95861 - LOW-ENERGY BUILDINGS AND CITIES

Conoscenze e abilità da conseguire

Al termine del modulo lo studente conosce i principi e le metodiche per ottimizzare il comportamento energetico e i livelli di comfort di edifici e complessi.

Contenuti

This course considers the problem of design resilient cities considering evolving climate conditions, urban morphology, physical properties of built environment and user behaviour. It will comprise the following topics:

1. An introduction to the Earth’s climate system and climatic zones classification (global circulation model and Koppen climate classification, web resources).
2. Future scenarios of climate evolution due to climate change and their impact on the built environment and settlements (essential data regarding future climate projections, weather vs climate, short and long-term patterns).
3. Climate data files, standard formats, analysis and morphing for climate change and Urban Heat Island effect (web tools for analysis and other free software for analysis and morphing).
4. Urban Heat Island (UHI) effect, causes and mitigation strategies, measurements and modelling techniques (fundamentals, impact of urban morphology, modelling tools).
5. Modelling building energy behaviour in an urban context, prototype buildings and urban morphology (construction of statistical reference building and simulation using simplified modelling tools, analysing key building characteristics and performance indicators).
6. Modelling aggregated electric and thermal energy demand at urban scale, carbon emission (load profiles analysis, load duration curves, visualization of time series, Sankey diagrams, energy-hubs).

With reference to the single building, the Course will deal with:

Physics of Heat Transfer in Buildings. Thermal Comfort, Air Quality, and Humid Air. HVAC Installation and Control. Infiltration and Ventilation. Energy Calculations for Buildings. Sustainable Smart Low Energy Buildings. Practical Consideration of Low Energy Buildings. Design and Simulation. Optimization of energy use in buildings.

In the case study, students draw geometry, define the walls and ceilings, as well as calculate the U-value, and energy balance. Moreover, they will find the optimal solution for the energy consumption, indoor air quality and HVAC system (heating, ventilation and air conditioning).

Key papers for the creation of the workflow and methodology for project:

• Data acquisition for urban building energy modeling: A review [1].
• Open data and energy analytics - An analysis of essential information for energy system planning, design and operation [2]
• Italian prototype building models for urban scale building performance simulation [3].
• Simplified evaluation metrics for generative energy-driven urban design: A morphological study of residential blocks in Tel Aviv [4]
• From energy performative to livable Mediterranean cities: An annual outdoor thermal comfort and energy balance cross-climatic typological study [5]
• Data-driven modeling of building thermal dynamics: Methodology and state of the art [6].
• Detailed cross comparison of building energy simulation tools results using a reference office building as a case study [7].
• Data-driven estimation of building energy consumption with multi-source heterogeneous data [8].
• Dynamic Assessment of Construction Materials in Urban Building Stocks: A Critical Review [9].
• Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment [10].
• A strategy for reducing CO2 emissions from buildings with the Kaya identity – A Swiss energy system analysis and a case study [11].
• Global scenarios of residential heating and cooling energy demand and CO2 emissions [12]
• Climate change and energy performance of European residential building stocks – A comprehensive impact assessment using climate big data from the coordinated regional climate downscaling experiment [13].
• Quantifying the impacts of climate change and extreme climate events on energy systems [14].

Testi/Bibliografia

[1] Wang C, Ferrando M, Causone F, Jin X, Zhou X, Shi X. Data acquisition for urban building energy modeling: A review. Build Environ 2022;217:109056. https://doi.org/https://doi.org/10.1016/j.buildenv.2022.109056.

[2] Manfren M, Nastasi B, Groppi D, Astiaso Garcia D. Open data and energy analytics - An analysis of essential information for energy system planning, design and operation. Energy 2020;213. https://doi.org/10.1016/j.energy.2020.118803.

[3] Carnieletto L, Ferrando M, Teso L, Sun K, Zhang W, Causone F, et al. Italian prototype building models for urban scale building performance simulation. Build Environ 2021;192:107590. https://doi.org/https://doi.org/10.1016/j.buildenv.2021.107590.

[4] Natanian J, Wortmann T. Simplified evaluation metrics for generative energy-driven urban design: A morphological study of residential blocks in Tel Aviv. Energy Build 2021;240:110916. https://doi.org/https://doi.org/10.1016/j.enbuild.2021.110916.

[5] Natanian J, Kastner P, Dogan T, Auer T. From energy performative to livable Mediterranean cities: An annual outdoor thermal comfort and energy balance cross-climatic typological study. Energy Build 2020;224:110283. https://doi.org/https://doi.org/10.1016/j.enbuild.2020.110283.

