Weather data for building simulation : New actual weather files for North Europe combining observed weather and modeled solar radiation

Dynamic building simulation is increasingly necessary for accurately quantifying potential energy savings measures in retrofit projects, to compliant with new stricter directives from EU implanted into member states legislations and building codes. For good result the simulation model need to be accurately calibrated. This requires actual weather data, representative for the climate surrounding the given building, in order to calibrate against actual energy bills of the same period of time. The main objective of this degree project is to combine observed weather (temperature, humidity, wind etc.) data with modeled solar radiation data, utilizing the SMHI STRÅNG model system; and transform these data into AMY (Actual Meteorological Year) files to be used with building simulation software. This procedure gives actual weather datasets that will cover most of the urban and semi urban area in Northern Europe while still keeping the accuracy of observed weather data. A tool called Real-Time Weather Converter was developed to handle data retrieval & merging, filling of missing data points and to create the final AMY-file. Modeled solar radiation data from STRÅNG had only been validated against a Swedish solar radiation network; validation was now made by the author with wider geographic coverage. Validation results show that STRÅNG model system performs well for Sweden but less so outside of Sweden. There exist some areas outside of Sweden (mainly Central Europe) with reasonable good result for some periods but the result is not as consistent in the long run as for Sweden. The missing data fill scheme developed for the Real-Time Weather Converter does perform better than interpolation for data gaps (outdoor temperature) of about 9 to 48 hours. For gaps between 2 and 5 days the fill scheme will still give slightly better result than linear interpolation. Akima Spline interpolation performs better than linear interpolation for data gaps (outdoor temperature) in the interval 2 to about 8 hours. Temperature uncertainty was studied using data from the period 1981-2010 for selected sites. The result expressed as SD (Standard Deviation) for the uncertainty in yearly mean temperature is about 1˚C for the Nordic countries. On a monthly basis the variation in mean temperature is much stronger (for Nordic countries it ranges from 3.5 to 4.7 ˚C for winter months), while summer months have less variation (with SD in the range of 1.3 to 1.9 ˚C). The same pattern is visible in sites at more southern latitudes but with much lower variation, and still lower for sites near coast areas. E.g. the cost-near Camborne, UK, has a SD of 0.7 to 1.7 ˚C on monthly basis and yearly SD of 0.5 ˚C. Mean direct irradiance SD for studied sites ranges from 5 to 19 W/m2 on yearly basis, while on monthly basis the SD ranges from 40 to 60 W/m2 for summer months. However, the sample base was small and of inconsistent time periods and the numbers can only be seen as indicative. The commonly used IWEC (International Weather for Energy Calculations) files direct radiation parameter was found to have a very strong negative bias of about 20 to 40 % for Northern Europe. These files should be used with care, especially if solar radiation has a significant impact of on the building being modeled. Note that there exist also a newer set of files called IWEC2 that can be purchased from ASHRAE, these files seems not to be systematically biased for North Europe but haven’t been studied in this paper. The STRÅNG model system does catch the trend, also outside of Sweden, and is thus a very useful source of solar radiation data for model calibration