GCRI · Cities and Built Environment

Energy technology for buildings

Energy technologies shape how buildings are heated, cooled and powered, and how much they emit. In this field they cover efficient cooling, building envelopes, rooftop solar and district energy as means to reduce heat risk, energy poverty and emissions.

02Application

What energy generation, storage and grid technology does here.

Energy generation, storage and grid technology cover the devices and systems that produce, store and deliver energy. They shape the reliability, cost and emissions of energy supply on which all other sectors rely. In cities and built environment, critical infrastructure and society and human development, energy technology assessment informs transition pathways that keep supply reliable during shocks. It links climate, materials and financial risks in the energy system. The canonical description is on the STEM Commons.

Building energy and overheating

Building simulation compares insulation, shading and ventilation options for both winter energy use and summer overheating in common housing types.

Rooftop solar potential

Roof geometry from building footprints and elevation data is combined with solar radiation to estimate rooftop generation potential by neighbourhood.

Energy poverty mapping

Income, housing and energy price data identify households unable to afford adequate heating or cooling.

03Geography

Energy now in India.

Night lights, population density and sunlight over India, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Energy now, for this page

About this layer
Evidence
Observed
Source
VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
Provider
NASA LAADS DAAC
Licence
NASA open data
Vintage
daily; Satellite radiance, corrected for moonlight and atmosphere
Newest at build
2026-10-12
Resolution
about 500 m grid
Uncertainty
Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Estimated
Source
Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
Provider
NASA SEDAC (CIESIN, Columbia University)
Licence
CC BY 4.0
Vintage
null; Census-based estimate, static (2020)
Resolution
about 1 km grid
Uncertainty
Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest month GIBS publishes)
Source
MERRA-2 (NASA GMAO / GES DISC)
Provider
NASA GMAO / GES DISC
Licence
NASA open data
Vintage
monthly; Reanalysis model; latest month GIBS publishes
Newest at build
2026-07-01
Resolution
about 2 km grid
Uncertainty
Reanalysis model estimate of monthly mean incoming sunlight over land; an indicator of solar resource, not a site yield assessment.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed
Source
VIIRS NOAA-20 corrected reflectance (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite image
Newest at build
2026-10-14
Resolution
about 250 m grid
Uncertainty
Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Modelled (latest year GIBS publishes)
Source
MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
Provider
NASA LP DAAC
Licence
NASA open data
Vintage
yearly; Satellite classification; latest year GIBS publishes
Newest at build
2024-01-01
Resolution
about 500 m grid
Uncertainty
Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
Evidence
Observed (clouds leave gaps)
Source
VIIRS NOAA-20 (NASA LANCE)
Provider
NASA LANCE
Licence
NASA open data
Vintage
daily; Satellite retrieval; clouds leave gaps
Newest at build
2026-10-14
Resolution
about 1 km grid
Uncertainty
Satellite skin temperature of the ground on the day shown, an indicator of cooling demand; not air temperature or a heat warning.
Reached through
gibs.earthdata.nasa.gov, only after you allow the live map

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Energy now, framed on India.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA/NOAA VIIRS · NASA JPL OPERA DIST-ALERTSources and licences

  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • MERRA-2 reanalysis, NASA Global Modeling and Assimilation Office; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Observed (EO): NASA/NOAA VIIRS (Suomi NPP). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA’s Global Imagery Browse Services (GIBS), part of NASA’s Earth Science Data and Information System (ESDIS).
  • Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
  • Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
  • Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
  • Optional layers (10 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Incoming sunlight at the surface over land, monthly mean: MERRA-2, NASA GMAO / GES DISC · July 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Land surface temperature, day: VIIRS NOAA-20, NASA LANCE · 13 Oct 2026

04Data

What the method consumes.

Datasets and records used by energy generation, storage and grid technology on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
Building stock dataArchetypesPublished statistics
Solar radiation datasetsPotentialMODELLED
Household energy surveysUse and spendingREPORTED
05Monitor

Power flow study.

The screen a team would use to follow this method: its measures, states and decisions. Names are examples and values are illustrative.

Power flow study

Cities · Energy technology for buildings · Run R-9488

  • Voltage range
    0.95to 1.05 puNormal
  • Losses
    1.9pct of load
  • Converged in
    5iterationsNormal
Two branches above 90 pctGCRI · Cities and Built Environment

Single-line diagram

example network

Branch loading

L1-277348Normal
L2-594356High
L3-461435Normal
T7102187Overload
Power flow study: the screen’s structure, terms and states for Cities.Example names and illustrative values; a design, not a record or a live system.
06Validation

How results are checked.

Technologies are evaluated through pilot deployments, standard testing and operational monitoring. Model results are compared with metered performance.

CheckHow it is done
Simulation calibrationBuilding models are calibrated against metered energy use
Overheating criteriaOverheating is assessed against stated adaptive comfort criteria
Survey representativenessEnergy surveys are checked for coverage of low-income households

Performance under extreme weather and at large scale may differ from tests. Supply chains for components and minerals are concentrated.

07Simulator

A cascade through interdependent networks.

A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows India; the model itself is not tied to a place.

