Abstract
Building energy simulations are normally run through Typical Weather Years (TWYs) that reflect the average trend of local long-term weather data. This paper presents a research aimed at generating updated typical weather files for the city of Catania (Italy), based on 18 years of records (2002–2019) from a local weather station. The paper reports on the statistical analysis of the main recorded variables, and discusses the difference with the data included in a weather file currently available for the same location based on measurements taken before the 1970s but still used in dynamic energy simulation tools. The discussion also includes a further weather file, made available by the Italian Thermotechnical Committee (CTI) in 2015 and built upon the data registered by the same weather station but covering a much shorter period. Three new TWYs are then developed starting from the recent data, according to well-established procedures reported by ASHRAE and ISO standards. The paper discusses the influence of the updated TWYs on the results of building energy simulations for a typical residential building, showing that the cooling and heating demand can differ by 50% or even 65% from the simulations based on the outdated weather file.
Highlights
The energy consumption in buildings, which is in large part due to heating, ventilation, and air-conditioning, covers a high share of the overall energy balance worldwide
2019 and compares the data data measured included in files available for the and and compares them with the data included in the weather files available airport “Catania Fontanarossa” in the EnergyPlus website (IGDG) and in the websitefor of the the airport the EnergyPlus website (IGDG) and in the website of the Italian
Weather data recorded from 2002 to 2019 through a stationary meteorological station owned by the Sicilian Agrometeorological Information System (SIAS) and located outside the city context have been compared to two currently available datasets: The one provided by the Italian Thermotechnical
Summary
The energy consumption in buildings, which is in large part due to heating, ventilation, and air-conditioning, covers a high share of the overall energy balance worldwide. In light of the rising concern towards environmental issues, and in accordance with the growing number of national and international regulations aiming at a severe reduction in the depletion of non-renewable primary energy sources, the need of detailed studies concerning the energy behavior of buildings has recently become strongly felt To this aim, software tools for dynamic energy simulation of buildings are nowadays commonly available and widely used by researchers, engineers, and others involved in the design and optimization of the energy performance of buildings. Most building energy simulation tools make use of weather files based on a Typical Weather Year (TWY), that is to say a full year of typical local hourly weather data generated by statistically averaging long-term weather measurements, issued by weather stations commonly placed in peripheral or rural zones.
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