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Reliability Analysis Platform
InfraRel is an emerging reliability-analysis platform for evaluating interconnected electrical and supporting infrastructure systems. It extends the foundation of SUBREL, which has been used in power-industry applications to evaluate and compare alternative substation configurations.
Under active development
The developing GR Infrastructure Assurance Framework is the lifecycle context for this platform. InfraRel remains under active development.
Engineering development status · October 2026
GR distinguishes the established SUBREL reliability methodology from ongoing software modernization and the broader InfraRel research agenda. Descriptions below identify the intended analytical behavior and development priorities; they are not claims that every function is implemented, independently verified or ready for customer production use.
SUBREL's substation reliability approach evaluates component outages, protective isolation, switching/restoration consequences and service impacts. Its legacy application experience should not be mistaken for verification of a new engine.
Current engineering work emphasizes network-state solution, protection consequence tracing, state-by-state switching checks, restoration timelines and reproducible test cases. Prototype results and regression checks require documented manual and scenario-based verification before release claims.
Intended scope expands from electrical service to dependencies involving UPS/storage, cooling, communications, controls and useful computation. Correlated/common-mode events, recovery duration and probabilistic consequences are research and implementation objectives—not a statement of present end-to-end simulation capability.
Research boundary: Integrated Grid–Data Center Reliability is a related collaborative research framework spanning grid and facility interactions. It is not advertised as an already implemented InfraRel capability. Specific feature maturity will be updated after documented acceptance testing.
Why InfraRel
Critical infrastructure depends on more than the availability of utility power. A data center, industrial facility or other essential service may also depend on local generation, batteries, switching systems, cooling, communications, controls, buildings and operational processes. A failure in any required subsystem can interrupt the service even when other parts of the system remain available.
InfraRel expands the modeled boundary so that failures, dependencies, restoration actions and their consequences can be evaluated across the complete service-delivery chain.
Power is also required by cooling, communications, controls, offices and supporting facilities — so electrical availability and supporting-system availability are coupled.
Foundation
InfraRel is relatively new, but its underlying reliability methodology is not. It extends SUBREL, a reliability-analysis program developed and used in power-industry applications to compare alternative substation configurations.
The established foundation includes the representation of component outages, system configurations, switching and restoration actions, and their effects on continuity of supply. InfraRel extends this approach to interconnected infrastructure systems and broader operational consequences.
InfraRel is emerging; it does not yet share SUBREL’s application history.
System boundary
External supply paths and interconnection points that feed the facility.
On-site generation that can support ride-through, islanded or backup operation.
Short-term continuity and bridging between sources.
Transfer paths that change the active supply configuration.
Isolation, protection and switching that shape outage and restoration sequences.
Thermal systems required to keep critical loads operable.
Networks that support monitoring, control and operational continuity.
Supervisory and control functions that govern response and recovery.
Supporting facilities that may be required for continued operation.
The loads whose interruption defines service failure for the study.
The model can be simplified to match the study objective. Not every system or component must be represented at the same level of detail, but material dependencies and exclusions should be identified explicitly.
Methodology
The objective is not merely to determine whether power is restored. For a data-center application, the relevant endpoint is whether useful computation continues or is restored within an acceptable time and cost.
Indices & consequences
A single availability percentage is insufficient for many infrastructure decisions. InfraRel organizes complementary measures so frequency, duration, operational impact and cost can be examined separately.
How often disruptive events are expected to occur.
How long physical supply or support is interrupted.
How long useful work is lost, including restart and recovery.
Energy not delivered because of interruptions.
Useful computational work not completed because of interruptions.
Accelerator or compute capacity-time lost to disruption and recovery.
Operational effects of switching, restart and return to service.
Economic consequences associated with interruptions and recovery.
Two systems with the same availability can experience very different interruption frequencies, restoration times, lost computation and financial consequences. InfraRel therefore separates the frequency of disruptive events from their physical and operational duration.
Related reading: outage duration clocks and cost boundaries →
Related methodology: Data-Center Power Architecture & Reliability → Configuration, switching and common-mode structure on that page can inform InfraRel case definition where scoped.
Related methodology: Grid Capacity & Flexibility Assurance Framework → InfraRel may support configuration and consequence analysis within that broader assurance workflow where scoped.
Related methodology: Load Behavior & POI → Operating-state, ramp, rebound and model-requirement framing can inform InfraRel scenarios where scoped.
Uncertainty & ranges
Each InfraRel run presently produces a single set of reliability and consequence indices for one defined system configuration and set of input parameters. These point estimates are useful for comparing alternatives, but they do not by themselves describe the complete range of possible outcomes or uncertainty in the assumptions.
Range-based assessments can be developed through a structured matrix of InfraRel cases in which selected failure rates, restoration times, dependency assumptions, demand levels, recovery times and cost parameters are varied. Because individual cases can generally be evaluated independently, parallel processing can make large sensitivity and scenario studies practical.
Vary one parameter at a time to identify influential assumptions.
Compare defined normal, adverse and extreme combinations of conditions.
Evaluate sampled parameter combinations to estimate ranges, percentiles, exceedance probabilities and tail exposure.
Use cases
Future distribution reliability applications: As the modernization work progresses, InfraRel methods could support engineering evaluation of interruption consequences, protection and restoration sequences, and the reliability impact of candidate feeder or substation changes. Linking those models with OMS, AMI, SCADA or other operational datasets would require additional data mapping, validation, security review and implementation work; these integrations are not presented as completed capabilities. Distribution reliability improvement approach →
The following are potential applications where the methodology is being developed and demonstrated. Validation and case studies are still in progress.
Limitations & development
InfraRel can organize complex reliability questions, compare defined alternatives and expose the consequences of failures and assumptions. It does not eliminate uncertainty or provide universally applicable answers. Data-center architectures, workloads, controls, recovery processes and economic consequences differ considerably among facilities.
| Limitation | Practical response |
|---|---|
| Uncertain failure and repair data | Sensitivity ranges and improved field data |
| Single-point result per run | Structured matrices of parallel cases |
| Difficult-to-quantify common-mode events | Explicit scenarios and bounded assumptions |
| Changing load and workload behavior | Multiple operating and recovery states |
| Simplified supporting systems | Selective detail with explicit dependencies |
| Facility-specific outage costs | Cost ranges and scenario analysis |
| Limited rare-event evidence | Stress cases and tail-risk reporting |
The objective is not to claim precision beyond the available evidence. It is to make assumptions explicit, identify which uncertainties influence the decision and test whether conclusions remain valid across credible conditions.
Collaboration
GR is developing comparative case studies to demonstrate the methodology, required data, reliability indices and configuration tradeoffs. Detailed assumptions, results and limitations will be presented in a forthcoming technical paper.
We welcome opportunities to explore pilot applications and collaborate with utilities, data-center operators, equipment manufacturers, engineering organizations, software developers and researchers who can contribute system knowledge, operational data and validation experience.
Data-center power & grid reliability → · From Analysis to Decision → · Utilities: grid–data center reliability →
