective of this work is to develop and validate a coupled fast-running Building Energy Modeling/Microclimate model for use in developing site-specific design strategies which minimize energy and water use All the micro-climate variables affecting the building energy consumption, such as solar radiation, long wave radiation, air temperature, wind speed and direction, are taken into account. Differently from previous literature [1, 2, 3], we propose a fully-dynamic coupling approach, fully surface-specific, coupling EnergyPlus and QES. • The exchange of information between these 2 pieces of software was managed by a Python code. • Full 24h simulations are performed in EnergyPlus for each timestep. Comparison of external convective heat fluxes between EnergyPlus and QES QES QUIC EnvSim: Quick Urban Industrial Complex Environmental Simulation (QES) [4, 5, 6, 7, 8] - a robust, low-cost numerical simulation system that can represent a wide range of urban microclimate physical processes over a wide range of scales. Comparison of external surface temperatures between EnergyPlus and QES 2000 CHTCs QES - Night Hours 100 North South East West Roof 1800 1600 80 CHTC [ mW2 K ] CHTC [ mW2 K ] 70 1200 1000 ICUC10 - 6-10 August 2018, New York, NY 800 60 50 40 600 30 400 20 200 10 0 North South East West Roof 90 1400 QUIC Urb is a mass consistent diagnostic wind model; it calculates the 3 dimensional mean wind characteristics around buildings. It employs empirical parametrizations to calculate the initial wind fields around complex urban geometries. Once the initial wind field has been solved, mass consistency is imposed. QUIC Plume is a random-walk Lagrangian module, designed to run on GPUs. It calculates the turbulence characteristics required to simulate convective heat flux. QES Transport calculates the distribution of temperature and moisture throughout a city. Heat and moisture exchanges between the atmosphere and urban canopies are calculated to compute a local energy balance on each urban cell in the domain. QES Radiant is a ray-tracing based radiative heat transfer model that calculates the radiative heat flux budget at surface in urban canopies including short-wave and long-wave heat fluxes on building surfaces. QES LSM receives inputs from the other modules and solves the surface heat balance. Given the building internal surface temperature, LSM calculates the external surface temperature and the conductive heat flux that balances out the external convective heat flux, the long wave and the shortwave radiation heat fluxes. For more details about QES, refer to Talk 4D.8 of the current conference. CHTCs QES - Day Hours 2 4 6 8 0 10 Time [h] 15 20 Time [h] Comparison of external CHTCs between EnergyPlus and QES Case Study Proof of concept of coupling QES and EnergyPlus has been demonstrated Results are sensitive to QES's surface sensible heat flux model at night, when temperature gradients are very weak, which must be improved. Future work should include passing radiation and vegetation. References [1] [2] [3] • No HVAC Systems (ideal loads). • 1-h time-steps. • Simulations for the 19th of March in Salt Lake City, UT (40.7608 N, 111.8910 W). • Material properties for red-brick. • • • • • 33m x 33m x 33m; 0.9 m thick. Wind direction = 262o Inlet wind speed = 3.8 m/s Ambient air temperature = 23.6o C Logarithmic inflow conditions [4] [5] [6] [7] [8] Xiaoshan Yang, Lihua Zhao, Michael Bruse, and Qinglin Meng. An integrated simulation method for building energy performance assessment in urban environments. Energy and Buildings, 54:243-251, 2012. Clayton Miller, Daren Thomas, Jérôme Kämpf, and Arno Schlueter. Urban and building multiscale co-simulation: case study implementations on two university campuses. Journal of Building Performance Simulation, 11(3):309-321, 2018. Jonas Allegrini, Viktor Dorer, and Jan Carmeliet. Coupled cfd, radiation and building energy model for studying heat fluxes in an urban environment with generic building configurations. Sustainable Cities and Society, 19:385-394, 2015. Matthew C. Overby. A high performance framework for coupled urban microclimate models. Master's thesis, University of Minnesota, November 2014. Michael D Williams, Michael J Brown, Balwinder Singh, and David Boswell. Quic-plume theory guide. Los Alamos National Laboratory, page 43, 2004. Eric R Pardyjak and Michael Brown. Quic-urb v. 1.1: Theory and userâĂŹs guide. Los Alamos National Laboratory, Los Alamos, NM, 2003. Kevin A Briggs. Evaluation of moisture and heat transport in the fast-response building-resolving urban transport code QUIC EnvSim. The University of Utah, 2015. Arash Nemati Hayati. A computational study of momentum and scalar transport in urban areas. PhD thesis, University of Utah, May 2018. This material is based upon work supported by the National Science Foundation under the following Grant: CBET 1512740.