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VisualMesa Oil blending

Multi-Period Blending Optimizer

Optional Supply Chain Scheduling System Plugin for Multi-Period Blending Optimization

Includes Multi-Product & Multi-Blend Optimization

Refinery & Petrochemical Feeds & Products

The objectives in the optimization include such objectives as: minimize octane giveaway, minimize deviation from planned recipe, minimize the use of more costly blend components, meet governmental and environmental requirements, avoid running out of blend components over the planning horizon, and many more.

Blending operations

VM-SCS provides support for the simulation and optimization of blending operations. The simulation model allows the calculations of the mix properties for the materials being blended. There are several methods for computing the mix value depending on the property. The most common are: linear volumetric average and linear weight average. For other properties with non linear mix behavior, specific methods are applied, as for Reid Vapor Pressure, Octane Number, Cetane Number, Aniline Point, etc.

In the case of crude oil properties, VM-SCS provides models for estimating the assay properties of the crude blend using the individual crude assay for each component of the blend.

Blending models are available both for steady-state operation and for batch blending. This means that the non linear blending properties are calculated as continuous variables being integrated along the time for batch operations. This capability allows the tracking of the blend properties along the batch blend operation.

Multi-Period Blending supports 3 optimization models:

  • Minimum cost recipe for a given spec with constrained stocks availability
  • Minimum cost corrective recipe for fixing out-of-spec batches
  • Minimize the deviation with a target recipe

Additionally, VM-SCS provides model for optimizing the recipe for blending operations. These optimization models minimize the cost of creating a blend of specified properties by using a pool of component with different qualities and cost. The optimization models are based on NLP and MILP mathematical programming.

For more information about VisualMesa Supply Chain Scheduling's blending optimizer, please contact us.

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Crude Oil, Gasoline & Fuels Blending
Multi-Period, Multi-Product Blending Optimizer
Crude Oil, Gasoline, Diesel, Fuel Oil, Bunker Oil, Heating Oil, Asphalt, Naphtha Feedstock
Multi-Blend Optimizer
Simultaneous Optimization of Dual Blender Lines
Component Tank & Unit Rundown Blending
Blending to Pipeline or Tank with Heel
Considers all Constraints & Component Inventories

Product blending user screen for defining each blend to be considered in the multi-period optimization. Setting start of blend, blend volume, setting specifications for RON, MON and RVP. Setting blend components allowed for the blend along with min & max blend limits. Provides control of blend optimization steps such as Minimize Blend Cost and Minimize Recipe Deviation.

VisualMesa Multi-Period Optimizer fully integrates the optimization: minimizing the use of more costly blend components but not at the expense of future blends, thereby avoiding running out of blend components over the planning horizon, while meeting governmental and environmental requirements; integrates to distribution in this illustration to product pipeline.

Optimal Feed Blend & Plant Constraints
i.e., Aromatics plant condensate feed blend optimization
Feed component for blending, CDU Kero effluent
Active constrained property is "Acidity of Kero", <= 0.04
Maximize the heavy naphtha content of the feed blend
Subject to sulphur and acidity constraints
Similar to crude selection, blending and feed scheduling taking into account a CDU/VDU yield model limited by throughput constraints downstream, such as heavy ends processing limits at coker or hydrocracker, hydrodesulfurization limit and such.

energy efficiency