neqsim-power-generation

name	neqsim-power-generation
description	Power generation patterns for NeqSim. USE WHEN: modeling gas turbines, steam turbines, HRSG, combined cycle systems, waste heat recovery, or calculating fuel gas consumption and thermal efficiency. Covers GasTurbine, SteamTurbine, HRSG, CombinedCycleSystem classes and heat integration with PinchAnalysis.
last_verified	2026-07-04

Power Generation with NeqSim

Guide for modeling power generation equipment — gas turbines, steam turbines, heat recovery steam generators (HRSG), and combined cycle systems.

When to Use This Skill

• Gas turbine modeling (power output, fuel consumption, exhaust conditions)
• Steam turbine expansion and power generation
• Heat recovery steam generator (HRSG) design
• Combined cycle system integration (GT + HRSG + ST)
• Waste heat recovery from process streams
• Fuel gas consumption and CO2 emissions from drivers
• Thermal efficiency calculations
• Heat integration / pinch analysis for process plants

Key NeqSim Classes

Class	Package	Purpose
GasTurbine	process.equipment.powergeneration	Gas turbine with compressor, combustor, expander
GasTurbineVendorPerformance	process.equipment.powergeneration	Vendor ISO-rated GT driver — fuel + CO2 matched to a shaft/electric load demand
SteamTurbine	process.equipment.powergeneration	Steam expansion turbine
HRSG	process.equipment.powergeneration	Heat recovery steam generator
CombinedCycleSystem	process.equipment.powergeneration	GT + HRSG + ST integrated system
PinchAnalysis	process.equipment.heatexchanger.heatintegration	Pinch analysis for heat integration
HeatStream	process.equipment.heatexchanger.heatintegration	Hot/cold stream for pinch analysis

Vendor-performance GT driver — matched fuel & power (PREFERRED for drivers)

For a real mechanical-drive or generator gas turbine (e.g. a GE LM2500 driving a compressor or an AC generator), the built-in simple-cycle GasTurbine is a rough model and is unreliable for net power / efficiency. Use GasTurbineVendorPerformance instead: it takes a load demand and returns the fuel rate and CO2 matched to that load using the fuel gas's rigorous ISO 6976 LCV and stoichiometric carbon.

GasTurbineVendorPerformance gt = new GasTurbineVendorPerformance("GT driver", fuelStream);
gt.setVendorRating(22.4, "MW", 0.37);        // ISO base power, base LHV efficiency
gt.setAmbientDerating(15.0, 0.007);          // design ambient C, power lapse /degC
gt.setSiteAmbientTemperature(15.0);
gt.setPartLoadHeatRateCoefficient(0.15);     // heat-rate rise at part load
gt.setLoadDemand(compressor.getPower("kW"), "kW");  // <-- the process power need
gt.run(UUID.randomUUID());
double fuel = gt.getFuelFlowRate("kg/hr");
double co2  = gt.getCO2EmissionRate("tonne/day");
double loadFrac = gt.getLoadFraction();      // vs site-rated MAX (bottleneck basis)
double spareKW  = gt.getSiteRatedPower("kW") - compressor.getPower("kW");

Matching rule (do this, never hardcode fuel/power):

• Mechanical-drive GT load demand = the simulated compressor shaft power (compressor.getPower("kW")), so fuel and CO2 track the process automatically.
• Fuel gas is a slip-stream of the real process gas (e.g. treated export gas). For a closed mass balance, physically tap it with a Splitter (setFlowRates([-1.0, fuelKgHr], "kg/hr")) so sales gas = gas − fuel.
• Platform electric LOAD is an operational quantity — resolve it by source priority, do NOT hardcode: (1) measured historian tag (tagreader/Seeq main-switchboard active power) — the correct primary source; (2) STID generator installed rating × documented load factor if STID exposes a structured rating; (3) a clearly-flagged fallback. STID's structured rating/load fields are frequently empty (they live in the datasheet PDF), so the historian is the right source for the actual load — record the chosen source in results.json so the value is never an unsourced magic number.
• Max limits / bottlenecks for production optimization: report per-GT getSiteRatedPower, getLoadFraction, spare power, and N+1 firm capacity for the generators; the highest-loaded unit is the power bottleneck.

