Interdependency mapping
Substations are linked to the water works, hospitals, telecommunications sites and fuel terminals they supply, and those back to the grid assets that depend on them.
The Global Centre for Risk and Innovation (GCRI)
Network science maps the energy system as connections: lines and substations, pipelines and terminals, and the dependencies that link them to water, telecommunications, transport and finance. It identifies the nodes and pathways through which a local failure becomes a regional or cross-sector one.
GCRI · Established · service level R0
Infrastructure interdependency analysis is the use of network science to map the energy system as connections, from lines and substations to pipelines and terminals, and their links to water, telecommunications, transport and finance. It identifies the nodes and pathways through which a local failure becomes regional or cross-sector.
The working screen behind this method: its structure, terms and states. Names are placeholders and values illustrative.
Energy · Network science for energy… · Run R-5955
nodes: assets · edges: dependencies
| N3 | 0.25 | 8 | Critical |
| N4 | 0.32 | 8 | Normal |
| N5 | 0.32 | 10 | Normal |
| N6 | 0.21 | 13 | Normal |
Network science and contagion study how the structure of connections among entities shapes the spread of failures, information and disease. It provides tools to analyse interdependent infrastructure, supply chains and financial systems. In energy, critical infrastructure and climate and hazards, network science identifies critical nodes and pathways through which shocks propagate across sectors. It informs targeted protection and diversification to limit cascades. The canonical description is on the STEM Commons.
Substations are linked to the water works, hospitals, telecommunications sites and fuel terminals they supply, and those back to the grid assets that depend on them.
Failures are introduced in one layer and propagated to dependent layers, showing which combinations of losses fragment service across sectors.
Centrality and percolation measures rank assets by how many dependent services rely on them, as one input to protection priorities set by operators.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Interdependency | A two-way dependency between infrastructures, such as power needing telecoms for control while telecoms need power to run. |
| Multilayer network | A network model with several layers, one per infrastructure, joined by dependency links. |
| Betweenness centrality | How often a node lies on shortest paths between others, a common measure of its criticality. |
Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment, shown for Ukraine as an example geography for this subject.
Data from the source register feeds the methods; calibration and an independent test gate the estimate and its limits; the decision stays with the competent authority.
Fig. 01Nodes carry their type, metrics and state; connectors show what feeds what; the gates are the validation steps; the timeline is one application. Design of the method's use, not a record of a run.
Datasets and records used by network science and contagion on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| OpenStreetMap power and infrastructure layers | Topology where official data are not public | REPORTED |
| Operator network data under agreement | Authoritative topology | OFFICIAL |
| Critical facility registers | Locations of dependent services | OFFICIAL |
| Fuel and gas pipeline databases | Fuel supply links | REPORTED |
Models are checked by reproducing observed cascades and outbreaks. Robustness of results to missing or uncertain links is tested.
| Check | How it is done |
|---|---|
| Historical cascade reproduction | Models are tested on documented blackouts to see whether they reproduce the observed spread |
| Missing link sensitivity | Results are re-run with links removed or added at random to test how much incomplete data changes the rankings |
| Disclosure review | Published network outputs are generalised so that sensitive assets cannot be singled out |
Network data are often incomplete or confidential. Static network models may miss adaptive behaviour during cascades.
Systems Science and Modelling stewards network science and contagion for the Consortium and reviews how it is applied across platforms.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.