Microclimate adapted localised weather data generation: implications for urban modelling and the energy consumption of buildings

Bourikas, Leonidas (2016) Microclimate adapted localised weather data generation: implications for urban modelling and the energy consumption of buildings. PhD thesis, University of Southanpton.

Abstract

Urban and building energy simulation models are usually driven by typical meteorological year (TMY) weather data often in a TMY2 or EnergyPlus Weather data file (EPW) format. In addition, currently, in many countries, weather data files with a TMY format are used for building regulation compliance calculations. 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 thesis, a humid sub-tropical climate context has been considered. An idealised “urban unit model” of 250m radius is 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 (e.g. 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 delivered results with performance evaluation indices comparable to previously published work (for air temperature; RMSE 0.9). The micro-climatic simulation results were then used to adapt the air temperature of the TMY file for Hangzhou to represent the local, site specific morphology under three different weather forcing cases, (i.e. 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. 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 coefficient of performance (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” (i.e. reference TMY) case. However, this assumes a cooling set-point of 26oC. If a lower set-point is used the predicted energy savings will be lost. 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 (i.e. the representation of the urban micro-climate) of current simulation weather data sets such as the TMY.