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Buildings and Cities: Difference between revisions
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=== Optimizing buildings ===
*'''[[Energy Demand Forecasting|Forecasting energy loads]]:''' The supply and demand of electric and thermal loads must be forecast ahead of time to inform electricity planning and scheduling. ML can help make these forecasts more accurate, improve temporal resolution, and quantify uncertainty.
*'''[[Non-Intrusive Load Monitoring|Non-Intrusive Load Monitoring (NILM)]]:''' A better understanding of the own energy consumption can lead to better energy efficiency by changing one's behavior or exchanging inefficient devices. ML can help to disaggregate a household's smart meter data and attribute energy consumption to individual devices for increased transparency.
*'''[[Controlling HVAC and lighting systems]]:''' Current building energy management systems are manually designed by human operators, which leads to energy inefficient operations. ML can help develop predictive models of building energy systems, leading to efficient building operation via advanced model-based optimal control methods.
*'''Fault detection and [[Predictive Maintenance|predictive maintenance]] in building systems:''' Buildings are embedded with complex engineering systems in dynamic interplay. Component's malfunctions are a constant threat to the building operations economics and comfort and safety of human occupants. ML can help to transfer from reactive maintenance to predictive maintenance and cut the maintenance cost by prolonging the remaining useful life of building engineering systems.
*'''[[Demand response]] and [[energy social games]]:''' There are opportunities to reduce the GHG emissions due to energy consumption in building by adapting the demand to when the share of renewable energy on the grid is higher and lower. ML provides tools to enable automatic demand response to current supply conditions, it also provides ways for users to optimize their demand based incentives.
*'''[[AI-guided building design and planning]]:''' Current building designs are drawn by the joined hands of the architect, mechanical, electrical, and control engineers using various computer-aided design tools. ML can help to navigate and optimize complex design landscapes, often balancing conflicting requirements such as energy efficiency, comfort, and cost.
*'''[[Sector-coupled districts and district heating systems]]''': To achieve decarbonization across the heating, electricity, and mobility sectors, they are increasingly coupled within districts in a joint spatial and organizational context. ML can help by providing surrogate models of thermal processes and quantify uncertainties of loads, supply, and mobility behavior.
*'''[[Surrogate modeling]]''': Building energy simulation (BES) programs are software tools that simulate the complex physics of buildings and are key enabling tools for R&D in the building's domain. However, detailed BES models are notoriously difficult to design, tune and typically have high computational demands. ML, in conjunction with physics, can help to build accurate yet computationally efficient surrogate models for faster simulations.
=== Urban planning ===
* '''Mapping [[Built-up infrastructure mapping|built-up]] and [[Energy Infrastructure Mapping|energy]] infrastructure:''' Decarbonizing the building and urban transportation sectors requires accurate mapping of the existing infrastructure but there are large data gaps. ML can help generate such data from remote sensing and existing maps.
* '''Macro-scale [[Macro-scale energy demand assessment in cities|energy demand]] and [[Greenhouse Gas Emissions Detection|GHG emissions]] assessment in cities:''' While some electricity system operators release publicly-available data on energy use and the emissions associated with fossil fuel generators, this data is not available in many cases. ML can help map greenhouse gas emissions using remote sensing and/or on-the-ground data.
* '''[[Identifying building retrofit needs]]:''' For reducing energy use for thermal comfort in buildings, many buildings need to be retrofitted to increase their thermal performance. ML can help pinpoint which buildings and which specific parts of buildings would yield the best performance gains.
* '''[[Designing Low-Carbon Urban Form|Designing Low-Carbon Urban Form]]:''' Urban form, the physical form of cities, has important implications of energy use and GHG emissions, for example sprawled cities can induce mobility demand. ML can help analyze energy use implications of different urban forms, simulate urban development pathways and (re-)designing neighborhoods by finding patterns in urban form data.
=== The future of cities ===
*'''[[Efficient sensing]]:''' The proliferation of sensors poses the question of how to minimize the energy use related to capturing, sending and storing the data. ML can help recognize what is the most information, possibly on the edge, make sensing more efficient.
*'''[[Causal inference]] of policy interventions:''' The effect of policy interventions are often uncertain, and it is important to evaluate them to evaluate their effectiveness. Causal inference methods in ML can help observe the effects of policies from observational data.
