The blending modeling process consists of mixing feedstocks from various upstream processes and some additives to make several blends per the required properties. Therefore, accuracy plays a major role in blend modeling. Any inaccuracy may result in the overall reduction of profit because it may sacrifice the quality of the product.
This topic walks through a generic blend modeling process valid for all blend optimizers in the market.
Components of Blending Modelling Process
- Gasoline blending blends several component streams into different grades of gasoline. Each component has its own specific importance and role. Generally, eight to fifteen components are blended simultaneously.
- Blend planning aims at increasing the net profit and keeping the component inventory balanced. Furthermore, by minimizing quality giveaway, it also helps to manage component export/import.
- The offline optimizer controls the volume and net composition of blends. It is used for single-recipe generation of gasoline, diesel, and fuel oil items. Furthermore, a monthly production estimate for multi-period blending can be driven out. However, it cannot schedule starting time of blend, perform blend sequencing, or simulate a processing unit. The offline optimizer also cannot model any change in stock qualities. There is no engineering judgment involved.
- Stock availability identifies the amount of stock available to blends. This is what determines the market price.
- Stock allocation deals with assigning stocks and pools to blends. Since refineries produce multiple products, stock allocation evaluates the energy and emission impacts of fuel systems.
- The blend should be prepared at a low cost to enhance profit while still meeting the prescribed specifications.
- Backcasting helps in calculating the ratio of a predicted value to actual results. In addition, it helps determine by what amount the calculations meet the theoretical predictions.
- Re-blending meets specifications by blending an off-test tank to meet requirements.
- Blend Studies deal with theoretical analysis of a situation of interest. Therefore, this topic is important as it sets out the steps and procedures to create the desired output.
- Recipe linking is useful for large blends. It causes different blends to have a similar recipe. Thus, it acts as a bridge for several blends altogether.
- Pooling combines several streams to form one component in blending. Thus, pooling maintains the vitality of blending by forming a single constituent as a whole.
- Suboptimality occurs when a solution that isn’t global optimum is converged to a solver.
- Heel track accounts for the quality and volume in blend tanks over a while. It is recommended to fill storage tanks with similar crudes for better profits so that the amount of value lost through mixing and degradation is reduced.
This topic describes the usage of a generic blend optimizer (and walks through all steps and required data to model a blending system).
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