Buildings are responsible for 40% of energy consumption and this percentage is expected to grow by 20% within 2035, when more and more people will live in cities always more populated and polluted. The concept of IoT and in particular that of Smart Building has therefore acquired relevant importance, since it represents a strong opportunity for applying energy-efficient solutions to make our society more sustainable. The goal of this master thesis is firstly to understand the current scenario for what concerns needs and requirements that building owners demand to the market and available technologies offered by multinational and start-up companies, and then to build a costs-benefits model that allow potential investors to clearly evaluate the investment they are going to make. The model is at the beginning formulated in general terms, with average values of consumptions and building dimensions. Then, a sensitivity analysis will allow to see the variation of the investment Payback Time, considering different building dimensions, its current energetic class, and the climatic zone in which it has been built. The focus is in particular on the Italian territory and the main goal is to make it possible for users to take better decisions according to specific and different contexts and requirements.
Gli edifici sono responsabili del 40% dei consumi energetici e, secondo diversi studi, questa percentuale crescerà del 20% entro il 2035, quando sempre più persone vivranno in città sempre più popolate ed inquinate. Il concetto di IoT e, in particolare, di Smart Building ha quindi acquistato una notevole rilevanza, in quanto rappresenta una grande opportunità per applicare soluzioni energetiche efficienti al fine di rendere la nostra società più sostenibile. L’obiettivo di questo lavoro di tesi è, innanzitutto, quello di capire quali siano i bisogni che i proprietari di edifici domandano al mercato e le soluzioni tecnologiche offerte da aziende multinazionali e start-up, al fine di costruire un modello costi-benefici che permetta a potenziali proprietari di immobili di valutare con chiarezza l’investimento che hanno intenzione di intraprendere. Il modello è inizialmente formulato considerando valori medi di consumo e di dimensioni dell’edificio. Successivamente, un’analisi di sensitività permetterà di visualizzare l’andamento del Payback Time al variare di diversi parametri del modello: dimensione dell’edificio, classe energetica e zona climatica in cui è stato costruito. Il focus è in particolare sul territorio italiano e l’obiettivo principale è quello di consentire agli utilizzatori di prendere decisioni migliori a seconda del contesto in cui operano e di bisogni molteplici e differenti.
Internet of Things & energy management : a model to assess costs and benefits of smart building projects
MAZZA, ANDREA;NEGRI, CARLO
2016/2017
Abstract
Buildings are responsible for 40% of energy consumption and this percentage is expected to grow by 20% within 2035, when more and more people will live in cities always more populated and polluted. The concept of IoT and in particular that of Smart Building has therefore acquired relevant importance, since it represents a strong opportunity for applying energy-efficient solutions to make our society more sustainable. The goal of this master thesis is firstly to understand the current scenario for what concerns needs and requirements that building owners demand to the market and available technologies offered by multinational and start-up companies, and then to build a costs-benefits model that allow potential investors to clearly evaluate the investment they are going to make. The model is at the beginning formulated in general terms, with average values of consumptions and building dimensions. Then, a sensitivity analysis will allow to see the variation of the investment Payback Time, considering different building dimensions, its current energetic class, and the climatic zone in which it has been built. The focus is in particular on the Italian territory and the main goal is to make it possible for users to take better decisions according to specific and different contexts and requirements.File | Dimensione | Formato | |
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2017_12_Mazza_Negri.pdf
non accessibile
Descrizione: Testo della tesi
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https://hdl.handle.net/10589/136961