*'''[[Assessing urban climate]]:''' Cities have an influence on their local climate -- which they tend to make hotter -- which has important implications for climate change mitigation and adaptation. ML can help investigate climatic processes in cities at high-resolution and how they related to the built infrastructure.
*'''[[Enabling nature-based solutions in cities]]:''' Nature-based solutions, for example planting trees, can provide multiple benefit including sequestrating carbon and providing cooling. ML can help assess what is the current vegetation in cities and pinpoint opportunities for planting trees.
*'''[[Predictive Maintenance|Predictive maintenance]] of public infrastructure:''' Public infrastructure, for example street lighting, can include a large amount of individual components that are difficult to monitor. ML can help predict which components are more likely to be dysfunctional to ease maintenance operations.
=== Urban transportation ===
''Main article: [[Transportation]]''
Urban transportation is of high relevance to mitigating climate change in cities, as mobility within cities represents a large share of the total final energy use in the transportation sector (40% in 2010<ref>{{Cite book|title=Policy Pathways: A Tale of Renewed Cities. International Energy Agency|last=IEA|first=|publisher=|year=2013|isbn=|location=Paris|pages=98}}</ref>). Transportation topics are treated as a separate [[Transportation|section]] of the wiki, where areas of particular relevance include:
* '''[[Understanding mobility patterns]]'''
* '''[[Enabling low-carbon shared mobility]]'''
* '''[[Electric vehicle charging infrastructure]]'''
* '''[[Fostering urban cycling]]'''
* '''[[Supporting public transportation network expansion]]'''
== Background Readings ==
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=== Academic perspectives ===
*'''Advances Toward a Net-Zero Global Building Sector''', Ürge-Vorsatz et al. (2020)<ref>Ürge-Vorsatz, Diana, et al. "Advances toward a net-zero global building sector." ''Annual Review of Environment and Resources'' 45 (2020): 227-269.https://doi.org/10.1146/annurev-environ-012420-045843</ref>: An authoritative review of the existing academic and professional literature towards decarbonizing the building sector globally.
*'''Six research priorities for cities and climate change''', Bai, X., et al. (2018)<ref>{{Cite journal|last=Bai|first=Xuemei|last2=Dawson|first2=Richard J.|last3=Ürge-Vorsatz|first3=Diana|last4=Delgado|first4=Gian C.|last5=Barau|first5=Aliyu Salisu|last6=Dhakal|first6=Shobhakar|last7=Dodman|first7=David|last8=Leonardsen|first8=Lykke|last9=Masson-Delmotte|first9=Valérie|last10=Roberts|first10=Debra C.|last11=Schultz|first11=Seth|date=2018-03|title=Six research priorities for cities and climate change|url=https://www.nature.com/articles/d41586-018-02409-z|journal=Nature|language=en|volume=555|issue=7694|pages=23–25|doi=10.1038/d41586-018-02409-z}}</ref>: Leading urban sustainability researchers call for long-term, cross-disciplinary studies to reduce carbon emissions and urban risks from global warming.
*'''Sustainability in an urbanizing planet''', by Seto, K C., et al. (2017)<ref>{{Cite journal|last=Seto|first=Karen C.|last2=Golden|first2=Jay S.|last3=Alberti|first3=Marina|last4=Turner|first4=B. L.|date=2017-08-22|title=Sustainability in an urbanizing planet|url=https://www.pnas.org/content/114/34/8935|journal=Proceedings of the National Academy of Sciences|language=en|volume=114|issue=34|pages=8935–8938|doi=10.1073/pnas.1606037114|issn=0027-8424|pmid=28784798}}</ref>: This introduction to a special issue in PNAS enumerates key common themes, knowledge gaps and research priorities towards sustainability in an urbanizing planet.
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* '''Set of courses on Sustainable Buildings Systems''', by TU Delft, on edX: Learn about different ways to reduce energy use in buildings without compromising occupant comfort, in a series of courses from a leading Dutch university. Courses available on [https://www.edx.org/course/energy-needs-in-buildings-2 Energy Demand in Buildings], [https://www.edx.org/course/distribution-and-control-of-heat-cold-and-air-flows-in-buildings Efficient HVAC Systems], [https://www.edx.org/course/energy-conversion-systems-for-buildings Energy Supply Systems for Buildings] and more on the edX website.