1. Gas Turbine

// Fuel gas stream — the combustion air is generated internally by the GasTurbine.
SystemInterface fuelGas = new SystemSrkEos(273.15 + 25, 30.0);
fuelGas.addComponent("methane", 0.90);
fuelGas.addComponent("ethane", 0.06);
fuelGas.addComponent("propane", 0.02);
fuelGas.addComponent("nitrogen", 0.02);
fuelGas.setMixingRule("classic");

Stream fuelStream = new Stream("Fuel Gas", fuelGas);
fuelStream.setFlowRate(5000.0, "kg/hr");
fuelStream.run();

// Simplified Brayton-cycle gas turbine: internal air compressor + combustor + expander + cooler.
GasTurbine gt = new GasTurbine("GT-001", fuelStream);
gt.combustionpressure = 18.0;      // firing / combustion pressure [bara]
gt.setExcessAirFactor(2.5);        // excess air over stoichiometric (caps firing temperature)
gt.run();

double power_MW = gt.getPower("MW");           // net shaft power (expander - air compressor)
double rejectHeat_W = gt.getHeat();           // heat rejected by the exhaust cooler [W]
   gt.calcIdealAirFuelRatio(); 

The legacy GasTurbine is a simplified thermodynamic Brayton model. For vendor-rated power, part-load + ambient correction, degradation, emissions, and dispatch use GasTurbineUnit + GasTurbineCatalog (see section 7).

Inverse (power-demand) mode — size fuel to a load

GasTurbine can also run inverse: instead of fuel-in → power-out, give it a required net power and it sizes the fuel-gas flow so the turbine delivers that load from the fuel lower heating value (LCV) and its thermalEfficiency. Use this when a compressor/generator load is known and you want the matching fuel (and CO₂) consumption as the process solves.

GasTurbine gt = new GasTurbine("GT-driver", fuelStream);
gt.setThermalEfficiency(0.36);          // REQUIRED (> 0) for power-demand mode
gt.setRequiredPower(18.0, "MW");        // driven load; unit: "W", "kW" or "MW"
gt.run();

double fuel_kghr = gt.getFuelFlowRate("kg/hr");  // fuel-gas consumption sized to the load
double fuel_Sm3d = gt.getFuelFlowRate("Sm3/day");
boolean inverse  = gt.isPowerDemandMode();       // true
double reqW      = gt.getRequiredPower();         // required power in Watts

setRequiredPower(0.0, ...) returns the turbine to the normal fuel-to-power mode. Power-demand mode throws if thermalEfficiency <= 0. For vendor-accurate fuel/CO₂ vs a load demand, prefer GasTurbineVendorPerformance (top of this skill) or the catalog-driven GasTurbineUnit (section 7).

2. Steam Turbine

// Steam at high pressure and temperature
SystemInterface steam = new SystemSrkEos(273.15 + 540, 100.0);
steam.addComponent("water", 1.0);
steam.setMixingRule("classic");

Stream steamFeed = new Stream("HP Steam", steam);
steamFeed.setFlowRate(50000.0, "kg/hr");

SteamTurbine st = new SteamTurbine("ST-001", steamFeed);
st.setOutletPressure(0.1);  // Condenser pressure in bara
st.setIsentropicEfficiency(0.85);
st.run();

double stPower = st.getPower("MW");
double outletT = st.getOutletStream().getTemperature() - 273.15;

3. Heat Recovery Steam Generator (HRSG)

// Recover heat from a hot turbine-exhaust gas stream. The HRSG takes a single
// hot-gas inlet stream; steam conditions are set on the unit.
HRSG hrsg = new HRSG("HRSG-001", exhaustGasStream);
hrsg.setSteamPressure(40.0);            // bara
hrsg.setSteamTemperature(400.0, "C");
hrsg.setFeedWaterTemperature(105.0, "C");
hrsg.setApproachTemperature(15.0);
hrsg.run();

double duty_W = hrsg.getHeatTransferred();
double steamFlow = hrsg.getSteamFlowRate("kg/hr");
double stackT = hrsg.getGasOutletTemperature() - 273.15;  // °C

