Capability & Use-Case Intelligence · Energy Infrastructure
What asset management and digital engineering do on energy infrastructure.
A use-case catalog organized by infrastructure class — generation fleets, renewables, grid, pipelines, and process plants. Each card names the application, what it runs on, and what it changes in operations.
AM — asset management capability
DE — digital engineering capability
Cross-cutting platform capability
CLASS · 01 Thermal & Hydro Generation
Rotating equipment is where predictive programs prove out first.
Turbines, generators, boilers, and balance-of-plant equipment carry the highest failure consequence per asset — which is why generation fleets are usually the entry point for condition monitoring and twin programs.
Turbines, generators & rotating equipment
Steam · Gas · Hydro · BOP
Vibration-signature analytics on turbine trains
Continuous spectral analysis of shaft-line vibration to distinguish bearing wear, misalignment, imbalance, and blade-pass anomalies weeks before functional failure.
Runs onProximity probes, accelerometers, phase reference, historian data
ChangesForced-outage avoidance; bearing/seal work moved into planned windows
Thermal performance twin for heat-rate recovery
Thermodynamic model of the steam/gas cycle running against live plant data to locate efficiency losses — fouled condensers, leaking valves, degraded compressor sections.
Runs onDCS process data, design heat-balance model, fuel & ambient data
ChangesFuel cost per MWh; targeted cleaning & overhaul scope
Creep-fatigue life assessment on boiler & HRSG components
Remaining-life calculation on headers, drums, and tubing based on operating-hour history, cycling profile, and inspection findings — the basis for run/repair/replace decisions.
Runs onOperating history, metallurgical sampling, NDE inspection records
ChangesDefensible life-extension decisions; capital deferral with documented risk
Risk-ranked outage scoping
Criticality and condition data used to build the outage work list — what must be opened this outage vs. what can defensibly wait — replacing scope-by-habit.
Runs onCriticality register, condition data, failure-mode library, cost models
ChangesShorter outages, less scope creep, documented deferral rationale
Start-up & cycling stress advisor
Model-based guidance on ramp rates and start sequences for units originally designed for baseload now cycling daily — quantifying the life cost of each fast start.
Runs onThermal stress models, metal temperatures, dispatch schedule
ChangesCycling damage per start reduced; life consumption made visible to dispatch
Critical-spares optimization
Failure-probability and lead-time data used to decide which capital spares (rotors, transformers, exciters) to hold, pool across the fleet, or contract for.
Runs onFailure statistics, OEM lead times, fleet commonality analysis
ChangesOutage duration risk capped without over-holding inventory
CLASS · 02 Wind & Solar
Distributed fleets make remote analytics the default, not the upgrade.
Hundreds of identical units spread across sites — high-value use cases exploit fleet statistics: any one turbine or string can be benchmarked against every sibling.
Wind fleets — onshore & offshore
Turbines · Foundations · Array cables
Gearbox & main-bearing failure prediction
SCADA and CMS data across the fleet trained against historical failures to flag drivetrain degradation months ahead — the difference between an up-tower repair and a crane mobilization.
Runs on10-min SCADA, vibration CMS, oil-particle counts, fleet failure history
ChangesCrane campaigns batched and scheduled; catastrophic drivetrain loss avoided
Drone blade inspection with automated defect classification
UAV imagery processed by vision models to detect and grade leading-edge erosion, lightning damage, and cracking — a full site inspected in days without rope teams.
Runs onUAV imagery, defect taxonomy, blade design data
ChangesRepair campaigns prioritized by AEP loss; rope access reserved for repair, not inspection
Offshore foundation & array-cable integrity management
Scour monitoring, corrosion protection surveys, and cable burial assessment feeding a risk-ranked subsea inspection plan — the largest uninsured exposure on many offshore assets.
Runs onROV/survey campaigns, CP readings, cable DTS/DAS data, metocean history
ChangesCable-failure exposure reduced; survey spend focused on highest-risk positions
Solar PV & storage
Utility-scale PV · Inverters · BESS
String-level underperformance detection
Combiner and string current data benchmarked against modeled yield to isolate soiling, shading, degradation, and connector faults invisible at the site meter.
Runs onString/combiner telemetry, irradiance data, digital yield model
ChangesRecovered MWh from faults that never trip an alarm; targeted cleaning
Aerial thermography for module & inverter faults
Drone IR flights detecting hot spots, bypass-diode failures, and dead strings across large sites, mapped to the as-built layout for work-order generation.
Runs onIR/RGB drone imagery, as-built site model, module serial mapping
ChangesWarranty claims substantiated; O&M truck rolls cut
BESS degradation & augmentation planning
Cell-level degradation tracking against warranty curves to time capacity augmentation and validate use-profiles — the core economic decision of a storage asset’s life.
