Nowadays in Italy, domestic heating and cooling still contributes significantly to pollution and overheating of cities. This occurs because most of the buildings in the area were built without paying attention to containing energy consumption. The European directives under discussion (e.g. EPBD) impose ambitious objectives for the reduction of energy consumption and greenhouse gas emissions and the means for their fulfilment is energy efficiency. Dynamic energy simulations are the tool which, thank to accurate models of building-plant system, guide us toward the most effective solutions for this purpose. The paper deals with applying this tool to a real case study to achieve different objectives. The study is divided into four steps. The first is based on understanding which aspects have the greatest influence on energy efficiency. For this purpose, numerous simulations were carried out with different settings (g-value, climatic files) and by comparing the results it was possible to identify the parameters that most affect the thermal requirements. The second with the aim of comparing the results obtained with those of “Law 10 Report”. This process was the most substantial and it is divided into several phases. We began by analysing the calculation differences in the two different approaches, continued by comparing the results and concluded by analysing the influence of the differences found on the energy balance. The third step was the presentation of a proposal with more realistic settings. Finally, the fourth and final step, was aimed at testing the resilience of the energy system to climate changes. The results that emerged are: the boundary conditions of the model account for more than 20%; the differences between dynamic and semi-stationary approach are quantified in a variation of around 10% for heating requirement and around 20% for cooling one; using realistic settings allows to obtain lower needs of more than 10%. Lastly, in the future, the demand for cooling thermal energy will increase by around 70%, making it necessary to design based on different needs. At the end of the study, the utilization factor was analysed in detail. By calculating the value that it should have taken to return heat requirement values similar to those read in the output from dynamic simulation given the difficulty of reading its trend in relation to the factors on which it depends, it was decided to try developing a new formula for its computation with the aim of finding an easy-to-read relationship that would allow to obtain better results closer to dynamics simulations ones. The result is a formula which makes it possible to obtain annual thermal requirements which deviate from the TRNSYS outputs by a value in a range of 10% against approximately 30% of those calculated with the standard procedure.
Oggigiorno in Italia il riscaldamento e raffrescamento domestico contribuiscono ancora significativamente all’inquinamento e surriscaldamento delle città. Questo avviene perché la maggior parte degli edifici presenti sul territorio sono stati costruiti senza prestare attenzione al contenimento dei consumi energetici. Le direttive europee in discussione (e.g. EPBD) impongono obbiettivi ambiziosi di riduzione del consumo energetico e di emissione di gas serra e il mezzo per il loro adempimento è l’efficienza energetica. Le simulazioni energetiche dinamiche sono lo strumento che, grazie a modelli accurati del sistema edificio-impianto, permettono di guidarci verso le soluzioni più efficaci allo scopo. L’ elaborato si occupa di applicare questo strumento a un caso di studio reale al fine di conseguire diversi obbiettivi. Lo studio è suddiviso in quattro steps. Il primo è improntato a capire quali sono gli aspetti che più influiscono sull’efficienza energetica. A tale scopo sono state svolte numerose simulazioni con diversi settings (e.g. g-value, file climatici) e confrontando i risultati è stato possibile individuare i parametri che maggiormente incidono sui fabbisogni termici. Il secondo con lo scopo di comparare i risultati ottenuti con quelli da metodo Relazione Legge 10. Questo processo è stato il più corposo e, a sua volta, è suddiviso in diverse fasi. Si è iniziato analizzando le differenze di calcolo nei due diversi approcci, si è proseguito confrontando i risultati e si è concluso analizzando l’influenza delle differenze riscontrate sui termini del bilancio energetico. Il terzo step è stata la presentazione di una proposta con dei settings più realistici. Infine, il quarto e ultimo step, ha avuto lo scopo di testare la resilienza del sistema energetico ai cambiamenti climatici. I risultati emersi sono: le condizioni al contorno del modello incidono per oltre il 20%; le differenze tra approccio dinamico e semi-stazionario si quantificano in una variazione attorno al 10% per il fabbisogno di riscaldamento e attorno al 20% per quello di raffrescamento; utilizzare dei settings realistici permette di ottenere dei fabbisogni minori di oltre il 10%; in ultimo in chiave futura la richiesta di energia termica di raffrescamento aumenterà del 70% circa rendendo necessaria una progettazione improntata verso una diversa necessità. In chiusura allo studio è stato analizzato nel dettaglio il fattore di utilizzazione. Calcolando il valore che esso avrebbe dovuto assumere per restituire dei valori di fabbisogno termico simili a quelli letti in output da simulazione dinamica e data la difficoltà di lettura del suo andamento in relazione ai fattori da cui dipende si è deciso di provare a sviluppare una nuova formula per il suo calcolo con l’obbiettivo di trovare una relazione di semplice lettura che permettesse di ottenere dei risultati migliori e più vicini a quelli delle simulazioni dinamiche. Il risultato è una formula grazie alla quale si sono ottenuti dei fabbisogni termici annui che si discostano dagli output TRNSYS di un valore nel range del 10% contro il 30% circa di quelli ottenuti con il calcolo standard.