==Conferences, Journals, and Professional Organizations==
===Major conferences===
'''Building modeling and control'''
*'''[https://bs2021.org/ Building Simulation]:''' With focus on advances in building physics modeling, estimation, and control. Co-organized by International Building Performance Simulation Association (IBPSA).
*'''[http://buildsys.acm.org/ BuildSys: ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation]:''' Is a highly selective, single track forum for researchers and practitioners working on systems' issues for energy-efficient buildings, cities, and transportation driven by networked sensing, computing, and control functions.
*'''[https://www.ashrae.org/conferences/topical-conferences/2020-building-performance-analysis-conference-simbuild Building Performance Analysis Simbuild Conference]:''' With focus on decision making process through the application of simulation and modeling over the entire building life cycle, from the earliest concept through operation and maintenance to achieve the goals of zero energy, zero carbon, or other high performance targets. Co-organized by ASHRAE and IBPSA-USA.
* '''[https://www.nmpc2021.org/ IFAC Conference on Nonlinear Model Predictive Control]:''' Control community conference with regular special sessions on Heating, ventilation, air conditioning (HVAC) control.
* '''[http://acc2020.a2c2.org/ American control conference]:''' Control community conference with regular special/invited sessions on Heating, ventilation, air conditioning (HVAC) control.
=== Major journals ===
* '''[https://www.journals.elsevier.com/energy-and-buildings/ Energy and Buildings]:''' Is an international journal publishing articles with explicit links to energy use in buildings. The aim is to present new research results, and new proven practice aimed at reducing the energy needs of a building and improving indoor environment quality.
* '''[https://www.journals.elsevier.com/applied-energy/ Applied Energy]:''' Provides a forum for information on innovation, research, development and demonstration in the areas of energy conversion and conservation, the optimal use of energy resources, analysis and optimization of energy processes, mitigation of environmental pollutants, and sustainable energy systems.
* '''[https://www.journals.elsevier.com/building-and-environment Building and Environment]:''' ''Building and Environment'' is an international journal that publishes original research papers and review articles related to building science, urban physics, and human interaction with the indoor and outdoor built environment.
* [https://www.tandfonline.com/toc/tbps20/current '''Journal of Building Performance Simulation''']: Publishes international research on building performance simulation including modelling and simulating thermal processes, energy conversion and weather data.
* '''[https://www.springer.com/journal/12273 Building Simulation]:''' Publishes original, high quality, peer-reviewed research papers and review articles dealing with modeling and simulation of buildings including their systems.
* '''[https://www.journals.elsevier.com/renewable-and-sustainable-energy-reviews/ Renewable and Sustainable Energy Reviews]:''' The aim of the journal is to share problems, solutions, novel ideas and technologies to support the transition to a low carbon future and achieve our global emissions targets as established by the United Nations Framework Convention on Climate Change.
* '''[https://www.journals.elsevier.com/energy/ Energy]:''' Is an international, multi-disciplinary journal in energy engineering and research. The journal aims to be a leading peer-reviewed platform and an authoritative source of information for analyses, reviews and evaluations related to energy.
* '''[https://www.mdpi.com/journal/energies Energies]:''' Is an open access journal of related scientific research, technology development, engineering, and the studies in policy and management.
* '''[https://www.journals.elsevier.com/automation-in-construction Automation in Construction]:''' The journal publishes refereed material on all aspects pertaining to the use of Information Technologies in Design, Engineering, Construction Technologies, and Maintenance and Management of Constructed Facilities.
* '''[https://onlinelibrary.wiley.com/journal/16000668 Indoor Air]:''' An international journal with multidisciplinary content, publishes papers reflecting the broad categories of interest in the field of indoor air quality.
* '''[https://www.journals.elsevier.com/journal-of-process-control/ Journal of Process Control]:''' This international journal covers the application of control theory, operations research, computer science and engineering principles to the solution of process control problems. The scope of process control problems involves a wide range of applications that includes energy processes, energy storage and conversion, smart grid, and data analytics among others.
===Major societies and organizations===
==Libraries and Tools==▼
* '''[https://www.globalcovenantofmayors.org/ The Global Covenant of Mayors for Climate & Energy]:''' GCoM is the largest global alliance for city climate leadership, built upon the commitment of over 10,000 cities and local governments.