4. Combined Cycle System

// Integrated GT + HRSG + ST. The sub-units are built internally from the fuel
// gas stream — configure conditions through the setters below.
CombinedCycleSystem ccgt = new CombinedCycleSystem("CCGT", fuelStream);
ccgt.setCombustionPressure(18.0);
ccgt.setSteamPressure(40.0);
ccgt.setSteamTemperature(400.0, "C");
ccgt.setGasTurbineEfficiency(0.38);
ccgt.setSteamTurbineEfficiency(0.85);
ccgt.run();

double totalPower = ccgt.getTotalPower("MW");
double gtPower_W = ccgt.getGasTurbinePower();
double stPower_W = ccgt.getSteamTurbinePower();
double combinedEfficiency = ccgt.getOverallEfficiency();
// Typical: 55-62% for modern CCGT

5. Heat Integration (Pinch Analysis)

// Identify minimum utility requirements for a process
PinchAnalysis pinch = new PinchAnalysis("Plant Heat Integration");

// Add hot streams (need cooling)
pinch.addHotStream(new HeatStream("Reactor effluent", 250.0, 60.0, 5000.0));
pinch.addHotStream(new HeatStream("Column overhead", 120.0, 40.0, 3000.0));
pinch.addHotStream(new HeatStream("Product cooler", 80.0, 30.0, 1500.0));

// Add cold streams (need heating)
pinch.addColdStream(new HeatStream("Feed preheater", 25.0, 180.0, 4500.0));
pinch.addColdStream(new HeatStream("Reboiler", 150.0, 160.0, 2000.0));

// Set minimum approach temperature
pinch.setMinApproachTemperature(10.0);  // degrees C
pinch.run();

double minHotUtility = pinch.getMinHotUtility();   // kW
double minColdUtility = pinch.getMinColdUtility();  // kW
   pinch.getPinchTemperature();     

6. Emissions from Power Generation

// Fuel gas composition determines CO2 emissions
// CH4 + 2O2 -> CO2 + 2H2O
// C2H6 + 3.5O2 -> 2CO2 + 3H2O
// C3H8 + 5O2 -> 3CO2 + 4H2O

// Approximate: 2.75 kg CO2 per kg natural gas (varies with composition)
double fuelRate_kg_hr = fuelStream.getFlowRate("kg/hr");
double co2Factor = 2.75;  // kg CO2 / kg fuel (adjust for actual composition)
double co2_tonnes_yr = fuelRate_kg_hr * co2Factor * 8760 / 1e6;

// For a rigorous full-carbon-balance CO2, NOx, and methane-slip estimate use the
// catalog-driven GasTurbineUnit (section 7): gt.getCO2EmissionKgPerHr().

7. Right-Sizing & Dispatch (gasturbine sub-package)

For late-life or turndown studies where the question is "which turbines, how many, and at what load?" — use the catalog-driven classes under neqsim.process.equipment.powergeneration.gasturbine. These integrate directly with ProcessSystem and link to Compressor.getPower() via the PowerDemandConsumer interface.

Class	Purpose
GasTurbineCatalog	Loads the bundled gas_turbine_catalog.csv (14 aero + industrial models: LM2500, LM2500PLUS_G4, LM6000PF/PG, RB211_6562, Trent 60, SGT-700/750, Centaur 50, Taurus 60/70, Mars 100, Titan 130/250)
GasTurbineSpec	Immutable rating point (rated MW, ISO heat rate, exhaust flow/T, NOx, mass)
GasTurbinePerformanceMap	Part-load + ambient correction (aero vs industrial polynomials, min-load fraction)
GasTurbineDegradation	Recoverable + non-recoverable fouling vs fired hours, offlineWash() full reset and onlineWash(effectiveness) partial recovery
GasTurbineWashPlanner	Wash-interval economics: sawtooth with partial recovery, extra fuel/CO2/cost per interval, optimal interval, payback of a permanent on-line wash installation
GasTurbineEmissions	Full-carbon-balance CO2, NOx, methane slip from fuel composition
CO2TaxSchedule	Loads co2_tax_norway.csv (2020–2040 NOK/tonne, CO2 tax + EU ETS), linear interpolation
GasTurbineUnit	TwoPortEquipment — runs inside a ProcessSystem, accepts fuel Stream, aggregates Compressor shaft load via addPowerConsumer
TurbineDispatchOptimizer	Picks the cheapest feasible on/off combination (brute-force ≤8 units, merit-order above) with N+1 reserve
LateLifeRetrofitStudy	Year-by-year NPV / CO2-avoided / payback for baseline vs retrofit fleet over a declining demand profile

Water-wash interval and permanent-wash business case

When the question is "how often should we wash, and is a permanent on-line wash skid worth it?", drive GasTurbineWashPlanner from the plant's measured corrected-efficiency trend rather than a generic OEM rate. An energy-management system usually trends "corrected turbine efficiency" in percentage points; lossRateFromCorrectedEfficiencyTrend(ppPer1000FiredHours, cleanEfficiencyPercent) converts that KPI slope into the fractional loss rate the planner needs.

