A method to account for the urban microclimate on the creation of 'typical weather year' datasets for building energy simulation, using stochastically generated data

Predicting buildings' heating and cooling needs through dynamic simulation methods requires the input of hourly weather data, so as to represent the typical meteorological characteristics of a specific location. Hence, the so called 'typical weather years' (TWY), mainly deduced from multi-year records of meteorological stations outside the urban centres, cannot account of the complex interactions between solar radiation, wind speed and high urban densities which lead to the formation of the urban heat island effect and to higher ambient air temperatures. As the assumption that climatic parameters at a reference location of a meteo station are similar for a densely built up area can lead to miscalculations of the heating and cooling needs, the aim of this study is to present a computational method for assessing the urban climate's effect during the generation of typical weather data for dynamic energy calculations. In this vein, a typical 'urban specific weather dataset' (USWD), reflecting the microclimatic conditions in front of a building unit inside an urban district in the city of Thessaloniki, Greece is created based on microclimate simulations with the Envi-met model; it is then compared with a typical reference weather dataset (RWD), representing climatic conditions at a reference location of a meteo station. The results indicate that the proposed method can capture microclimate characteristics; higher dry bulb temperatures were reported during the year inside the urban canyon, compared to the corresponding values at the reference location, with indicative mean daily deviations up to 1.0°C and 0.75°C in February and July respectively. Wind speed, near the building façade is generally found lower than the corresponding values at the reference location, due to wind sheltering by neighbouring constructions. Given that climatic parameters strongly influence the output of energy simulations the proposed computational method provide a contribution for higher accuracy of building energy simulation in the urban context. Future work will involve energy performance simulations of a typical building unit with the generated USWD file so as to evaluate the urban climate's influence on energy needs.