* '''[https://globalabc.org/ The Global Alliance for Buildings and Construction (GlobalABC)]:''' With over 130 members, including 29 countries, the GlobalABC is a leading global platform for governments, the private sector, civil society and intergovernmental and international organizations to increase action towards a zero-emission, efficient and resilient buildings and construction sector.
* '''[https://nacto.org/ National Association of City Transportation Officials (NACTO)]:''' NACTO’s mission is to build cities as places for people, with safe, sustainable, accessible, and equitable transportation choices that support a strong economy and vibrant quality of life.
* https://buildings.lbl.gov/cbs/bpd<nowiki/>The Global GCTC program is a collaborative platform for the development of smart cities and communities, led by National Institute of Standards and Technology (NIST) which enables local governments, nonprofit organizations, academic institutions, technologists, and corporations from all over the world to work onInternet of Things (IoT) and Cyber-Physical Systems (CPS) applications within the city and community environment.
* '''[http://www.ibpsa.org/ International Building Performance Simulation Association (IBPSA)]:''' Is a non-profit international society of building performance simulation researchers, developers and practitioners, dedicated to improving the built environment.
* [https://www.ashrae.org/ '''The American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE)''']: Organization with a mission on advancing the arts and sciences of heating, ventilation, air conditioning, refrigeration and their allied fields.
* [https://www.asme.org/ '''The American Society of Mechanical Engineers (ASME)''']: Serves a wide-ranging engineering community through quality learning, the development of codes and standards, certifications, research, conferences and publications, government relations, and other forms of outreach. Mechanical engineering plays a crucial role in building HVAC systems design, modeling, and control.
*[https://www.ifac-control.org/ '''International Federation of Automatic Control (IFAC)''']: Multinational federation is concerned with automatic control and its representation in the fields of engineering, science and the impact of control technology on society. Building energy systems are one of the prominent applications spaces of the community.
▲==Libraries and Tools==
{{SectionStub}}
==Data==
=== Building energy use ===
* '''[https://buildings.lbl.gov/cbs/bpd Building Performance Database]:''' The largest publicly-available collection of measured energy performance data for buildings in the United States, curated by the Berkeley Lab.
* '''[https://data.cityofnewyork.us/City-Government/NYC-Municipal-Building-Energy-Benchmarking-Results/hpid-63r5
* '''[https://catalog.data.gov/dataset/commercial-buildings-energy-consumption-survey The Commercial Buildings Energy Consumption Survey (CBECS)]:'''
* '''[https://ec.europa.eu/energy/eu-buildings-database_en EU Buildings Database]''': A database with country-level information on the buildings and their energy performance in the European Union.
* '''[https://trynthink.github.io/buildingsdatasets/ Datasets from the Department of Energy]''': A list of datasets including Building Operations Data, Building Stock & Energy Data and Developer Resources.
* '''[http://episcope.eu/building-typology/overview The TABULA project]:'''
* '''[https://data.openei.org/submissions/2977 AlphaBuilding - Synthetic Dataset]:''' A synthetic building operation dataset that includes HVAC, lighting, electric loads, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals.
=== City metabolism ===
''The "metabolism" of a city includes the electricity used, waste generated, and GHG emitted.''
* '''[https://metabolismofcities.org/resources/data/datasets Metabolism
* '''The [http://www.ceads.net/ China Emission Accounts & Datasets]:''' This page provides energy, emission and socio-economic accounting inventories for China
* [https://www.nature.com/articles/sdata2018280
* '''The [https://www.cdp.net/ Carbon Disclosure Project]:'''
=== Urban Land Use, Infrastructure Data ===
* '''[https://www.openstreetmap.org/ OpenStreetMap]:''' OSM is a cooperative alternative to Google Maps where all the data is open access.
* '''[http://atlasofurbanexpansion.org/ NYU’s Atlas of Urban Expansion]:'''
* '''[http://www.citygmlwiki.org/index.php?title=Open_Data_Initiatives Open 3D models]:''' 3D models of buildings are available for a few cities, mostly in Europe.
* '''[https://land.copernicus.eu/local/urban-atlas The Urban Atlas of the European Union agency Copernicus]:'''
▲* [http://episcope.eu/building-typology/overview The TABULA project] combines data on building types across all of Europe.
==References==
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