A Novel Scheduling Strategy for Crude Oil Blending

Bai, Liang; Jiang, Yongheng; Huang, Dexian; Liu, Xianguang

doi:10.1016/s1004-9541(09)60129-4

Cited by 20 publications

(37 citation statements)

References 19 publications

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“…In a study related to the stabilization of feedstock properties in refineries (by combining different types of crude oil), a two-level optimization procedure based on a hybrid algorithm combining Tabu search (TS) and DE was proposed (Bai et al 2010). As the true boiling point influences the yield and the operational stability of the crude distillation unit, this parameter was used as a main quality index for evaluating the crude oil properties.…”

Section: Modified and Hybrid De Variants Inmentioning

confidence: 99%

The use of differential evolution algorithm for solving chemical engineering problems

Drăgoi

Curteanu

2016

Reviews in Chemical Engineering

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AbstractDifferential evolution (DE), belonging to the evolutionary algorithm class, is a simple and powerful optimizer with great potential for solving different types of synthetic and real-life problems. Optimization is an important aspect in the chemical engineering area, especially when striving to obtain the best results with a minimum of consumed resources and a minimum of additional by-products. From the optimization point of view, DE seems to be an attractive approach for many researchers who are trying to improve existing systems or to design new ones. In this context, here, a review of the most important approaches applying different versions of DE (simple, modified, or hybridized) for solving specific chemical engineering problems is realized. Based on the idea that optimization can be performed at different levels, two distinct cases were considered – process and model optimization. In both cases, there are a multitude of problems solved, from different points of view and with various parameters, this large area of successful applications indicating the flexibility and performance of DE.

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Section: Modified and Hybrid De Variants Inmentioning

confidence: 99%

The use of differential evolution algorithm for solving chemical engineering problems

Drăgoi

Curteanu

2016

Reviews in Chemical Engineering

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“…The location of wax appearance increased dramatically as the crude oil heat capacity increased, whereas the location of wax appearance slightly increased as the crude oil density increased. The heat capacity of crude oil is the quantity of heat, or heat rate, required to change the temperature of a kilomole of crude oil by 1 o C [23,24]. Heat capacity increases the amount of energy required to decrease crude oil temperature along the pipeline.…”

Section: The Effect Of Density and Heat Capacity On Pipe Distance Or mentioning

confidence: 99%

Computational Fluid Dynamics Simulation of a Crude Oil Transport Pipeline: Effect of Crude Oil Properties

Rukthong

Piumsomboon

Weerapakkaroon

et al. 2016

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Abstract.Transporting crude oil inside a pipeline is a common process in the petroleum industry. Crude oil from different sources has different properties due to terrains and climates which cause the transport profile to change during operations. In this study, the computational fluid dynamics model was developed using computer language code. The governing equations were employed to study the effect of crude oil properties such as crude oil density and viscosity on the transport profile using the 2 4 factorial experimental design. A good agreement between the developed numerical model and commercial software suggests that the proposed numerical scheme is suitable for simulating the transport profile of crude oil in a pipeline and predicting the phenomena affecting conditions. The result showed that the heat capacity and density of crude oil had statistical significance to the transport profile at 95% confidence level. The heat capacity had the most significant effect on wax appearance. Therefore, the physical properties of crude oil should be modified to prevent the occurrence of wax inside the crude oil pipeline.

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“…Thus, the yields of the fractions, the compatibility and the viscosity of the mixed oils should be considered as the model's objective. Referenced with the articles (Dong, 1990;Bai et al, 2010), the objectives of the model can be simplified as the total profit of all fractions (≤350 • C) would be as large as possible; the viscosity of mixed crude oil would be as small as possible in theory.…”

Section: The Preparing For Modelmentioning

confidence: 99%

“…Downloaded by [McGill University Library] at 07:24 07 February 2015 The total profit of all fractions distilled from the mixed crude oil in theory (Bai et al, 2010) is…”

Section: The Preparing For Modelmentioning

confidence: 99%

“…In order to reduce operating costs, improve the efficiency of pipelines and storage tanks, the crude oil tended to be mixed before the transporting, storing, and refining (Bai et al, 2010;Rubio and Yu, 2004;Oddsdottir et al, 2013). Due to the changing of the relative content of each component in the oil, the incompatible happened in the mixing of the different crude oil, which can result in the flocculation and deposition of the asphaltenes, and furthermore, may lead to severe fouling or coking on the process units (e.g., the storage tanks, transporting pipelines, heat exchange tubes; Radhakrishnan et al, 2007;Álvarez et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

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An Optimization Model for Shanbei Crude Oil Blending

Li¹,

Hou²

2015

Petroleum Science and Technology

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The basic properties of the Shanbei crude oils and its mixed were studied first. Then, a hybrid coefficient function for the viscosity of the mixed oils was introduced. With these, an optimization model of the proportion for the crude oils blending was established and solved. An applicable proportion for six Shanbei crude oils' blending was given. With the proportion, one mixed oil was prepared and distilled. Fouling and coking are discussed with the simulation in the distillation to assist the optimization. The experiment results showed that the model was valid for the oils blending.

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A Novel Scheduling Strategy for Crude Oil Blending

Cited by 20 publications

References 19 publications

The use of differential evolution algorithm for solving chemical engineering problems

The use of differential evolution algorithm for solving chemical engineering problems

Computational Fluid Dynamics Simulation of a Crude Oil Transport Pipeline: Effect of Crude Oil Properties

An Optimization Model for Shanbei Crude Oil Blending

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