PW-02·U1Smart grid management
Demand forecasting that dynamically adjusts energy flow across the network.
- Forecasts with confidence bands
- Flow adjusted ahead of demand
Generation that schedules its own maintenance.
Thermal plants, grids and storage: turbine health, fuel and emissions, dispatch and peak load — with condition-based maintenance that raises its own SAP notification.
PW-02·1GenerationThermal and combined cycle
PW-02·2EmissionsPredictive monitoring
PW-02·3GridDemand, load, storage
PW-02·4AssetsBoiler, turbine, BOP
01/ OverviewPower
Powering the future with AI-driven automation
The power sector is under pressure to deliver reliable, efficient and sustainable energy. Integrating renewables with traditional grids, managing fluctuating demand and preventing outages all call for next-generation tools.
SMHcoders provides AI-driven automation that creates smart, autonomous power operations — resilient, efficient and ready for cleaner sources.
What power operators tell us
CH·01
Heat-rate drift
Efficiency losses accumulate unnoticed between performance tests.
CH·02
Emissions monitoring
Hardware CEMS is costly to run and maintain.
CH·03
Ageing fleet
Reliability pressure on units past design life.
CH·04
Load-following stress
Cycling duty wears equipment designed for baseload.
02/ Where we helpEach links to the product or solution behind it
03/ Use casesDrag or scroll the strip
Intelligent automation for power operations
Real-time insight, predictive capability and autonomous control for energy operations.
PW-02·U2Real-time monitoring
Automated fault detection that minimises outages and restores service faster.
- Faults found before they cascade
- Faster, guided restoration
PW-02·U3Energy trading and load balancing
Bidding strategies improved with AI, and ML models that balance renewable and conventional sources.
- Fewer losses in power markets
- Renewables integrated without strain
PW-02·U4Autonomous plant dashboards
One live view of plant performance — heat rate, emissions, availability — for operators and management.
- Demand and consumption forecasting
- The same numbers for shift and board
04/ Before and afterDrag the divider
Today, and with SMHcoders.
The same plant, the same people — the difference is what the data does between the lab, the control room and the work order.
AreaTodayWith SMHcoders
Heat rateFound at the annual performance testTracked every minute, with deviation alerts
EmissionsHardware CEMS, costly to keep runningPredictive estimates from process data
Equipment healthForced outages on ageing unitsDegradation flagged before the trip
Load-followingCycling wears baseload equipmentMPC holds stable, efficient setpoints
DemandPlanned on yesterday's profileForecast across the day and season
05/ Solutions portfolioFrom the Power brochure
The portfolio, mapped to what's already built.
Every solution in our Power brochure. Where one runs on a product or solution we deliver, it links there — the rest are scoped as engagements on the same delivery stack.
01Autonomous load dispatch and optimisationScoped engagement
02AI-based predictive maintenance of gas and steam turbinesSolution · Predictive Maintenance
03Autonomous fuel consumption management for thermal plantsScoped engagement
04Real-time emission control and regulatory complianceProduct · Soft sensing & analytics
05Virtual power plant (VPP) autonomous coordinationScoped engagement
06AI-powered grid stability and blackout preventionScoped engagement
07Intelligent peak load managementScoped engagement
08Autonomous smart-grid energy storage optimisationScoped engagement
09AI-based fault detection, localisation and restorationScoped engagement
10Condition-based maintenance with SAP notification generationProduct · AssetOps CMMS
11Intelligent renewable forecasting and integrationProduct · Plant Autopilot
12AI-powered cybersecurity for grid protectionScoped engagement
06/ What it changesPW-02 · impact board
Lower heat rate at every loadOK
Continuous emissions visibilityOK
Fewer forced outagesOK
Smoother load-followingOK
“A plant that knows its heat rate every minute does not wait a year to find the losses.”
In your industry · SMHcoders
07/ ProductsDelivered in this industry's stack
08/ Common questions
Where do plants like ours usually start?
With one measurable use case — most often a soft sensor or an equipment-health model on a unit that matters. Small scope, visible payoff, then scale.
Do you work on site?
Yes. Scoping and commissioning happen at your site in the Gulf region; model development runs in-house with our own engineering team.
What data do we need to start?
Most engagements start with 6–24 months of historian, lab or document data. We audit coverage in the first week and tell you plainly if it is not enough — before you commit.
Where does it run, and who sees our data?
On your infrastructure — plant-side servers, your Azure or AWS tenancy, or an air-gapped network. Data never leaves your boundary, and nothing is used to train third-party models.
Is the consultation really free?
Yes — 45 minutes with an engineer, a feasibility read and suggested next steps. No obligation.