[6] Wang Z, Chen Y. Data-driven modeling of building thermal dynamics: Methodology and state of the art. Energy Build 2019;203:109405. https://doi.org/https://doi.org/10.1016/j.enbuild.2019.109405.

[7] Magni M, Ochs F, de Vries S, Maccarini A, Sigg F. Detailed cross comparison of building energy simulation tools results using a reference office building as a case study. Energy Build 2021;250:111260. https://doi.org/https://doi.org/10.1016/j.enbuild.2021.111260.

[8] Pan Y, Zhang L. Data-driven estimation of building energy consumption with multi-source heterogeneous data. Appl Energy 2020;268:114965. https://doi.org/https://doi.org/10.1016/j.apenergy.2020.114965.

[9] Göswein V, Silvestre JD, Habert G, Freire F. Dynamic Assessment of Construction Materials in Urban Building Stocks: A Critical Review. Environ Sci Technol 2019;53:9992–10006. https://doi.org/10.1021/acs.est.9b01952.

[10] Tronchin L, Manfren M, Nastasi B. Energy efficiency, demand side management and energy storage technologies – A critical analysis of possible paths of integration in the built environment. Renew Sustain Energy Rev 2018;95:341–53. https://doi.org/https://doi.org/10.1016/j.rser.2018.06.060.

[11] Mavromatidis G, Orehounig K, Richner P, Carmeliet J. A strategy for reducing CO2 emissions from buildings with the Kaya identity – A Swiss energy system analysis and a case study. Energy Policy 2016;88:343–54. https://doi.org/https://doi.org/10.1016/j.enpol.2015.10.037.

[12] Mastrucci A, van Ruijven B, Byers E, Poblete-Cazenave M, Pachauri S. Global scenarios of residential heating and cooling energy demand and CO2 emissions. Clim Change 2021;168:14. https://doi.org/10.1007/s10584-021-03229-3.

[13] Yang Y, Javanroodi K, Nik VM. Climate change and energy performance of European residential building stocks – A comprehensive impact assessment using climate big data from the coordinated regional climate downscaling experiment. Appl Energy 2021;298:117246. https://doi.org/https://doi.org/10.1016/j.apenergy.2021.117246.

[14] Perera ATD, Nik VM, Chen D, Scartezzini J-L, Hong T. Quantifying the impacts of climate change and extreme climate events on energy systems. Nat Energy 2020;5:150–9. https://doi.org/10.1038/s41560-020-0558-0.

[15] Hugo Hens, Building Physics - Heat, Air and Moisture: Fundamentals and Engineering Methods with Examples and Exercises, Wilhelm Ernst & Sohn (2017)

[16] Marko Pinterić, Building Physics, From physical principles to international standards, Springer (2017)

[17] Trnsys software (www.trnsys.com )

[18] Dalec, Building Energy under control (dalec.zumtobel.com)

[19] Ies software (www.iesve.com )

Metodi didattici

The course is included in the Integrated Course "Making the city resilient" and represents the technical/scientific core of the Integrated Course, whilst the other course "Optimizing economic and environmental effectiveness" represents the economic core

The course will illustrate the concepts and methods for the energy simulation of buildings and districts for a more sustainable design of interventions on the built environment.

The course will be carried out by means of lessons in class and guided laboratory exercises.

Modalità di verifica e valutazione dell'apprendimento

At the end of the course, the students are requested to elaborate a written report. The final exam consists of an oral test, aimed at evaluating the organic understanding of the subject with reference to the key concepts illustrated during the course.

It will be assessed as excellent (27-30) the performance of those students achieving an organic vision of the course contents, the use of a proper specific language, originality of reflection and familiarity with the energy performance of the building tools. It will be assessed as discrete (23-26) the performance of those students showing mostly mechanical or mnemonic knowledge of the subject, disarticulated synthesis and analysis capabilities, or a correct but not always appropriate language, as well as a scholastic study of energy, climate, environment. It will be assessed as barely sufficient (18-22) the performance of those students showing learning gaps, inappropriate language, lack of knowledge of the tools of energy performance of building. It will be assessed as insufficient the performance of those students showing learning gaps, inappropriate language, no orientation within the recommended bibliography and inability to analyze the energy performance of the buildings.

Strumenti a supporto della didattica

Free software for energy and environmental evaluations

Orario di ricevimento

Consulta il sito web di Lamberto Tronchin

Consulta il sito web di Paolo Valdiserri

Consulta il sito web di Alex Lambruschi