GasTurbineWashPlanner planner = new GasTurbineWashPlanner();
planner.setShaftPowerW(22.1e6);
planner.setBaselineHeatRateKJPerKWh(10090.0);
planner.setFuelLhvKJPerSm3(36500.0);          // from Standard_ISO6976 getValue("LCV","kJ/m3")
planner.setCo2PerSm3Fuel(2.06);               // carbon balance on the fuel composition
planner.setEfficiencyLossRatePerFiredHour(
    GasTurbineWashPlanner.lossRateFromCorrectedEfficiencyTrend(0.24, 92.0));
planner.setRecoveryEffectiveness(0.40);       // on-line ~0.3-0.5, off-line crank ~0.85-0.95
planner.setOutageHoursPerWash(0.0);           // on-line washing has no outage
planner.setWashCostPerEvent(20000.0);
planner.setFuelValuePerSm3(3.0);
planner.setCo2PricePerTonne(CO2TaxSchedule.loadDefault().getTotalNOKPerTonne(2026));
GasTurbineWashPlanner.WashPlan best = planner.optimize(24.0, 4380.0, 12.0);
double payback = GasTurbineWashPlanner.paybackYears(6.0e6, currentPractice, best);

Gotchas:

• The outage/deferment term dominates an off-line crank-wash case. Price it with an explicit deferment fraction and report the payback excluding it as the headline; a fully-deferred outage makes crank washing look arbitrarily bad.
• An off-line optimum that lands on the scan upper bound means annual crank washing is already the best off-line practice — the lever is on-line washing, not a shorter crank cycle.
• The two methods are complementary: on-line washing controls the sawtooth amplitude, off-line washing resets the residual (1-e)rT/e that an imperfect on-line wash leaves behind.

Catalog & site-corrected available power

GasTurbineSpec spec = GasTurbineCatalog.get("LM2500");
GasTurbineUnit gt = new GasTurbineUnit("GT-A", fuelStream, spec);
gt.setAmbientTemperatureK(273.15 + 30.0);  // hot day derate
gt.setDemandedPower(15.0e6);                // 15 MW shaft
gt.run(UUID.randomUUID());
double avail_MW = gt.getAvailablePowerW() / 1.0e6;
double load     = gt.getLoadFraction();
double co2_tph  = gt.getCO2EmissionKgPerS() * 3.6;

Linking turbine shaft to compressor demand

Each GasTurbineUnit aggregates the live shaft demand from any number of Compressor objects in the same flowsheet — the dispatcher reads it on every run():

ProcessSystem plant = new ProcessSystem();
plant.add(exportCompressor);     // existing Compressor
plant.add(injectionCompressor);
GasTurbineUnit gt = new GasTurbineUnit("GT-A", fuelStream,
        GasTurbineCatalog.get("LM2500"));
gt.addPowerConsumer(exportCompressor);
gt.addPowerConsumer(injectionCompressor);
plant.add(gt);
plant.run();   // gt sums Compressor.getPower() automatically

Fleet dispatch with N+1 redundancy

List<GasTurbineUnit> fleet = Arrays.asList(gt1, gt2, gt3);  // each is a GasTurbineUnit
TurbineDispatchOptimizer disp = new TurbineDispatchOptimizer(
        /*fuelPriceNOKPerKg*/ 4.5,
        /*co2CostNOKPerTonne*/ 1500.0);
disp.setRequireNplusOne(true);
TurbineDispatchOptimizer.DispatchResult r = disp.dispatch(fleet, 18.0e6);
if (r.feasible) {
    System.out.println(r.summary());   // running units, load, NOK/hr
}

Retrofit NPV vs baseline

double[] demandMW = new double[15];
for (int i = 0; i < 15; i++) demandMW[i] = Math.max(8.0, 20.0 - i * 0.8);

