English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Received: 22 March 2018 Accepted: 27 May 2018 Dynamic energy simulation of buildings has recently become a very common tool to assess energy needs and thermal comfort in buildings. Software tools are now available at a low price, and allow a very detailed description of the building behaviour. However, one issue that is often neglected is the need to use accurate weather data to perform reliable dynamic simulations. The aim of the paper is to discuss the uncertainty generated by the choice of the weather data in the energy simulation of an existing office building located in the University campus of Catania, Southern Italy. To this aim, different sets of data are considered: the first one corresponds to the weather file available in the EnergyPlus database for the airport of Catania; the second one is generated by morphing the first one with a tool that takes into account the effect of buildings, vegetation and heat sources in the urban area. The paper discusses the differences amongst these data, and considers their impact on the calculation of the building heating and cooling load, as well as on the indoor thermal comfort. In the authors’ opinion, the outcomes of the study provide interesting information about the reliability of dynamic simulation as a tool for energy planning at urban scale. The results also point out the need to implement energy simulation with tools for weather data morphing in case of urban context.

Weather data morphing to improve building energy modeling in an urban context