Restoration curve analysis
Customer outage records from past events are converted into restoration curves, so the time to recover is measured alongside the size of the initial loss.
The Global Centre for Risk and Innovation (GCRI)
Reliability and resilience engineering asks how energy assets and systems fail, how quickly they recover, and which components and organisational arrangements set the recovery time. It turns outage records, damage surveys and asset data into resilience measures that operators and regulators can compare across events.
GCRI · Established · service level R0
Reliability and resilience engineering is the study of how assets and systems fail and how quickly they recover. For energy it turns outage records, damage surveys and asset data into measures such as restoration curves and fragility curves that operators and regulators can compare across events.
Reliability and resilience engineering studies how systems fail, how failures can be prevented and how systems absorb, adapt and recover from disruption. It addresses both technical components and the organisations that operate them. In energy, critical infrastructure and climate and hazards, resilience engineering identifies critical components and recovery bottlenecks across connected systems. It informs redundancy, spares and restoration priorities. The canonical description is on the STEM Commons.
Customer outage records from past events are converted into restoration curves, so the time to recover is measured alongside the size of the initial loss.
The paths by which a hospital, water works or data centre loses supply are traced through grid feeds, transfer switches, generators and fuel, revealing single points of failure.
The probability of damage to poles, lines and substations is related to wind speed, ice load or flood depth using post-event damage surveys.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Fragility curve | The probability that an asset reaches a given damage state as hazard intensity, such as wind speed, increases. |
| Fault tree analysis | A top-down method that traces the combinations of component failures that lead to a defined system failure. |
| Mean time to repair | The average time needed to restore a failed component to service. |
Where demand concentrates in cities and the rail, road and port corridors that move fuel and equipment, shown for the Nordic and Baltic region 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 reliability and resilience engineering on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.
| Data | Role | Label |
|---|---|---|
| Utility outage and interruption records | Failure rates and durations | OFFICIAL |
| Post-event damage surveys | Fragility estimation | REPORTED |
| Asset registers | Age, type and condition of components | OFFICIAL |
| Incident investigation reports | Failure sequences | REPORTED |
Reliability predictions are compared with field failure data. Exercises and post-event reviews check whether recovery performed as planned.
| Check | How it is done |
|---|---|
| Field data comparison | Predicted failure rates are compared with recorded failures for the same asset class |
| Common-cause review | Redundant components are checked for shared causes such as one fuel supplier or one flood zone |
| Exercise and post-event review | Restoration assumptions are tested against exercises and actual events |
Common-cause failures and rare events are hard to estimate from limited data. Human and organisational factors resist quantification.
Critical Infrastructure stewards reliability and resilience engineering 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.