GCRI · Critical Infrastructure
Electricity and lifelines
Electricity is the lifeline other lifelines depend on: water pumping, telecommunications, hospitals, fuel distribution, payments and traffic control all stop or degrade when power stops. Outages come from weather, equipment failure, operating errors, cyber incidents and supply shortfalls. This page sets out how power systems fail and recover, how reliability is measured, and what evidence serves the operators and regulators who keep the lights on.
Electricity and lifelines in seven parts.
- 01The questionElectricity and lifelines: how the risk develops
- 02Across the domainsElectricity sits under every other lifeline
- 03IndicatorsWhat is measured, and how well
- 04SourcesWhere the evidence comes from
- 05DecisionsWho decides, and what the evidence serves
- 06Core questionsWhat experts ask
- 07MechanismsDrivers and failure pathways
Electricity and lifelines: how the risk develops.
Dependency of services on power. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Weather damages the network
Wind, ice, heat, flood and wildfire damage lines, substations and generation. Distribution networks, with long exposed overhead lines, account for most customer outage time.
Balance must hold every second
Supply and demand must match continuously. A sudden loss of generation or a line can cause frequency and voltage swings that trip further equipment unless protection and reserves respond.
Other lifelines follow
Backup generators and batteries carry critical loads for hours to days. When fuel runs out or backup is absent, water, telecommunications and health services fail in turn.
Restoration is staged
After a large outage, operators restart generation with black-start units and rebuild the network step by step. Priority customers and dependent lifelines shape the order of restoration.
Energy now in Western Europe.
Night lights, population density and true-colour imagery over Western Europe, 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
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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 Western Europe.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 HLS S30Sources 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 HLS S30 (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
Electricity sits under every other lifeline.
Lifeline studies are designed for the Strategic Systems series. Reliability is reported with IEEE 1366 indices; the 2021 cold-weather outages in Texas showed how gas, power and water failed together.
- Outage records with affected services.
- Restoration priority rules.
Asset criticality register.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Asset criticality register
Electricity and lifelines · Lifeline system A · Register v9
Critical assets
| SS-12 | Electricity | Tier 1 | Flood 1-in-100 | 7 |
| WTW-2 | Water | Tier 1 | Flood 1-in-100 | 28 |
| DX-1 | Telecom | Tier 2 | Heat | 10 |
| H-Campus | Health | Tier 1 | Earthquake | 40 |
| PN-3 | Transport | Tier 2 | Storm surge | n/a |
SS-12 dependencies
- Upstream
- Transmission L4, L7
- Downstream
- WTW-2, H-Campus, DX-1
- Restoration target
- 12 h
- Owner
- Asset owner
Dependency graph
red: SS-12 and its dependants
Restoration time by sector
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| System Average Interruption Duration Index | minutes per customer per year | annual | Utility reliability reports | Published statistics |
| System Average Interruption Frequency Index | interruptions per customer per year | annual | Utility reliability reports | Published statistics |
| Customers without power | count of customers | hourly during events | Utility outage reporting | REPORTED |
| Energy not supplied | megawatt hours | per event | System operator incident reports | Published statistics |
| Reserve margin | percent of peak demand | seasonal | Adequacy assessments | FORECAST |
| Critical facilities with backup power | percent of designated facilities | annual | Facility surveys | REPORTED |
| Restoration time for major events | hours to restore a stated share of customers | per event | Incident reports | OBSERVED |
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 Western Europe; 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
- 4%
- Assets still working
- 69%
- Amplification of the initial damage
- 8.5 times
- Steps to settle
- 1
Numbers, methods and sources
| Step | Transport working (%) | Power working (%) | Telecoms working (%) |
|---|---|---|---|
| 0 | 100 | 94 | 94 |
| 1 | 100 | 56 | 50 |
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
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- 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
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Critical Infrastructure in Foundry
- Tested at Critical Infrastructure in Universe
- Codified in Energy and Critical Infrastructure in Standards
- Published in Critical Infrastructure in Reports
- Taught in Faculty of Infrastructure, Energy and Industry in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| ENTSO-E Transparency Platform | European generation, load, outages and cross-border flows | Free, ENTSO-E terms of use |
| US EIA electric power data and Form OE-417 disturbance reports | Generation data and reports of major electric incidents | Public domain, US government data |
| NERC State of Reliability and seasonal assessments | Analysis of bulk power system performance and adequacy | Public, NERC terms |
| CEER benchmarking reports on quality of electricity supply | Comparable continuity of supply indicators across European regulators | Public, CEER terms |
| World Bank Enterprise Surveys | Firm-reported outages and generator use | Free with registration, World Bank terms |
| Global Energy Monitor trackers | Power plants and infrastructure by location and status | Open, CC BY 4.0 |
Model electricity and lifelines as a system. Run the cascade.
