Utilising Open Geospatial Data to Refine Weather Variables for Building Energy Performance Evaluation—Incident Solar Radiation and Wind-Driven Infiltration Modelling

Abstract

In building thermal energy characterisation, the relevance of proper modelling of the effects caused by solar radiation, temperature and wind is seen as a critical factor. Open geospatial datasets are growing in diversity, easing access to meteorological data and other relevant information that can be used for building energy modelling. However, the application of geospatial techniques combining multiple open datasets is not yet common in the often scripted workflows of data-driven building thermal performance characterisation. We present a method for processing time-series from climate reanalysis and satellite-derived solar irradiance services, by implementing land-use, and elevation raster maps served in an elevation profile web-service. The article describes a methodology to: (1) adapt gridded weather data to four case-building sites in Europe; (2) calculate the incident solar radiation on the building facades; (3) estimate wind and temperature-dependent infiltration using a single-zone infiltration model and (4) including separating and evaluating the sheltering effect of buildings and trees in the vicinity, based on building footprints. Calculations of solar radiation, surface wind and air infiltration potential are done using validated models published in the scientific literature. We found that using scripting tools to automate geoprocessing tasks is widespread, and implementing such techniques in conjunction with an elevation profile web service made it possible to utilise information from open geospatial data surrounding a building site effectively. We expect that the modelling approach could be further improved, including diffuse-shading methods and evaluating other wind shelter methods for urban settings.

Building Energy Performance Evaluation of a Norwegian single-family house applying ISO-52016

“…Shading masks for each façade were approximated using a simplified building footprint and the national elevation model in 1-meter resolution. The approach to obtain building height H b , shading masks F sh , and morphology parameters plan area density λ p and wind sheltering factor λ w are described in (Skeie and Gustavsen 2021). The shading mask and solar irradiance is calculated using the R-package solarCalcISO52010 (Lundström 2018).…”

“…Previous works show that rearranging gridded weather data, such as the operational MET Nordic Analysis and Forecast, or global and regional reanalysis, along the time dimension make it possible to compile hourly multi-year weather datasets in seconds. Open spatial datasets can also be utilised to adjust for local sheltering and shadow conditions in a simplified manner or model surrounding buildings and vegetation in 3D in a pre-processing step (Skeie and Gustavsen 2021). Realistic evaluations spanning several years in actual local climate using computationally efficient models based on international standards, provides a basis for as-built performance evaluation, and enables comparison with measurements.…”

Open Data and Models for Energy and Environment

“…In the eight paper, Manfren et al [8] review the role of energy modelling and analytics for energy transitions in the construction sector. Skeie and Gustavsen [9] investigate the use of geospatial data to improve the level of definition of weather variables used in data-driven building thermal performance characterization. Finally, in the tenth paper, Agostinelli et al [10] illustrate the use of cyber-physical systems, Internet of things, and machine learning to achieve optimized energy management for a residential district in Rome.…”