Controls

Assets per layer
18
Hazard footprint
8% of area
Assets that depend on another layer
60%
Spare capacity (tolerance)
30%

Readouts

Assets hit by the hazard
6%
Assets still working
76%
Amplification of the initial damage
4.3 times
Steps to settle
1
Numbers, methods and sources
StepTransport working (%)Power working (%)Telecoms working (%)
08994100
17850100

Methods

  1. Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
  2. Overload cascades Motter and Lai (2002), Physical Review E 66
  3. Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
  4. Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
  5. Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
  6. Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
  7. One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley

Data

The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:

  • Major roads Natural Earth
  • Railways Natural Earth
  • Seaports Natural Earth
  • Airports Natural Earth
  • Urban extents Natural Earth
  • Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
  • Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
A cascade through interdependent networks. Illustrative teaching model: it runs on the values set by the controls, not on measured data. Methods: Interdependent networks (Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464); Overload cascades (Motter and Lai (2002), Physical Review E 66); Betweenness load (Brandes (2001), Journal of Mathematical Sociology 25).
08Connections

Topics that rely on this method.

09Twin and cascade simulator

Model energy technology for buildings as a system. Run the cascade.

Assembled from the Nexus Standards area profile Cities and the built environment: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

  • Ice-jam flood
  • Earthquake
  • Dam failure
  • Aftershock sequence (set off downstream)
  • Fault surface rupture (set off downstream)
  • Soil liquefaction (set off downstream)
  • Slope slide (set off downstream)
  • Rockfall (set off downstream)
  • Tsunami (set off downstream)
  • Building collapse (set off downstream)
  • Widespread power outage (set off downstream)
  • Water supply failure (set off downstream)
  • Mass displacement (set off downstream)
  • Disaster and conflict debris (set off downstream)
  • River flood (set off downstream)
  • Flash flood (set off downstream)
  • Turbidity current (set off downstream)
  • Seismically and structurally vulnerable stock (set off downstream)

Controls

  • NS-0 Constitution and principles
  • NS-3 Risk record UNIs (grammar, legacy crosswalk, allocation authority)
  • NS-5 Figure, map and visualisation standard (with the UI/UX kit)
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-10 Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NRS-X5 Cities and built environment risk
  • NRS-H91 Hazard family: Urban and building-stock stress (NHS-1 infra.urban)
  • NRS-H113 Hazard family: Financial-system fragility (NHS-1 soc.financial-system)
  • NRS-K7 Domain pack profile: Cities urban (DOMAIN-007)
  • NRS-H31 Hazard family: Persistent and bioaccumulative substances (NHS-1 poll.persistent)
  • NRS-H34 Hazard family: Waste and residue failures (NHS-1 poll.waste)

Observation

  • Global Human Settlement Layer (listed for reference)
  • WorldPop gridded population (listed for reference)
  • Overture Maps buildings theme (listed for reference)
  • OpenStreetMap (listed for reference)
  • World Development Indicators (listed for reference)
  • Direct economic loss in relation to global GDP, damage to critical infrastructure and number of disruptions to basic services, attributed to disasters
  • Proportion of local governments that adopt and implement local disaster risk reduction strategies in line with national strategies
  • Proportion of urban population living in slums, informal settlements or inadequate housing
  • Percentage of local governments that adopt and implement local disaster risk reduction strategies in line with national strategies

Example geography

  • India: 65 hexagonal cells
  • Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
  • Rain rate, last half hour (IMERG), NASA GIBS
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Surface soil moisture (SMAP), NASA GIBS
10Stewardship

Who maintains the method.

Energy Nexus stewards energy generation, storage and grid technology for the Consortium and reviews how it is applied across platforms.

11Sector signature

The sector signature of energy technology for buildings.

The sectors energy technology for buildings touches and how strongly they depend on each other: what a study has to observe and model together.

Select corners · hover lines6 / 15 relations

Signature

Energy and its partners

Energy gives power for transport and telecoms to infrastructure (0.8), pumping and treatment to water (0.5) and fertiliser, machinery and cold chains to food (0.5).

W · E · I · F · H · B

Sectors
4 of 6
Relations
6 of 15
Coupling
0.46 share of total

Strongest relations in play

  • Energy → Infrastructure · power for transport and telecoms0.8
  • Water → Energy · cooling water and hydropower0.6
  • Water → Food · irrigation0.8
  • Infrastructure → Water · pipes, dams and treatment works0.6
Teaching values for a typical city-region, not measurements for any place. Coupling is the summed strength of the relations in play, as a share of all fifteen.
12Connected

Where this page leads across the Consortium.

13Methods and evidence

How energy technology for buildings is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

System model

The couplings between the systems in energy technology for buildings: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.

++−++CitiesCritical infrastructureSocietyCommunitiesEconomyR reinforcingB balancing
Causal loop diagram from the page’s systems; signs show the direction of influence. Illustrative structure for a system dynamics or network model, not estimated couplings.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
14Questions

Questions and answers.

What are the limits of energy generation, storage and grid technology in this field?
Performance under extreme weather and at large scale may differ from tests. Supply chains for components and minerals are concentrated.
How are results checked?
Technologies are evaluated through pilot deployments, standard testing and operational monitoring. Model results are compared with metered performance.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
ReportsContribute

Contribute evidence from this page.

Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

GCRICities and Built EnvironmentGlobal Sector Risk and ResilienceEvidence Brief
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Our articles, maps and twins are free to read and free to republish. Readers and partners keep it that way.

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Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.

Licence

Articles: CC BY 4.0. Figures, maps, twins and data: CC BY 4.0. Other uses: ask through the permissions form.