A power plant with an average heat rate of 10,300 Btu/kWh is running at 33% efficiency. A 1% improvement on a 500 MW gas unit is worth $580,000 in fuel savings every year. A 2% availability recovery on the same unit is worth over $2 million in generation revenue. And the auxiliary load — the fans, mills, pumps, and precipitators the plant itself consumes — quietly eats 7 to 12% of gross generation on coal units, 5 to 10% on average, and doesn't even get benchmarked at most stations. Every one of those numbers is measurable. Every one of them moves. And every one of them is being reviewed once a month at most stations in an end-of-shift heat rate report — a report that is a bill, not a warning. The plants that recover heat rate, cut auxiliary consumption, and protect availability don't do it with new turbines. They do it with live visibility across every unit on the station, benchmarked against the same unit's history and the fleet's peers, with the drift caught while it's still 20 Btu/kWh instead of 200. iFactory Generation Efficiency Analytics is built to run exactly that — plant-wide, unit by unit, live.
iFactory Generation Efficiency Analytics
Plant-Wide Visibility on Heat Rate, Aux Load, and Availability — Live
One dashboard across every unit on the station: heat rate deviation, auxiliary consumption, availability, and capacity factor — trended against the unit's own baseline and against the fleet.
$580K
saved per 1% heat rate gain
$2M+
from 2% availability recovery
7-12%
coal aux load range
25-30%
forced outage cut, PdM
The Live Station Dashboard — What Every Unit Should Say
Plant-wide visibility means every unit reporting the same four KPIs against its own baseline, live, at the same moment. This is what a station dashboard looks like on a mixed-fleet plant — with drift flagged inside each tile before it needs to hit anyone's inbox.
Unit 1
Coal 500 MW
On target
Heat rate10,280Btu/kWh
Aux load7.2%gross
Availability92.1%30-day
Capacity factor78%MTD
Heat rate10,460+180 vs baseline
Aux load8.6%+1.4 pts
Availability89.4%30-day
Capacity factor74%MTD
Unit 3
Gas CCGT 450 MW
On target
Heat rate7,020Btu/kWh
Aux load2.4%gross
Availability95.8%30-day
Capacity factor62%MTD
Unit 4
Wind 120 MW
Curtailed
Availability86.3%30-day
Capacity factor31%MTD
Curtailment4.2%MTD
Fleet ranking2 of 4station
Heat Rate — Where the Fuel Actually Goes
Heat rate is the single most important efficiency metric in power generation. It tells you how many Btu of fuel it takes to make one kWh of electricity — and how far the plant is from the theoretical best. The gap between the two is where every dollar of fuel recovery lives.
Theoretical
3,412 Btu/kWh
100%
Best-in-class CCGT
6,800-7,000
~50%
Modern coal supercritical
8,800-9,200
~38%
Coal fleet average
10,300
~33%
Aging coal at 40+ years
11,000+
~31%
1% improvement on a 500 MW gas unit = $580K/year in fuel. On coal, the math is comparable and the gap-to-benchmark is usually wider.
The Auxiliary Load Nobody Watches
Every plant consumes some of its own generation to run its fans, mills, pumps, precipitators, and cooling. That's auxiliary load — measured as a percent of gross generation — and it's one of the biggest recoverable numbers in the industry. On coal units, it ranges from 7% at best-in-class 500 MW plants to 12% at smaller aging units. Every point above benchmark is generation you produced and then paid to consume.
Nuclear
1-3%
Steady base loads, mature systems. High-consequence anomalies rare but expensive.
Gas turbine
<2-3%
Simple aux systems. Any creep above 3% is a red flag worth investigating.
Coal (best)
5-7%
Large modern units with efficient FGD, SCR, and fan drives.
Coal (avg)
7-10%
Where most fleet units sit — every point recoverable adds real dollars annually.
Coal (aging)
10-12%
Reliability trouble. Fan wear, mill inefficiency, and pump degradation stacked together.
Want to see where your auxiliary load actually sits? Book a demo — bring one month of station-service data and we'll break it down.
Availability × Heat Rate — Same Dollars, Two Doors
Availability and heat rate are both efficiency levers, but they hit the P&L in different ways. Availability is about generation revenue you missed. Heat rate is about fuel cost you paid extra for. Both matter, and the same live-monitoring stack catches both.
