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AI Autopilot — 25日間の管理されたパイロットで+6%のスループットと年間$781Kの利益増を達成。Brasil Mineral #441(2024年7月)。パイロット結果を見る
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実体経済を動かすAI。鉱業。産業。音声。2019年よりブートストラップ運営。
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プライバシーポリシー利用条件
Energy · Generation

Power generation — AI for combined-cycle, steam and gas turbines

AI Autopilot optimizes heat-rate across combined-cycle, peaker and baseload plants. It coordinates turbine loading, boiler firing, HRSG duty, and auxiliary power to push efficiency while respecting operational envelopes and emissions limits.

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ライブデモを試す
Combined-cycle gas turbine generator hall

概要

Every 1% of heat-rate improvement on a 500 MW combined-cycle plant is roughly $2-4M per year in fuel alone. Generators have wrung most of the easy gains out through CCMS upgrades and advisory tools — what is left requires real-time, multi-unit optimization that humans simply cannot manage.

Dispatch patterns, ambient conditions, and fuel quality all interact. Optimal loading for one unit is rarely optimal for the plant as a whole. Operators default to rules-of-thumb that leave dollars on the table during off-peak hours and during ramps.

BrainiAll AI Autopilot runs a multi-unit dispatch optimizer that accounts for current demand, ambient temperature and humidity, fuel price, emissions constraints, and equipment health. It recommends loading per unit, steam routing, and auxiliary adjustments — continuously, not once per shift.

-0.5-1.5%Heat-rate reduction typical
↑ MWNet output on hot days
PermitEmissions stay inside envelope
< 12 moTypical payback

Autopilotの機能

連続的・多変数制御 — 単一ループPIDではありません。アドバイザリ層アーキテクチャにより安全性はそのまま維持されます。

Multi-unit dispatch optimization

Coordinates loading across gas + steam turbines to minimize heat-rate across the total plant load curve.

Ambient-aware tuning

Adjusts inlet-air cooling, compressor washing, and dispatch to shifts in temperature and humidity.

Emissions-aware optimization

Holds NOx / CO within permit while maximizing efficiency — not at opposite ends.

Ramp & start-up guidance

Optimizes start sequences to cut fuel waste during non-steady-state hours.

Health-based dispatch

Equipment-condition scoring ranks units to delay maintenance costs without compromising reliability.

継続的に調整される変数

AIはサークルのすべてのセンサーを読み、最適なセットポイント組み合わせをリアルタイムで解決します。

  • Load (MW) per unitPrimary dispatch lever.
  • Inlet-air cooling / foggingHigh-impact on hot days.
  • HRSG duty & diverterRoutes heat between steam and bypass.
  • Combustion air / fuel ratioNOx-efficient trim.
  • Auxiliary power (house load)Often under-optimized.
ビジネスケース

On a 500 MW combined-cycle block, a 1% heat-rate improvement at $4/MMBtu gas is worth roughly $2-3M/year. Add ambient-tuned output on hot days and the business case gets stronger. Payback under a year in most deployments.

既存のコントロールシステムと統合

GE Mark VIeSiemens SPPAMitsubishi DIASYSABB 800xAEmerson OvationHoneywell Experion

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AI Autopilotがあなたの工場で何を開くかを見る

Free Bottleneck Assessment - 私たちのエンジニアはあなたの工場データを分析し、事実に基づくレポートを10営業日以内に提供します。

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