Bio fuel

Solutions : Blending optimization

Better margins and an edge on the competition equal long-term success for refineries. The refining industry has proven the benefits of efficient online analysis in the blending optimization loop; successful applications save $0.05-$0.30/bbl.
We provide complete solutions that allow the monitoring and optimization of the blending stage.
Without this technology, the refinery is forced to strike a balance between giveaway and the costs of re-blending, excess inventory, demurrage, or missed shipments

Technology Summary

The blending optimization loop begins with measurement. We accurately and efficiently measure properties in real-time, on-line and/or off-line, using Near Infra-Red analyzers and Topnir models (See Topnir Technology).
The solution provides the End User with the facility to efficiently prepare and run the operation with full confidence all along the blend.
Our solution is compliant with any existing facilities and has been interfaced with most of the DCS, Regulatory blend controlers and blending optimizers.

Blend Preparation
The first step consists in measuring the destination tank heel and blending components quality using Topnir model implemented off-line (less than 1 minute per product are required to output the full suite of properties). The blending optimizer uses this fresh and accurate quality information to output the best achievable recipe.
Note that we can either provide our own optimizer (Optiblend) or interface Topnir to the existing optimization system.

Blend Operation
Topnir implemented on line provides every 1 minute all the properties required by the blender header (No limitation of number of properties). The information is transferred to the DCS and allows maximizing the blending optimizer efficiency.
For complex blending process, where no intermediate component tanks are being used, our technology allows to monitor on-line multiple streams (components and blender headers) using a single analyzer

Typical savings

Give away minimization

  • Accurate and frequent predictions on constrained properties
  • Insures maximum efficiency of the blending optimization loop
    Typical savings: 1 - 3 M$/Year per pool

    Re-blend reduction

  • Demurrage costs reduction
  • Inventory reduction and yearly production increase
    Savings: 1 M$/Year

    Laboratory work load reduction

  • Increase analyzes frequency
  • Daily tasks reduced on conventional analyzes
    Savings: 250 K$/Year
    Maintenance cost reduction
  • Offline and online apparatus to be maintained at very low frequency
  • Only single model to be maintained on regular basis
    Savings: 250 K$/Year

Key advantages

Predictions accuracy & model robustness

The keys of success and benefits from this NIR application are definitely the model accuracy and robustness.
Topnir complies with ASTM/ISO standard and therefore offers the same accuracy as the conventional analyzers; but compared to those analyzers, Topnir provides the full suite of properties in less than 1 minute!
Furthermore, the increased robustness obtained thanks to the densification process and know-how allows Topnir to efficiently handle the blending real life, including atypical blending recipe and process variation.

Management of Additive Effect

(See also Additive optimization)
When additive is input to boost the Cetane Number and the CFPP, Topnir is able to predict the final properties, based on the NIR spectra and the amount of additive input.
Topnir’s sister product “Optiblend” also optimizes (off-line and/or on-line) the required additive input to reach the commercial specifications. Integration of the tank additives amount allow a complete monitoring of the tank properties

Direct Prediction of Blending Indices

To improve the consistency across the successive optimization chain, Topnir calculates the linear blending indices of each component in a particular grade. These parameters integrate “Positive/negative” effect of the different component and make the blending optimization stage more accurate and far much easier.
KEROSENE GASOIL
True Values Blending Indices True Values Blending Indices
Density @15 0.795 0.795 0.845 0.845
Cloud point -45 -35 -5 0
Flash point 38 33 65 70
Cetane Index 43 40 50 55

Blend Simulation Features

This Topnir feature enables the operators to drive the blend and detect any risk in re-blending from the spectral graphical interface.

Number of calibration samples

Only 20 samples per grade and 5 samples per blending components have to be measured in the laboratory. Our approach is to use the results available for products quality certification to minimize the laboratory workload.
Diesel Blending Cetane Number, Cetane Index, Cloud Point, CFPP, Pour Point, Flash Point, Viscosity, Density, ASTM Distillation D86, Aromatics ,...
Gasoline Blending RON, MON, RVP, DVPE, %Aromatics, % Benzene, %Olefins, % Naphtene, % Parafins, MTBE, ETBE, Oxygenate, ASTM Distillation D86, Density,...

Mogas & Diesel Blending Topnir advantages

Optimization Maximizes refinery profits by giving a straightforward achievement of finished products according to commercial specifications.

Typical profits :

Between 1 to 5 MUS$ per year depending on refinery throughput.

  • Finished products accurate quality measurements

  • Blending components quality measurements

  • Additives response predictions

  • Diesel additives input optimization

  • Accurate direct calculation of blending indices

  • Innovating off-line blending optimizer

  • Minimize quality give-away

  • Minimize re-blending operations

  • Reduce demurrage cost

  • Manage components inventory

  • Increase throughput

  • Reduce laboratory workload

  • Reduce analyzer maintenance cost

Real Case Study

Gasoline yearly production: 1300KT
3 Grades, main constraints on Octane and RVP

Incremental Benefits on Gasoline blending

Item   Yearly savings ($)  
Give away minimization (0.3 on Octane and 4 KPa on RVP) 2.9 M $
Re-blend rate minimization (from 20% to 7%) 1.3 M $
Sampling and laboratory cost minimization not estimated
Maintenance cost reduction not estimated
Yearly Global Saving  4.2 M $

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