Integration of Hydrogen and CO2 Management within Refinery Planning

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

A MULTIDISCIPLINARY TECHNO-ECONOMIC DECISION SUPPORT TOOL FOR VALIDATING LONG-TERM ECONOMIC VIABILITY OF BIOREFINING PROCESSES

Increasing demand for energy and transportation fuel has motivated researchers all around the world to explore alternatives for a long-term sustainable source of energy. Biomass is one such renewable resource that can be converted into various marketable products by the process of biorefining. Currently, research is taking strides in developing conversion techniques for producing biofuels from multiple bio-based feedstocks. However, the greatest concern with emerging processes is the long-term viability as a sustainable source of energy. Hence, a framework is required that can incorporate novel and existing processes to validate their economic, environmental and social potential in satisfying present energy demands, without compromising the ability of future generations to meet their own energy needs. This research focuses on developing a framework that can incorporate fundamental research to determine its long-term viability, simultaneously providing critical techno-economic and decision support information to various stakeholders. This contribution links various simulation and optimization models to create a decision support tool, to estimate the viability of biorefining options in any given region. Multiple disciplines from the Process Systems Engineering and Supply Chain Management are integrated to develop the comprehensive framework. Process simulation models for thermochemical and biochemical processes are developed and optimized using Aspen Engineering Suite. Finally, for validation, the framework is analyzed by combining the outcomes of the process simulation with the supply chain models. The developed techno-economic model takes into account detailed variable costs and capital investments for various conversion processes. Subsequently, case studies are performed to demonstrate the applicability of the decision support tool for the Jackson Purchase region of Western Kentucky. The multidisciplinary framework is a unique contribution in the field of Process Systems Engineering as it demonstrates simulation of process optimization models and illustrates its iterative linking with the supply chain optimization models to estimate the economics of biorefinery from multi-stakeholder perspective. This informative tool not only assists in comparing modes of operation but also forecasts the effect of future scenarios, such as, utilization of marginal land for planting dedicated energy crops and incorporation of emerging enzymatic processes. The resulting framework is novel and informative in assisting investors, policy makers and other stakeholders for evaluating the impacts of biorefining. The results obtained supports the generalizability of this tool to be applied in any given region and guide stakeholders in making financial and strategic decisions

Discourse and sociotechnical transformation: the emergence of refinery information systems

This thesis considers the emergence and diffusion of British Petroleum's (BP) Refinery Information Systems (RIS). Insights from the associology of translation are coupled with the Foucauldian concepts of discourse and power /knowledge in order to analyse accounts of the system provided by organisational participants. The analysis suggests that a new form of managerialism, or "new commercial agenda" is being selectively deployed both within BP and within the wider commercial world. This transformed managerialism seeks to maintain control and heighten commercialism through a re- working of hierarchical relations within the organisation. Artefacts and practices of organisational life are revealed as prime vehicles for instantiating this new agenda and BP's Refinery Information Systems are thus seen to be both a condition and a consequence of the changes underway

Modeling and Optimization of Gas Networks in Refinery

Master'sMASTER OF ENGINEERIN

ECOS 2012

The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology

Development and Integration of Simple and Quantitative Safety, Pollution and Energy Indices into the Design and Retrofit of Process Plants

Currently, the main focus in a chemical process design is cost reduction and profitability. This approach results in high expenditure due to the generation of huge amounts of wastes, which in turn requires waste control stations such as wastewater treatment facility, incinerator and so on. In other words, in conventional design the waste reduction is carried out at the late stage of process design, sometimes referred to as the end of pipe treatment, which causes impacts on environment, inventory of hazardous chemicals, energy consumption as well as cost impacts on the process. Due to all the above aspects, the impact of decision making is highest at the conceptual phase of a process design. However, this impact can be minimized by shifting the waste reduction from the late step of the process design to its early stage. There are several barriers for such shifting; the most important of which is the lacking of a methodology to be used as a screening tool at the conceptual design phase in order to select the inherently safer and the environmentally friendlier design. The objective of this thesis is to develop simple and quantitative indices that can be employed in minimizing the adverse effects of material and energy emissions from chemical industries. Several improvements to existing methodologies for pollution minimization are given. These are based on waste reduction concepts and are applicable from the initial step of a process design to revamping of existing processes. A simple risk index for the evaluation of risks to the safety of chemical processes is also developed. The work provides indices for evaluation of potential environmental impacts as well as safety risks of a chemical process in order to reduce the hazardous wastes generation and energy consumptions as well as safety risks reduction while maintaining the process throughput and profitability. This research offers new methodologies, which have significant contributions in sustainability development by providing new and simple indices to be employed at initial step of a chemical process design with minimum available process data for the evaluation of energy impacts of the process on the environment and at the same time for the assessment of the risks to the chemical process. These new indices are combined with the well-known WAR algorithm to offer a composite index to help investors, regulators and also process designers to select the sustainable design from other process design array. The new methodology uses Key Process Index (KPI) for ranking purposes merely from technical point of view. Even when two or more sustainable processes are concerned, the composite index can find the inherently safest, environmentally friendliest process without trade off with process economy and profitability. So, the new indices can be renamed as “Must Know Composite Indices” for chemical process designers. These Must Know Composite Indices are illustrated on several case studies and are proven to be effective tools on several fronts such as: 1. As screening tools for investors/owners who need not be experts in chemical, environmental or safety engineering. They usually receive a bunch of proposals after advertising a tender for a new project or retrofitting an existing chemical process plant. The utilization of the Must Know Composite Indices will allow them to enter the available process and economic and calculate all indices, rank the proposals and recommend the top ranked processes. 2. As screening tools for process designers: A process engineer will get into the insight of design alternatives in terms of environmental protection, inherent safety and energy impacts of the alternative designs. Then, s/he will make necessary changes to make a sustainable design at minimum impacts of decision at conceptual design stage. 3. As a coding system for process design similar to piping codes. For instance, KPI 1234 (234, 500, 500); where 234, 500 and 500 are the contribution of energy impacts, environmental impacts and safety risks to the process design, respectively. 4. As an incentive/penalty tool for the government in order to penalize plants who are harmful to the environment and society or to, otherwise, provide stimulus programs