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|Title: ||Integration of Hydrogen and CO2 Management within Refinery Planning|
|Authors: ||Alhajri, Ibrahim|
|Keywords: ||MINLP Optimization|
|Approved Date: ||2-Dec-2008 |
|Date Submitted: ||1-Dec-2008 |
|Abstract: ||The petroleum refining industry is considered to be one of the most important industries affecting daily life. However, this industry is facing many new and challenging situations, including such new trends as increased heavy crude markets, a shrinking market for fuel oils, clean-fuel legislation that encourages production of ultra low-sulfur (ULS) gasoline and diesel fuels, and strict green house gas (GHG) regulations to reduce CO2 emissions into the atmosphere. Refineries thus face a serious need to increase the capacity of their conversion units, such as the hydrocracker and fluid catalytic cracking units (FCCs), and to increase their consumption of hydrogen to meet the new requirements. These increases should be planned with reference to allowable CO2 emission limits. Refineries therefore need an appropriate tool for planning their operations and production.
This research focuses on refinery planning under hydrogen and carbon management considerations. A systematic method that uses mathematical programming techniques to integrate the management of hydrogen and CO2 for refinery planning is proposed. Three different models for refinery planning, hydrogen management, and CO2 management, are prepared and then properly integrated. Firstly, a Nonlinear Programming (NLP) model that provides a more accurate representation of the refinery processes and which is able to optimize the operating variables such as the Crude Distillation Unit (CDU) cut-point temperatures and the conversion of the FCC unit is developed. The model is able to evaluate properties of the final products to meet market specifications as well as required product demands, thereby achieving maximum refinery profit.
A systematic methodology for modeling the integration of hydrogen management and refinery planning was considered next. This resulted in a Mixed Integer Nonlinear Programming (MINLP) model that consists of two main building blocks: a set of nonlinear processing unit models and a hydrogen balance framework. The two blocks are integrated to produce a refinery-wide planning model with hydrogen management. The hydrogen alternatives considered in this research are hydrogen balancing, compressors, and purification processes. The model was illustrated on representative case studies and lead to an improvement in the hidden hydrogen unavailability that prevents refineries from achieving their maximum production and profit. It was found that an additional annual profit equivalent to $7 million could be achieved with a $13 million investment in a new purification unit.
The consideration of CO2 management and the integration with refinery planning and the hydrogen network required the formulation of a CO2 management model. This model focused on the refinery emission sources and the mitigation options. The refinery emissions sources are the fuel system, hydrogen plant, and FCC unit, and the mitigation options considered are load shifting, fuel switching, and capturing technology. The model performance was tested on different case studies with various reduction targets. The optimization results showed that CO2 mitigation options worked successfully together to meet a given reduction target. The results show that load shifting can contribute up to a 3% reduction of CO2 emissions, and fuel switching can provide up to 20% reduction. To achieve greater than 30% reductions, a refinery must employ capturing technology solutions. The proposed model provides an efficient tool for assisting production planning in refineries and at the same time determines the optimum hydrogen and CO2 emissions strategies.|
|Program: ||Chemical Engineering|
|Department: ||Chemical Engineering|
|Degree: ||Doctor of Philosophy|
|Appears in Collections:||Faculty of Engineering Theses and Dissertations |
Electronic Theses and Dissertations (UW)
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