LateLifeRetrofitStudy study = new LateLifeRetrofitStudy(
        baselineFleet,    // e.g. 2x LM6000PF
        retrofitFleet,    // e.g. 2x SGT-700
        demandMW,
        /*startYear*/ 2026,
        CO2TaxSchedule.loadDefault(),
        /*fuelPriceNOKPerKg*/ 4.5);
study.setRetrofitCapexMNOK(800.0);
study.setDiscountRate(0.08);
study.setAnnualOperatingHours(8000);
LateLifeRetrofitStudy.RetrofitResult res = study.run();
System.out.println("NPV (MNOK):       " + res.npvMNOK);
System.out.println("CO2 avoided (t):  " + res.totalCO2AvoidedTonne);
System.out.println("Payback (yr):     " + res.simplePaybackYear);

When to choose this sub-package vs the legacy GasTurbine

Use legacy GasTurbine	Use GasTurbineUnit + catalog
You model the GT thermodynamically (compressor + combustor + expander) and care about exhaust composition into an HRSG	You are doing right-sizing, dispatch, retrofit, or fleet-level CO2/NPV studies and want vendor rating points, part-load + ambient correction, degradation, and N+1
Combined-cycle integration where exhaust gas feeds an HRSG	Late-life turndown, replacing oversized turbines, CO2-tax sensitivity

Flue-gas composition, NOx, SO2 and adiabatic flame temperature — CombustionCalculator

For the exhaust (flue-gas) composition and pollutant rates of any turbine, burner, or fired heater, use neqsim.process.util.combustion.CombustionCalculator. It deliberately splits the two physically different families of exhaust species — do not use a single Gibbs reactor for the whole problem:

• Major species (N2, O2, CO2, H2O, Ar) and SO2 — stoichiometric. These are combustion-complete (not equilibrium-limited at the exhaust), so an exact element balance of full combustion with excess air is used: all fuel C -> CO2, all fuel H -> H2O, all fuel S (e.g. H2S) -> SO2.
• NOx and CO — kinetically frozen. Thermal (Zeldovich) NO and CO quench in the exhaust. A Gibbs reactor over-predicts NO at flame temperature and returns ~0 at stack temperature, so it is the wrong tool. They come from public EMEP/EEA-style emission factors (g per GJ fuel LHV), which the caller replaces with a vendor guarantee or CEMS value.
• Adiabatic flame temperature is a rigorous NeqSim energy balance (bisection on the product mixture enthalpy so the released LHV heats the products from 298 K) — excess air lowers it via inert dilution.

SystemInterface fuel = new SystemSrkEos(288.15, 20.0);
fuel.addComponent("methane", 0.95);
fuel.addComponent("ethane", 0.03);
fuel.addComponent("H2S", 0.0002);
fuel.setMixingRule("classic");

CombustionCalculator.CombustionResult r = new CombustionCalculator(fuel)
    .setFuelFlowRate(7896.0)         // kg/hr (total combusted fuel)
    .setExcessAirRatio(3.2)          // GT ~3-3.5 -> ~14-15 vol% exhaust O2; burner ~1.05-1.2
    .setBurnerType(CombustionCalculator.BurnerType.GAS_TURBINE_DLE) // sets typical NOx/CO for the technology
    .setNoxFactorGPerGJ(130.0)       // optional: override with a vendor/CEMS value AFTER setBurnerType
    .setCoFactorGPerGJ(30.0)
    .setAssumedFuelH2sPpmv(5.0)      // used only if the fuel carries no sulphur
    .calculate();

r.getFlueMoleFraction("CO2");         // exhaust CO2 mole fraction
r.exhaustO2VolPercent;                // ~14 vol% for a GT
r.pollutantPpmv.get("NOx");           // NOx ppmv (emission-factor basis)
r.getMassRateKgPerHr("SO2");          // SO2 kg/hr (fuel-sulphur stoichiometric)
r.adiabaticFlameTemperatureK;         // rigorous NeqSim energy balance
String json = r.toJson();

Burner technology (BurnerType) — NOx and CO are combustion-technology-dependent, so the calculator ships a small burner database that sets typical factors: CONVENTIONAL (130/30 g/GJ), LOW_NOX (60/40), ULTRA_LOW_NOX (30/50), GAS_TURBINE_CONVENTIONAL (300/40), GAS_TURBINE_DLE (90/30), GAS_TURBINE_WET (130/60). A low-NOx technology trades lower NOx for somewhat higher CO. These are screening defaults on a natural-gas basis — always override with a vendor guarantee or CEMS value when available. Accuracy also depends on fuel composition (H2 raises flame temperature and NOx), excess air / O2, combustion-air preheat, load, humidity / water-steam injection and the reference-O2 reporting basis (3% for heaters, 15% for GT); the stoichiometric majors and SO2 are exact, only the emission-factor NOx/CO carry this technology sensitivity.