Analisi energetica dinamica a supporto della progettazione di un nuovo distretto resiliente ai cambiamenti climatici e confronto con calcolo semi-stazionario
BARTESAGHI, ANDREA
2022/2023
Abstract
Nowadays in Italy, domestic heating and cooling still contributes significantly to pollution and overheating of cities. This occurs because most of the buildings in the area were built without paying attention to containing energy consumption. The European directives under discussion (e.g. EPBD) impose ambitious objectives for the reduction of energy consumption and greenhouse gas emissions and the means for their fulfilment is energy efficiency. Dynamic energy simulations are the tool which, thank to accurate models of building-plant system, guide us toward the most effective solutions for this purpose. The paper deals with applying this tool to a real case study to achieve different objectives. The study is divided into four steps. The first is based on understanding which aspects have the greatest influence on energy efficiency. For this purpose, numerous simulations were carried out with different settings (g-value, climatic files) and by comparing the results it was possible to identify the parameters that most affect the thermal requirements. The second with the aim of comparing the results obtained with those of “Law 10 Report”. This process was the most substantial and it is divided into several phases. We began by analysing the calculation differences in the two different approaches, continued by comparing the results and concluded by analysing the influence of the differences found on the energy balance. The third step was the presentation of a proposal with more realistic settings. Finally, the fourth and final step, was aimed at testing the resilience of the energy system to climate changes. The results that emerged are: the boundary conditions of the model account for more than 20%; the differences between dynamic and semi-stationary approach are quantified in a variation of around 10% for heating requirement and around 20% for cooling one; using realistic settings allows to obtain lower needs of more than 10%. Lastly, in the future, the demand for cooling thermal energy will increase by around 70%, making it necessary to design based on different needs. At the end of the study, the utilization factor was analysed in detail. By calculating the value that it should have taken to return heat requirement values similar to those read in the output from dynamic simulation given the difficulty of reading its trend in relation to the factors on which it depends, it was decided to try developing a new formula for its computation with the aim of finding an easy-to-read relationship that would allow to obtain better results closer to dynamics simulations ones. The result is a formula which makes it possible to obtain annual thermal requirements which deviate from the TRNSYS outputs by a value in a range of 10% against approximately 30% of those calculated with the standard procedure.File | Dimensione | Formato | |
---|---|---|---|
2023_05_Bartesaghi_Executive Summary_02.pdf
accessibile in internet solo dagli utenti autorizzati
Dimensione
1.13 MB
Formato
Adobe PDF
|
1.13 MB | Adobe PDF | Visualizza/Apri |
2023_05_Bartesaghi_Tesi_01.pdf
accessibile in internet solo dagli utenti autorizzati
Dimensione
28.27 MB
Formato
Adobe PDF
|
28.27 MB | Adobe PDF | Visualizza/Apri |
I documenti in POLITesi sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/10589/211770