Transforming typical hourly simulation weather data files to represent urban locations by using a 3D urban unit representation with micro-climate simulations. Issue 1 (8th July 2016) - Bourikas, Leonidas; James, Patrick A. B.; Bahaj, AbuBakr S.; Jentsch, Mark F.; Shen, Tianfeng; Chow, David H. C.; Darkwa, Jo
Abstract: Urban and building energy simulation models are usually driven by typical meteorological year (TMY) weather data often in a TMY2 or EPW format. However, the locations where these historical datasets were collected (usually airports) generally do not represent the local, site specific micro-climates that cities develop. In this paper, a humid sub-tropical climate context has been considered. An idealised "urban unit model" of 250 m radius is being presented as a method of adapting commonly available weather data files to the local micro-climate. This idealised "urban unit model" is based on the main thermal and morphological characteristics of nine sites with residential/institutional (university) use in Hangzhou, China. The area of the urban unit was determined by the region of influence on the air temperature signal at the centre of the unit. Air temperature and relative humidity were monitored and the characteristics of the surroundings assessed (eg green-space, blue-space, built form). The "urban unit model" was then implemented into micro-climatic simulations using a Computational Fluid Dynamics – Surface Energy Balance analysis tool (ENVI-met, Version 4). The "urban unit model" approach used here in the simulations delivered results with performance evaluation indices comparable to previously published work (for air temperature; RMSE <1, index of agreement d > 0.9). The micro-climatic simulation results were then used to adapt the air temperature and relative humidity of the TMY file for Hangzhou to represent the local, site specific morphology under three different weather forcing cases, (ie cloudy/rainy weather (Group 1), clear sky, average weather conditions (Group 2) and clear sky, hot weather (Group 3)). Following model validation, two scenarios (domestic and non-domestic building use) were developed to assess building heating and cooling loads against the business as usual case of using typical meteorological year data files. The final "urban weather projections" obtained from the simulations with the "urban unit model" were used to compare the degree days amongst the reference TMY file, the TMY file with a bulk UHI offset and the TMY file adapted for the site-specific micro-climate (TMY-UWP). The comparison shows that Heating Degree Days (HDD) of the TMY file (1598 days) decreased by 6 % in the "TMY + UHI" case and 13 % in the "TMY-UWP" case showing that the local specific micro-climate is attributed with an additional 7 % (ie from 6 to 13 %) reduction in relation to the bulk UHI effect in the city. The Cooling Degree Days (CDD) from the "TMY + UHI" file are 17 % more than the reference TMY (207 days) and the use of the "TMY-UWP" file results to an additional 14 % increase in comparison with the "TMY + UHI" file (ie from 17 to 31 %). This difference between the TMY-UWP and the TMY + UHI files is a reflection of the thermal characteristics of the specific urban morphology of the studied sites compared to the wider city. A dynamic thermal simulation tool (TRNSYS) was used to calculate the heating and cooling load demand change in a domestic and a non-domestic building scenario. The heating and cooling loads calculated with the adapted TMY-UWP file show that in both scenarios there is an increase by approximately 20 % of the cooling load and a 20 % decrease of the heating load. If typical COP values for a reversible air-conditioning system are 2.0 for heating and 3.5 for cooling then the total electricity consumption estimated with the use of the "urbanised" TMY-UWP file will be decreased by 11 % in comparison with the "business as usual" (ie reference TMY) case. Overall, it was found that the proposed method is appropriate for urban and building energy performance simulations in humid sub-tropical climate cities such as Hangzhou, addressing some of the shortfalls of current simulation weather data sets such as the TMY.