stoichAirFuelMassRatio / airFuelMassRatio, fuelLhvKJperKg, fuelEnergyGJperHr and the full massRateKgPerHr map (NOx key is NOx_as_NO2) are also returned. This pairs with GasTurbineVendorPerformance / GasTurbine (which give the fuel rate) and with the CO2 accounting above. The same setBurnerType(...) / emission-factor NOx/CO is available on the FurnaceBurner unit operation via setUseEmissionFactorPollutants(true) or setBurnerType(...).

Stack-emission reporting (dry basis, reference O2, mg/Nm3, Nm3/hr, t/yr)

For a regulatory stack-emission report (EU IED / EN 14792 NOx, EN 15058 CO, EN 14791 SO2) the concentration must be dry, at a reference O2, in mg/Nm3 — not wet ppmv. The calculator does this chain correctly:

• setReferenceO2VolPercent(3.0) for fired heaters/boilers, 15.0 for gas turbines. The result then carries pollutantPpmvAtReferenceO2 and pollutantMgPerNm3AtReferenceO2 (the value directly comparable with a permit limit). The reference-O2 correction C_ref = C*(20.9-O2ref)/(20.9-O2meas) is applied on the dry concentration at the dry exhaust O2 (exhaustO2VolPercentDry) — the 20.9 % basis is dry air, so mixing wet ppmv with it (a common mistake) is wrong.
• setNormalTemperatureC(0.0) (EU "Normal", 273.15 K; use 15/25 for other bases) drives the mg/Nm3 conversion and the normalized flue-gas flow flueGasNm3PerHrWet / flueGasNm3PerHrDry. Sanity check: 1 ppmv NOx-as-NO2 ~ 2.05 mg/Nm3, CO ~ 1.25, SO2 ~ 2.86 at 0 degC.
• setAnnualOperatingHours(8000) rolls the mass rates up to massRateTonnesPerYear (permit / annual report). pollutantPpmv is wet, pollutantPpmvDry is dry — always compare limits on the dry / ref-O2 outputs.

SO3 / acid dew point, other pollutants, NOx routes, actual stack conditions

The extended stack-emission physics (all optional, 0 / off by default so clean-gas results are unchanged):

• SO3 & acid dew point — setSo3FractionOfSox(0.03) splits fuel-sulphur oxides into SO2 and SO3 (typically 1–5 %). The result then reports SO3, the acidDewPointC (Verhoff-Banchero sulfuric-acid dew point) and always the waterDewPointC. The acid dew point (often 120–150 °C) is well above the water dew point and sets the cold-end / stack minimum metal temperature to avoid corrosion.
• Other pollutants — setPmFactorGPerGJ, setCh4SlipFactorGPerGJ, setVocFactorGPerGJ, setN2oFactorGPerGJ add particulates, methane slip, non-methane VOC and N2O (relevant for liquid/dual-fuel, lean-premix GT, and reciprocating gas engines). Each appears in massRateKgPerHr, massRateTonnesPerYear, and (for the gaseous species) the ppmv / mg/Nm3 maps.
• NOx route breakdown — the base NOx factor is the thermal (Zeldovich) route; add the additive setPromptNoxFactorGPerGJ (Fenimore) and setFuelNoxFactorGPerGJ (fuel-bound N). The result carries noxThermalKgPerHr / noxPromptKgPerHr / noxFuelKgPerHr and the total in massRateKgPerHr["NOx_as_NO2"].
• Actual stack conditions (dispersion/plume) — setStackGasTemperatureC(150.0) (the measured or heat-recovery-outlet temperature, NOT the adiabatic flame temperature) gives the actual volumetric flow stackActualM3PerHr (Am³/hr); adding setStackDiameterM(1.5) gives the stack-exit stackVelocityMPerS. setStackPressureBara sets the basis for the actual flow and the dew-point partial pressures.