Runs onBMS data, cycling history, capacity tests, warranty terms
ChangesAugmentation CAPEX timed correctly; warranty positions protected
CLASS · 03 Transmission & Distribution
The grid’s problem is scale: millions of assets, thin data on most.
Use cases here concentrate on the highest-consequence equipment — transformers, breakers, lines — and on stretching inspection coverage with remote sensing.
Substations, transformers & lines
HV/MV assets · Overhead lines · Switchgear
Transformer health via online DGA & thermal models
Dissolved-gas analysis, bushing monitoring, and hot-spot thermal models combined into a health index per unit — the standard for managing a transformer fleet where a single failure can mean 12–24 month lead times.
Runs onOnline DGA sensors, load history, oil tests, nameplate & design data
ChangesReplacements sequenced years ahead; catastrophic failure risk ranked fleet-wide
Satellite & LiDAR vegetation management
Satellite imagery and LiDAR flights identifying encroachment and hazard trees along corridors, replacing fixed-cycle trimming with risk-ranked clearance — a top wildfire-mitigation control.
Runs onSatellite multispectral data, LiDAR point clouds, corridor GIS, growth models
ChangesVegetation-caused outages and ignition risk down; trim budget re-aimed at real encroachment
Dynamic line rating
Real-time conductor temperature and weather data unlocking capacity above static ratings — deferring reconductoring and easing renewables interconnection congestion.
Runs onConductor sensors or weather-model DLR, SCADA loading, line design data
ChangesTransfer capacity gained without new build; curtailment reduced
Asset health indexing & replacement prioritization
Condition, age, criticality, and obsolescence scored across breakers, transformers, and cables to build the regulator-facing replacement program — the evidence base for rate cases.
Runs onInspection & test records, failure statistics, criticality, spares position
ChangesDefensible capital plans; regulator-accepted risk justification
Storm hardening & climate-exposure targeting
Outage history, weather exposure, and asset condition combined to target undergrounding, pole-class upgrades, and sectionalizing where they cut the most customer-minutes lost.
Runs onOutage (OMS) history, hazard maps, asset condition, customer density
ChangesSAIDI/SAIFI improvement per dollar maximized; hardening spend defensible
Network digital twin for outage & switching studies
A connectivity-accurate network model used to rehearse switching plans, study contingencies, and validate protection settings before crews touch the real grid.
Runs onGIS network model, SCADA state, protection settings database
ChangesSwitching errors and planned-outage overruns reduced
CLASS · 04 Pipelines & Midstream
Integrity is the license to operate.
Linear assets crossing public land make this the most regulation-driven class: use cases center on knowing the condition of steel you cannot see.
Transmission pipelines, compressor & pump stations
Gas · Liquids · Storage
ILI-based corrosion growth modeling
Successive in-line inspection (smart pig) runs aligned signal-to-signal to measure corrosion growth rates per anomaly, setting re-inspection intervals and dig programs on evidence.
Runs onILI datasets across runs, pipe book data, CP survey history
ChangesDig programs cut to anomalies that are actually growing; PHMSA-defensible intervals
Fiber-optic leak & intrusion detection (DAS/DTS)
Distributed acoustic and temperature sensing on existing or new fiber detecting leaks, third-party strikes, and ground movement along the entire right-of-way in real time.
Runs onFiber along the ROW, acoustic/thermal signal models, alarm-management config
ChangesThird-party damage (the top loss cause) caught in progress; leak localization to meters
Geohazard & ground-movement management
InSAR satellite deformation data, strain gauges, and geotechnical surveys identifying slopes and water crossings loading the pipe — increasingly the dominant integrity threat in mountainous systems.
Runs onInSAR time series, IMU/strain data from ILI, geotech assessments
ChangesStrain-relief digs targeted before rupture; monitoring replaces blanket mitigation
Compressor & pump station health analytics
Vibration, thermodynamic performance, and valve data on reciprocating and centrifugal units predicting failures at stations that are often unmanned.
Runs onStation SCADA, vibration CMS, performance curves, maintenance history
ChangesUnmanned-station reliability up; throughput loss from unit trips reduced
Methane detection & quantification
Aerial, satellite, and continuous point-sensor surveys locating and quantifying methane emissions across the network — now both a compliance obligation and a product-loss recovery.
Runs onSatellite/aerial spectrometry, ground sensors, facility inventory
ChangesSuper-emitter events found in days not years; regulatory reporting substantiated
Records reconciliation & MAOP validation
Digitizing and reconciling decades of construction and test records to substantiate maximum allowable operating pressure — a regulatory mandate that is, at core, an engineering-data project.
