Search results for " Weather Data"

showing 2 items of 2 documents

Building energy demand assessment through heating degree days: the importance of a climatic dataset

2019

Abstract The weather is one of the main factors to consider when designing a building because it represents the most important boundary condition to affect the dynamic behaviour of the building. In the literature, many studies use the degree day to predict building energy demand. However, linking the results obtained from a generic building simulation tool with defined degree days, will not give reliable energy evaluation. The goal of this study is to demonstrate that the assessment of building energy demand through the use of the degree day is correct only if the determination of the climate index is a function of the same weather data. The relationship between Heating Degree-Day and heati…

Decision support systemComputer science020209 energymedia_common.quotation_subject02 engineering and technologyManagement Monitoring Policy and LawDegree (temperature)Heating energy demandDegree day020401 chemical engineering0202 electrical engineering electronic engineering information engineeringSettore ING-IND/10 - Fisica Tecnica Industriale0204 chemical engineeringFunction (engineering)Reliability (statistics)media_commonHeating energy demand Degree days Building thermal balance Weather data Building simulation model Empirical correlationsSettore ING-IND/11 - Fisica Tecnica AmbientaleDegree dayMechanical EngineeringWork (physics)Building simulation modelBuilding and ConstructionEmpirical correlationsIndustrial engineeringGeneral EnergyEnergy (all)Weather dataEmpirical correlationBuilding thermal balanceDegree daysHeating degree dayEnergy (signal processing)
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A new approach to model the effect of climate change on the building sector: A climate models data fusion

2020

Several climate models have been developed and used to forecast the effects of the climate changes, however the variability of results due to different models lead to a significant uncertainty on the estimation of the building energy use for the next century. In this context, the paper analyses this uncertainty and combines different climate models in order to improve the robustness of energy consumption predictions. The data of the climate models were then used to generate hourly weather files for the future period 2020-2099 and energy simulations for a case study located in Palermo (Italy) were performed. Results show a wide variability among all models (either alone or combined with our …

Settore ING-IND/11 - Fisica Tecnica Ambientalebusiness.industrySettore ING-INF/03 - TelecomunicazioniEnvironmental resource managementClimate Change Building Sector Building Simulation General Circulation Models Data Fusion Weather DataEnvironmental scienceClimate changeClimate modelbusinessSensor fusion
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