Field calibration and fuel-composition / turndown studies

• Field-calibrate the emission factor to a CEMS/stack test point: calibrateNoxFromMeasuredPpmv(measuredPpmv, measuredExhaustO2VolPercent) (and the CO analogue) set a multiplicative factor so the model reproduces the measurement and scales to other loads on a fuel-energy basis. This anchors magnitude before predicting other conditions.
• Fuel-composition effect (e.g. ethane/propane ratio) is captured rigorously through stoichiometry, AFR, LHV and flame temperature. Optional enableThermalNoxScaling(refFlameTempK) scales NOx with the Zeldovich temperature dependence (Ta ~ 38000 K) — directionally correct (hotter flame -> more NOx).
• Fixed-air / minimum-fuel turndown: setAirFlowRate(kgPerHr) puts the calculator in air-driven mode — lambda floats from the fixed air, the fuel rate and the fuel composition, so you can lower the fuel rate and watch lambda rise (leaner), exhaust O2 rise and NOx fall. The result flags airDriven and subStoichiometric (lambda < 1, air-starved — outside the valid screening range). Caveat: enableThermalCoScaling(...) must not be used to predict CO over an excess-air (lambda) sweep — CO vs lambda is U-shaped (O2-driven), and the flame-T scaling predicts the wrong sign there; field-calibrate CO against measured CO-vs-O2 for load/turndown studies.

Physics basis / limits (state-of-the-art alignment): stoichiometry + excess air (Turns; GPSA; API 560/537), Zeldovich thermal NOx (Ta ~ 38000 K; Lefebvre), EMEP/EEA + EPA AP-42 emission factors, EPA Method 19 / EN 14792 reference-O2 correction, Verhoff-Banchero acid dew point. Prompt/fuel-N NOx and N2O/PM/CH4/VOC are available as optional emission factors; the SO3 split and acid/water dew points and the actual stack conditions are modelled. The one remaining physics limit is high-temperature dissociation in the adiabatic flame temperature (like a no-dissociation H&MB simulator it slightly over-predicts near stoichiometric). For rigorous flame chemistry use Cantera/CHEMKIN with a validated mechanism (GRI-Mech 3.0) — this class is the fast, auditable engineering-screening model consistent with how process simulators estimate emissions.

Combined-cycle retrofit (HRSG + SteamTurbine on top of the fleet)

To evaluate a bottoming cycle on top of a GasTurbineUnit retrofit fleet, feed the synthesised exhaust into the legacy HRSG + SteamTurbine. Use the per-unit exhaust mass flow and temperature from GasTurbineSpec (corrected by GasTurbinePerformanceMap if needed) to build an exhaust Stream, then size the bottoming cycle and add its power output to the retrofit LateLifeRetrofitStudy result as an annual energy credit (extra MWh × fuel-equivalent × CO2 factor). The 20-year rightsizing notebook (see below) demonstrates this pattern in section 10.

Reservoir + pipeline-driven shaft demand

Instead of a synthetic linear decline, drive the compressor shaft load from a physics-based reservoir + flow line model. A simple gas-law material balance on the reservoir gives (P_res, T_res) each year; a PipeBeggsAndBrills riser plus flow line gives arrival pressure at the platform; the export compressor suction pressure then sets shaft demand which the GasTurbineUnit / TurbineDispatchOptimizer resolves. This couples the late-life study to real field decline (recovery factor, reservoir size uncertainty) and is the right pattern when CO2 tax and turbine count must be evaluated against an uncertain production profile rather than a stipulated demand curve. Section 11 of the 20-year rightsizing notebook implements this end-to-end.

Worked example

See examples/notebooks/gas_turbine_rightsizing_20yr.ipynb for a complete 20-year late-life right-sizing study: catalog + site correction, degradation, dispatch with N+1, LateLifeRetrofitStudy with CO2TaxSchedule, HRSG + steam-turbine combined-cycle extension, and reservoir-driven demand.

Applicable Standards

Standard	Scope
ISO 2314	Gas turbine acceptance tests
IEC 60034	Rotating electrical machines
API 616	Gas turbines for petroleum industry
API 611/612	Steam turbines
ASME PTC 22	Gas turbine power performance
ASME PTC 6	Steam turbine performance

Common Pitfalls

Pitfall	Solution
Unrealistic efficiency (>45% simple cycle)	Typical: 30-40% simple cycle, 55-62% combined cycle
Missing air stream for gas turbine	GT requires both fuel and combustion air
Steam below saturation in turbine outlet	Check for wet steam — may need superheat or extraction
Pinch analysis with wrong units	HeatStream uses °C for temperature, kW for duty