Runs onLegacy records digitization, pipe book reconstruction, hydrotest history
ChangesTraceable, verifiable, complete records; pressure restrictions lifted where evidence supports
CLASS · 05 Process Plants & LNG
Dense, hazardous, and shutdown-driven — the deepest use-case stack.
Refineries, gas plants, and LNG terminals concentrate thousands of pressure systems in one fence line. Turnaround economics dominate everything.
Pressure systems, piping & static equipment
Refining · Gas processing · LNG
Risk-based inspection across pressure systems
Damage-mechanism assessment (corrosion loops, CUI, HTHA, fatigue) driving inspection scope and interval per circuit — the canonical AM use case, cutting inspection volume while raising coverage of what matters.
Runs onProcess conditions, materials data, thickness history, damage-mechanism library
ChangesTurnaround inspection scope rationalized; loss-of-containment risk ranked per circuit
Permanently installed corrosion & thickness sensors
Wireless UT sensors on high-risk circuits streaming wall-thickness trends continuously — turning corrosion-rate assumptions into measured data between turnarounds.
Runs onWireless UT arrays, process data correlation, corrosion models
ChangesCorrosion excursions from feed changes caught in days; scaffold-and-inspect spend cut
Laser-scan / point-cloud plant twin for turnarounds & brownfield work
Millimeter-accurate 3D capture of as-built plant used to plan scaffolding, lifts, and tie-ins off-site — clash detection before steel arrives at the gate.
Runs onLaser scanning, photogrammetry, tagged P&ID linkage
ChangesTurnaround duration and rework down; brownfield engineering done without site visits
Fired-heater & exchanger fouling prediction
Performance models tracking fouling rates on heaters and exchanger networks to time cleaning against energy cost and throughput loss rather than fixed schedules.
Runs onProcess historian, design performance curves, energy cost data
ChangesCleaning timed at economic optimum; tube-metal-temperature excursions avoided
Safety-instrumented system proof-test optimization
SIS demand and failure data used to set proof-test intervals per safety integrity level — keeping protection layers verified without over-testing that itself introduces trip risk.
Runs onSIS event logs, failure-rate data, SIL calcs, test records
ChangesSpurious trips reduced; functional-safety compliance evidenced
Connected-worker rounds & AR work packs
Digitized operator rounds with sensor-augmented checklists, and AR overlays serving isolation points, torque specs, and P&ID context to maintenance crews at the equipment.
Runs onMobile/AR devices, EDMS linkage, work-order system integration
ChangesWrench-time up, isolation errors down; rounds data feeds condition models
PLATFORM · 06 Cross-Cutting Capabilities
The layer underneath every use case above.
Four platform capabilities determine whether the asset-class use cases scale beyond pilots. Weakness here is the usual reason individual use cases stall.
Platform · P-01
Asset data foundation & EDMS
A single trusted register — hierarchy, tagging, criticality, linked drawings and P&IDs. Every analytics use case inherits its quality ceiling from this layer.
Applies to: every use case in this catalog; first investment when data is fragmented across CMMS, spreadsheets, and drawing archives.
Platform · P-02
OT/IT data integration & historians
Secure, governed movement of control-system data into analytics environments — contextualized (which sensor, which asset, which state) rather than raw tag streams.
Applies to: all condition-monitoring, twin, and predictive use cases; the usual bottleneck between pilot and fleet rollout.
Platform · P-03
OT cybersecurity
Segmentation, monitoring, and integration governance for control networks — every sensor and connection added by the use cases above widens the surface this capability must hold.
Applies to: any use case touching SCADA/DCS/SIS; non-negotiable for unmanned stations and remote operations.
Platform · P-04
APM / decision-support layer
Where condition data, models, and risk logic converge into work: health indices, alert triage, and automatic work-order generation into the CMMS/EAM.
Applies to: converting every detection use case into scheduled, costed maintenance action — the last mile that realizes the value.
MAP · 07 Capability × Infrastructure Matrix
Where each capability is core, growing, or emerging.
A scoping aid: read down a column to see the use-case stack for one infrastructure class; read across a row to see where a capability investment reuses.
| Capability | Generation | Wind | Solar/BESS | Grid/T&D | Pipelines | Process/LNG |
|---|---|---|---|---|---|---|
| Vibration / condition monitoring | ||||||
| Predictive ML on failure modes | ||||||
| Digital twin (performance / 3D) | ||||||
| Drone / remote inspection | ||||||
| Satellite sensing (InSAR / veg / methane) | ||||||
| Risk-based inspection / integrity | ||||||
| Health indexing & replacement planning | ||||||
| Fiber sensing (DAS/DTS) | ||||||
| Connected worker / AR field tech | ||||||
| Records digitization & EDMS |
Core — established, widely deployed
Growing — scaling from early adopters
Emerging — pilots and niche deployment