Research On Optimization Of Hydrogen System In Refinery And Its Application

During the past decade, crude oil has become heavier and contains more sulfur and nitrogen, while clean fuels specifications are progressively tightened via the market and legislation for environmental protection. Hydrocracking and hydrotreating, which consume the most part of hydrogen in refinery, are used more and more widely to upgrade heavy oils to obtain more valuable products. As the demand for hydrogen grows, hydrogen cost has become the second most important cost after the cost of crude oil. Optimization of hydrogen systems will play a great role in energy saving, and definitely will bring considerable profit to the refinery at the same time. In this thesis, after the summary of the recent research issues in refinery hydrogen system, challenging issues about the optimization of hydrogen system in refinery are investigated systematically. Finally, case studies based on the data from real refineries are presented to illustrate the effectiveness and feasibility of the proposed approaches. The main contributions of this thesis are as follows:1) Two improved systematic mathematical approaches are developed based on a two-step approach and a simultaneous optimization approach respectively for the optimization design of hydrogen system in refinery. To make the approaches proposed more practical for the real system application, the flowrate and purity at the reactor inlet of hydrogen consumers and the recovery of purification units are considered as optimization variables, and at the same time the minimum pure hydrogen of hydrogen consumers will be satisfied. Mixed integer nonlinear programming (MINLP) models are formulated with the objective function of the minimization of total annual cost subject to constraints of sources, sinks, purifiers, logic variables, etc. As shown in the case study, optimized results are more practical and economical than those recently reported the literature. Therefore the proposed strategies play an important role in guiding the management of hydrogen system in refinery.2) A novel multi-objective optimization approach is presented to balance the two conflicting objectives between operating cost and investment cost. Based on detailed analysis of off-gases of the hydrogen system, a MINLP model is formulated for the multi-objective optimization problem. This problem is transferred into the single objective optimization problem based on the weighted method with varying weight coefficients. By solving the problem, the Pareto front of the multi-objective optimization problem is obtained to balance the operating cost and investment cost leading to a suitable compromise between the two objectives. As shown in the case study, the relation of operating cost and investment cost indicates a deep insight in to the system operation,, and the optimized results based on the proposed multi-objective optimization strategy are practical and suitable for the real system.3) The uncertainty of the crude oil supply, external product demand, market condition and operation condition will result in uncertainties in the hydrogen production and consumption, off-gases production and related prices in refinery. A novel chance constrained programming approach is adopted to address the hydrogen system optimization problem under various uncertainties such as hydrogen production and consumption, off-gases production and the price of electricity, hydrogen and fuel gas. In this way, important input and state constraints will be satisfied with predefined probability levels. The problem is then transformed to an equivalent deterministic MINLP problem so that it can be solved by a MINLP solver. The effectiveness of the proposed approach comparing with the traditional deterministic methods is demonstrated by a case study.4) A novel approach for the design and optimization of flexible hydrogen systems is addressed based on the consideration of varying operation conditions and demand of hydrogen system in refinery, and a corresponding MINLP model is formulated to address the flexible optimization problem. Using a linearization method the MINLP formulation is approximated by a mixed-integer linear programming (MILP) problem, resulting in an acceptable quality and a high efficiency. An industrial hydrogen system is taken for a case study. As shown in the case study, the optimized hydrogen system based on the presented flexible optimization strategy has better flexibility, and significant savings and stable operation of hydrogen system is realized in comparison to the existing design.5) A multi-period optimization scheduling approach for hydrogen system is developed based on the consideration of the varying hydrogen demand. The impact factors of hydrogen system scheduling are elaborated, and a MINLP model is developed for the optimal scheduling of hydrogen system. The solution of the MINLP problem is obtained based on an MILP-NLP iterative algorithm, avoiding the solving of the MINLP problem directly and resulting in better quality and efficiency. A case study is presented to illustrate the effectiveness of the proposed methodology. Optimized results based on a complete iteration show that the optimized scheduling scheme is reliable and practical, the abnormal phenomena of the hydrogen imbalance, compressor start-stop, and hydrogen source change could be prevented, and the economic loss and unstable operation can also be avoided.