Assembled from the Nexus Standards area profile Critical infrastructure and critical entities: 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
- Dam failure
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
Systems and couplings
- Critical infrastructure and critical entities
- Energy risk standards Dependency
- Space weather, spectrum and timing risk standards Common-mode dependency
- Compound and cascading hazard standards Cascade
- Cyber resilience and digital operational resilience Common driver
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H107Hazard family: Digital infrastructure concentration and monoculture (NHS-1 tech.digital-concentration)NRS-K31Domain pack profile: Cyber national resilience (DOMAIN-031)NRS-K36Domain pack profile: Critical infrastructure (DOMAIN-036)NRS-K48Domain pack profile: Financial system resilience (DOMAIN-048)
Observation
- OpenStreetMap planet and replication (listed for reference)
- Global Power Plant Database (listed for reference)
- NASA Black Marble night-time lights (VNP46) (listed for reference)
- Global Human Settlement Layer (listed for reference)
- Damage to critical infrastructure attributed to disasters
- Number of disruptions to basic services attributed to disasters
- Proportion of the rural population who live within 2 km of an all-season road
Example geography
- Europe: 113 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
Who decides, and what the evidence serves.
Critical Infrastructure prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Transmission and distribution operators | Where to harden, underground or add redundancy | Outage patterns by cause; restoration evidence |
| Energy regulators | Which reliability standards and incentives to set | Continuity indicators compared over time and with peers |
| Emergency management agencies | Which facilities need backup power and fuel priority | Backup endurance reviews; dependency maps |
| System operators | How much reserve and black-start capability to hold | Adequacy assessments; incident reports |
Outputs this topic produces
- Outage pattern analyses by cause, season and network type
- Backup power endurance reviews for critical facilities
- Restoration sequencing studies linking power to dependent lifelines
- Reliability evidence notes for regulators
Coupled risk, applied response.
The sectors urban flood touches and how strongly they depend on each other: what a study has to observe and model together.
Choose a context
Sectors · Urban floodStress
Pillars · Urban floodKPI
In this contextDependence or handoff, heavier is strongerOutside this context
Programme yearAll phases
Context
Urban flood
Flooded streets take out substations, pumping stations and clinic access together; drinking water fails when power does.
W · E · I · F · H · B
Risk
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Hover a corner, a line or a row to trace it across both sides.
Route
Applied to urban flood
L · F · U · S · R · A
Response
- Pillars
- 5 of 6
- Handoffs
- 11 of 18
- Loops
- 8 closed
Expected value
- What is at stake
- $390Ba year at least, in infrastructure disruption costs to households and firms in low- and middle-income countriesWorld Bank, Lifelines, 2019
- Return on resilience
- 4 : 1benefit to costWorld Bank, Lifelines, 2019
- Avoided loss
- 30%less damage with 24 hours' warning of a storm or heatwaveGlobal Commission on Adaptation, Adapt Now, 2019
Hover a pillar, a line or a row to read how it is applied.
A: a teaching cascade (shock 0.6, gain 0.35, four rounds) over teaching values for a typical city-region, not measurements. B: illustrative applications and the KPI each pillar answers for; values are published benchmarks, cited, not forecasts. Open events: NASA EONET, live.
What experts ask.
- Which services fail immediately on loss of power, and which degrade over hours or days?
- How long do backup generators, batteries and fuel stocks actually last under real demand?
- How do grid failures propagate, and how quickly can a grid be restarted after a wide-area blackout?
- How does the shift to variable renewable generation, storage and distributed resources change reliability?
- Which loads should be restored first, and who decides?
How electricity and lifelines 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 electricity and lifelines: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
Drivers and failure pathways.
Power systems must balance supply and demand continuously. A disturbance such as a line fault, generator trip or sudden demand change shifts flows across the network; protection systems disconnect equipment to prevent damage, and if the disturbance is large enough, these disconnections can cascade into a wide-area blackout. Restarting a collapsed grid requires black-start capable generation and careful sequencing, which takes time.
Downstream services meet power loss through backup arrangements, and these are where hidden fragility lies. Generators fail to start, fuel deliveries depend on roads and pumps that themselves need power, batteries at telecommunications sites last hours rather than days, and backup systems are often tested less than assumed. Prolonged outages therefore produce a second wave of failures as backup capacity is exhausted.
Extreme heat and cold raise demand while stressing equipment, and wildfire, storm and flood damage transmission and distribution. Energy system science is shared with Energy Nexus.
How it is studied.
- 01
Grid reliability analysis
Contingency analysis and probabilistic reliability methods from power systems engineering test how grids respond to losing components.
- 02
Dependency inventories
Structured surveys record which services depend on power, their backup capacity and their tolerable outage duration.
- 03
Restoration modelling
Optimisation from optimisation and operations research explores restoration orders that bring back critical loads first.
- 04
Limits
Backup durations are often self-reported and untested. Grid models rely on operator data that is rarely public, and cascades depend on conditions that are hard to reproduce.
How it is studied, and what the methods cannot say.
- 01Power systems engineeringContingency analysis · Hardening distribution networks · Black-start and restoration plansApplied here
- 02Reliability and resilience engineeringResilience metrics for lifelines · Reliability analysis of networks · Restoration planningApplied here
- 03Network science and contagionCritical node and link analysis · Interdependent network models · Redundancy assessmentApplied here
- 04Energy generation, storage and grid technologyBackup power options · Microgrids for critical services · Fuel supply in emergenciesApplied here
- 05Optimisation and operations researchResilience investment portfolios · Restoration scheduling · Network design under uncertaintyApplied here
Where this page's references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Questions and answers.
What is SAIDI?
What is black start?
Why do other services fail when power fails?
Do backup generators solve the dependence on power?
Do renewables make grids less reliable?
Does the platform set restoration priorities?
Who reviews coverage of this topic?
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