Nowadays, due to the growing interest in improving building energy performance, energy models and simulation tools offer new chances to manage the increasing complexity of environments such as nearly Zero-Emission Buildings (nZEBs) and Smart Buildings (SBs). These tools enable us to accelerate innovation cycles, rapidly exploring and exploiting new potential solutions that range from the use of geothermal to air heat pumps, photovolitac systems and controlled mechanic ventilation. In this scenario, it is very relevant to quantify the importance of model inputs and their interactions with respect to model outputs. This paper presents a Global Sensitivity Analysis (GSA) of the software SAFE (Sensitivity Analysis For Everybody)-based first-principle dynamic model of a Living Lab on ZEBs available at the University of Padova (Italy). As opposed to a local view, the GSA provides an overall view of the influence of inputs on outputs, indeed all the model input factors are varied simultaneously, and the sensitivity is evaluated over the entire range of each input factor. Specifically, amidst the many mathematical techniques available in the literature, this preliminary research study leverages the Morris method to perform the GSA because of its simplicity and low computational cost. In this way, one quantifies the variability in model predictions resulting from the uncertainty in multiple input factors, shedding light on the complex characteristics of this kind of buildings from the energy point of view.
Nowadays, due to the growing interest in improving building energy performance, energy models and simulation tools offer new chances to manage the increasing complexity of environments such as nearly Zero-Emission Buildings (nZEBs) and Smart Buildings (SBs). These tools enable us to accelerate innovation cycles, rapidly exploring and exploiting new potential solutions that range from the use of geothermal to air heat pumps, photovolitac systems and controlled mechanic ventilation. In this scenario, it is very relevant to quantify the importance of model inputs and their interactions with respect to model outputs. This paper presents a Global Sensitivity Analysis (GSA) of the software SAFE (Sensitivity Analysis For Everybody)-based first-principle dynamic model of a Living Lab on ZEBs available at the University of Padova (Italy). As opposed to a local view, the GSA provides an overall view of the influence of inputs on outputs, indeed all the model input factors are varied simultaneously, and the sensitivity is evaluated over the entire range of each input factor. Specifically, amidst the many mathematical techniques available in the literature, this preliminary research study leverages the Morris method to perform the GSA because of its simplicity and low computational cost. In this way, one quantifies the variability in model predictions resulting from the uncertainty in multiple input factors, shedding light on the complex characteristics of this kind of buildings from the energy point of view.
Analisi di sensitività globale applicata a un modello di simulazione energetica dinamica: il caso studio del prototipo UniZEB
RICCARDI, BEATRICE
2021/2022
Abstract
Nowadays, due to the growing interest in improving building energy performance, energy models and simulation tools offer new chances to manage the increasing complexity of environments such as nearly Zero-Emission Buildings (nZEBs) and Smart Buildings (SBs). These tools enable us to accelerate innovation cycles, rapidly exploring and exploiting new potential solutions that range from the use of geothermal to air heat pumps, photovolitac systems and controlled mechanic ventilation. In this scenario, it is very relevant to quantify the importance of model inputs and their interactions with respect to model outputs. This paper presents a Global Sensitivity Analysis (GSA) of the software SAFE (Sensitivity Analysis For Everybody)-based first-principle dynamic model of a Living Lab on ZEBs available at the University of Padova (Italy). As opposed to a local view, the GSA provides an overall view of the influence of inputs on outputs, indeed all the model input factors are varied simultaneously, and the sensitivity is evaluated over the entire range of each input factor. Specifically, amidst the many mathematical techniques available in the literature, this preliminary research study leverages the Morris method to perform the GSA because of its simplicity and low computational cost. In this way, one quantifies the variability in model predictions resulting from the uncertainty in multiple input factors, shedding light on the complex characteristics of this kind of buildings from the energy point of view.File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.12608/40576