An in-depth analysis of the climate files and their effect on the energy analysis of buildings was developed. The weather files contain all the information related to the climate of a specific location: they contain hourly data of the air thermo-hygrometric conditions, the solar radiation and the wind characteristics. These data strongly influence the energy simulation outcomes. One of the more important climatic parameters is solar radiation. While weather stations usually measure global radiation on a horizontal plane using pyranometers, the main dynamic simulation software requires two distinct components, direct and diffuse radiation. If the two components are not measured separately, mathematical models are used to derive the direct and diffused radiation. In literature, there are more than 150 algorithms used to split the radiation: they show variable performances depending on the data from which they were obtained. To study the split model performances and their effect on energy simulations, 33 models were selected. They were applied to a weather dataset recorded in Trieste and to a test building simulation: the results, in terms of statistical indicators and energy consumption differences, were studied. Furthermore, the research focused on the effect of climate files on building energy simulation. The weather files are obtained from different procedures that aim to generate an annual dataset representative of the average climatic conditions of a specific location. An optimization was carried out to simulate a building renovation activity: three climate files from Trieste were tested, and the differences between the pareto frontiers were analyzed. In 2015, the CTI published new climate files, to update the available ones that were derived from dated measurements. To study the effect of the new dataset introduction, the results deriving from the application of the dated and the updated dataset have been applied to the entire Italian scenario. Finally, the methodology described in the UNI EN 15927-2 was applied to the raw data made available by the CTI, for the identification of the summer design day. The design days were obtained, characterized by extreme conditions useful for cooling system sizing. This method was compared with the results of other three widely used methodologies, for the Italian panorama.
È stata condotta un'analisi approfondita dei file climatici e dei loro effetti sull'analisi energetica degli edifici. I file meteo contengono tutte le informazioni relative al clima di un luogo specifico: contengono dati orari delle condizioni termo-igrometriche dell’aria, della radiazione solare e le caratteristiche del vento. Questi dati influenzano fortemente i risultati della simulazione energetica. Uno dei parametri climatici più importanti è la radiazione solare. Solitamente le stazioni meteorologiche misurano la radiazione globale su un piano orizzontale usando piranometri; tuttavia, i software di simulazione dinamica richiedono le due componenti di radiazione, la diretta e diffusa. Se le due componenti non vengono misurati separatamente, si utilizzano dei modelli matematici per derivare la due componenti. In letteratura, ci sono più di 150 algoritmi utilizzati per dividere la radiazione: essi hanno prestazioni variabili a seconda del dataset originale da cui sono stati ottenuti. Per studiare le prestazioni del modello split e il loro effetto sulle simulazioni energetiche, sono stati selezionati 33 modelli. Sono stati applicati a un dataset meteorologico registrato a Trieste e ad una simulazione di un edificio test: sono stati studiati i risultati, in termini di indicatori statistici e differenze di consumo energetico dell’edificio test. Inoltre, la ricerca si è concentrata sull'effetto di diversi file climatici sulla simulazione energetica degli edifici. I file meteo sono ottenuti da diverse procedure che mirano a generare un dataset annuale rappresentativo delle condizioni climatiche medie di un luogo specifico. È stata effettuata un'ottimizzazione per simulare una ristrutturazione edilizia: sono stati testati tre file climatici di Trieste e sono state analizzate le differenze tra i vari fronti di Pareto. Nel 2015, la CTI ha pubblicato nuovi file climatici, per aggiornare quelli disponibili che derivano da misurazioni datate. Per studiare l'effetto della nuova introduzione dei nuovi anni tipo, i risultati derivanti dall'applicazione del dataset datato e aggiornato sono stati applicati all'intero scenario italiano. Infine, la metodologia descritta nella UNI EN 15927-2 è stata applicata ai dati grezzi resi disponibili dal CTI, per l'identificazione del giorno di progetto estivo. Sono stati ottenuti i giorni di progetto, caratterizzati da condizioni estreme utili per il dimensionamento dei sistemi di raffreddamento. Questo metodo è stato confrontato con i risultati di altre tre metodologie ampiamente utilizzate, e applicate al panorama italiano.
THE CLIMATE DATA EFFECT ON BUILDING ENERGY SIMULATION / Lupato, Giorgio. - (2019 Mar 28).
THE CLIMATE DATA EFFECT ON BUILDING ENERGY SIMULATION
LUPATO, GIORGIO
2019-03-28
Abstract
An in-depth analysis of the climate files and their effect on the energy analysis of buildings was developed. The weather files contain all the information related to the climate of a specific location: they contain hourly data of the air thermo-hygrometric conditions, the solar radiation and the wind characteristics. These data strongly influence the energy simulation outcomes. One of the more important climatic parameters is solar radiation. While weather stations usually measure global radiation on a horizontal plane using pyranometers, the main dynamic simulation software requires two distinct components, direct and diffuse radiation. If the two components are not measured separately, mathematical models are used to derive the direct and diffused radiation. In literature, there are more than 150 algorithms used to split the radiation: they show variable performances depending on the data from which they were obtained. To study the split model performances and their effect on energy simulations, 33 models were selected. They were applied to a weather dataset recorded in Trieste and to a test building simulation: the results, in terms of statistical indicators and energy consumption differences, were studied. Furthermore, the research focused on the effect of climate files on building energy simulation. The weather files are obtained from different procedures that aim to generate an annual dataset representative of the average climatic conditions of a specific location. An optimization was carried out to simulate a building renovation activity: three climate files from Trieste were tested, and the differences between the pareto frontiers were analyzed. In 2015, the CTI published new climate files, to update the available ones that were derived from dated measurements. To study the effect of the new dataset introduction, the results deriving from the application of the dated and the updated dataset have been applied to the entire Italian scenario. Finally, the methodology described in the UNI EN 15927-2 was applied to the raw data made available by the CTI, for the identification of the summer design day. The design days were obtained, characterized by extreme conditions useful for cooling system sizing. This method was compared with the results of other three widely used methodologies, for the Italian panorama.File | Dimensione | Formato | |
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