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GITA50001

Petrochemical & Refining

A complex network of fired heaters, steam and compressors whose optimization requires an integrated energy-process view.

In petrochemical and refining plants, energy flows as fuel to fired heaters, as high- and medium-pressure steam, and as electricity to compressors and pumps, and these flows are tightly interdependent. Fired heater combustion efficiency, the health of the steam network and its traps, and the volume of gas burned in the flare are among the most significant loss centers. Because units typically run continuously at variable feed rates, energy analysis must normalize against feed rate and ambient conditions rather than compare raw consumption alone.

Energy management challenges in petrochemical and refining

Energy losses in the steam network from failed steam traps that often go undetected

Low fired heater combustion efficiency caused by fouling and poorly tuned excess air

Volume of gas burned in the flare, both an energy loss and an environmental risk

Complexity of the integrated energy-process network, which makes single-equipment analysis misleading and calls for pinch analysis

Ambient temperature swings affecting condenser and cooling tower performance

Coordinating unit turnarounds with abnormally high transient energy consumption

Gita 50001 for petrochemical & refining

Fired heater combustion efficiency monitoring

Continuous calculation of combustion efficiency from stack temperature and excess oxygen, giving early warning of burner tuning or cleaning needs.

Steam network and trap management

Logging steam trap status and estimating the energy loss of each failed trap to prioritize repairs by return on investment.

Flare gas volume monitoring

Logging and trending the volume of gas burned in the flare to spot abnormal patterns and track gas recovery initiatives.

Integrated energy-process modeling

Supporting pinch analysis and logging heat recovery opportunities between process streams to reduce purchased fuel and steam.

Feed-rate-dependent baseline

Regression modeling of unit energy consumption against feed rate, ambient temperature and production rate for a genuine period-to-period comparison.

  • Fired process heaters
  • Steam network and steam traps
  • Process compressors
  • Flare system and gas recovery
  • Distillation columns and transfer pumps
  • Cooling tower
  • Utility unit and boilers
  • Unit feed rate
  • Ambient temperature
  • Product output rate
  • Steam network pressure
  • Feed composition

0.0GJ/t

Process unit energy intensity index

Based on feed throughput, varies by unit type

0%

Typical loss share from failed steam traps

Of total energy distributed through the steam network

0%

Fuel reduction potential from combustion tuning

From optimizing the air-to-fuel ratio of fired heaters

At a refining unit, systematic logging of steam trap condition and repair prioritization by estimated energy loss per trap, combined with periodic tuning of the air-to-fuel ratio in fired heaters, enabled a measurable reduction in both purchased steam from the utility unit and heater fuel consumption over one full maintenance season.

The figures and charts shown on this website are illustrative sample data used to demonstrate the software's capabilities and do not reflect the actual performance of any organization.

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