Availability
"How much generation did we lose to outages?"
Forced outage rate drives lost revenue
2% availability gain = $2M+ on a 500 MW unit
Vibration, temp, oil sensors cut forced outage 25-30%
Predictive maintenance is the primary lever
Heat rate
"How much fuel did we spend for each kWh?"
Every extra Btu/kWh is fuel you paid extra for
1% heat rate gain = $580K on a 500 MW gas unit
Boiler, turbine, cold-end, aux — all contribute
Live per-unit trending is the primary lever
What Live Analytics Actually Change
The value of moving from monthly reports to live analytics isn't just cleaner data — it's earlier action. Every drift caught two weeks earlier is two weeks of fuel or generation that stops being wasted.
01
Ingest Historian
MW, fuel flow, steam conditions, aux drives, ambient — pulled live from PI, AVEVA, or GE Historian across every unit.
02
Compute Live KPIs
Net heat rate, gross-net difference, aux %, availability, capacity factor — recalculated every interval per unit.
03
Normalize & Baseline
Load-band, ambient, and fuel-quality corrections applied before drift detection runs on the baseline.
04
Flag & Attribute
Drift ranked by dollar impact. Attribution to boiler, turbine, cold-end, or aux systems — not just the total number.
05
Verify Recovery
Post-action chart confirms KPI returned to baseline — event closes with quantified fuel and revenue impact.
What Plant-Wide Visibility Delivers
Live analytics on generation efficiency pay back in the same currency the plant already spends most heavily — fuel and capacity revenue. These are the outcomes stations typically see after moving from monthly performance reports to live analytics across every unit.
$580K
Per 1% heat rate
on a 500 MW gas unit, in fuel
$2M+
Per 2% availability
from recovered generation revenue
25-30%
Forced outage cut
within 12 months of PdM deployment
Lower
CO₂ per MWh
from every Btu/kWh recovered
Curious what a fleet-wide view would surface on your station? Talk to our generation team — we'll benchmark your units against the fleet.
Frequently Asked Questions
How is this different from what our PI displays already show?
PI shows the reading. Generation Efficiency Analytics shows the deviation, the ranked cause, and the dollar impact. Your PI trend can tell you heat rate is 10,460 Btu/kWh. It can't tell you that's 180 Btu/kWh worse than your unit's normalized baseline for this load and ambient, that most of the gap is in cold-end losses, and that at current fuel prices it's costing you $18,000 per day. That translation from reading to action is what the analytics layer adds.
Which fuel and unit types does this handle?
Coal (subcritical, supercritical, ultra-supercritical), gas (open cycle and combined cycle), nuclear, and renewables (wind and solar for availability and capacity-factor tracking). Each fuel type has its own baseline logic — combined-cycle heat rate normalizes for ambient temperature, coal normalizes for GCV and moisture, wind normalizes for wind resource — so cross-fleet comparison stays honest.
How does the auxiliary load monitoring actually work?
By reading station-service and unit-auxiliary meters and computing gross-to-net delta continuously. The system separates unit-auxiliary consumption (fans, mills, pumps directly tied to a unit) from station-auxiliary (fuel handling, water treatment, lighting) — because they have different owners and different drift patterns. Coal units typically show 7-10% total; anything above 10% is a reliability signal worth investigating.
How much heat rate improvement is realistic in year one?
Most stations that move from monthly reporting to live analytics recover 50-150 Btu/kWh in the first year — worth $290K to $870K per 500 MW unit in fuel. The gains come from catching drifts weeks earlier: condenser fouling, APH leakage creep, aux drive degradation, excess air drift. Nothing exotic. Just seeing the drift while it's still worth fixing cheaply.
Can we see it running on our station before committing?
Yes. Bring one or two units and 60-90 days of historian data. We'll build the normalized baseline for each unit, compute live heat rate and aux load, and show every drift that would have been flagged and the fuel and revenue value of catching it. Book a demo and we'll walk it live on your data.
Stop reviewing what already happened.
See Live Generation Analytics On Your Own Station
Bring one or two units and 90 days of historian data. We'll build the normalized baseline per unit, run live heat rate and aux-load analytics, and show every drift SPC would have caught weeks before your next performance review — with the fuel and revenue impact quantified.
