Multi-objective optimization design of hydrogen infrastructures simultaneously considering economic cost,safety and CO2 emission

Recently increasing attention has been given to a hydrogen infrastructure (HI) including producing, transporting, and delivering H₂, the next generation alternative renewable energy source to users. This paper is concerned with designing the HI considering multiple perspectives of economic cost efficiency, safety and low CO₂ emission simultaneously. An optimization modeling approach is thus proposed to address such multiple objectives of cost efficiency of H₂ supply, safety guarantee and cost efficiency of CO₂ mitigation in the HI design. The proposed model employs fuzzy multiple objective programming to compute a compromising solution among multiple objectives. A case study of the future HI in Korea is presented to demonstrate the applicability of the proposed model with some comments. The proposed modeling work can be further utilized for developing systematic decision-making tools for policy makers to determine investment strategies for developing HIs.     

Fuzzy optimization design of multicomponent refinery hydrogen network

Hydrogen and light hydrocarbon components are essential resources of the refinery. The optimization of the refinery hydrogen system and recovery of the light hydrocarbon components contained in the gas streams are key strategies to reduce the operating costs for sustainable development. Many research efforts have been focused on the optimization of single impurity hydrogen network, and the flowrates of the hydrogen sources and sinks are assumed to be constant. However, their flowrates vary along with the quality of crude oil and refinery processing plans. A general superstructure of multicomponent refinery hydrogen network is proposed, which considers four components, namely H₂, H₂S, CH₄ and , as well as the flowrate variations of hydrogen source and hydrogen sink. The mathematical model based on the superstructure is developed with objective functions, including the minimization of total annualized cost and the maximization of overall satisfaction of the hydrogen network. Moreover, the model considers the removal of hydrogen sulfide and the recovery of light hydrocarbon components (i.e.C₂₊, ) in the optimization. To verify the applicability of the proposed mathematical model, a simplified industrial case study with four scenarios is solved. The optimization results show that the economic benefit can be maximized by considering both the direct reuse of gas streams from high-pressure separator (HP gas stream) and from low-pressure separator (LP gas stream) and the recovery of the light hydrocarbon streams. The fuzzy optimization method can be used to guide the optimal design of the refinery hydrogen system with multi-period variable flowrates.     

集成轻烃回收单元代理模型的氢气网络多目标优化

当前炼油企业氢气需求持续增长,导致炼厂成本及生产过程温室气体排放增加,炼油企业通过增设轻烃回收单元对氢气和轻烃组分进行回收利用,能有效缓解这一现状。因此,在氢气网络优化中有必要考虑轻烃回收单元。本研究提出了一种集成轻烃回收单元的氢气网络多目标数学规划模型,对轻烃回收单元采用代理模型建模方法,解决了直接嵌入严格机理模型可能导致的高计算成本问题,以总年度费用最小为优化目标,同时将系统的环境影响也纳入优化目标。实例计算表明,所提出的方法能够有效降低氢气网络的年度费用及温室气体排放,并揭示了集成轻烃回收单元的氢气网络经济性能与环境影响之间的权衡关系,为工业应用提供了一定的理论基础。     

石化园区厂际提纯回用氢气系统优化

石化园区化肥厂、乙烯厂等富氢气体送往炼油厂,能够缓解炼油厂的氢气亏缺,因而石化园区厂际氢气系统优化具有重要的意义.本文构建了石化园区厂际提纯回用氢气系统超结构模型,以年度化总费用为目标函数,建立优化的数学模型,使用商业优化软件GAMS平台建模,用DICOPT作为求解器.对某石化园区的氢气系统进行了优化,结果表明,总的年度化费用比现行的系统降低了33.1%.     

Integration strategies of hydrogen network in a refinery based on operational optimization of hydrotreating units

Inferior crude oil and fuel oil upgrading lead to escalating increase of hydrogen consumption in refineries. It is imperative to reduce the hydrogen consumption for energy-saving operations of refineries. An integration strategy of hydrogen network and an operational optimization model of hydrotreating (HDT) units are proposed based on the characteristics of reaction kinetics of HDT units. By solving the proposed model, the operating conditions of HDT units are optimized, and the parameters of hydrogen sinks are determined by coupling hydrodesulfurization (HDS), hydrodenitrification (HDN) and aromatic hydrogenation (HDA) kinetics. An example case of a refinery with annual processing capacity of eight million tons is adopted to demonstrate the feasibility of the proposed optimization strategies and the model. Results show that HDS, HDN and HDA reactions are the major source of hydrogen consumption in the refinery. The total hydrogen consumption can be reduced by 18.9% by applying conventional hydrogen network optimization model. When the hydrogen network is optimized after the operational optimization of HDT units is performed, the hydrogen consumption is reduced by 28.2%. When the benefit of the fuel gas recovery is further considered, the total annual cost of hydrogen network can be reduced by 3.21×10₇ CNY·a_-1, decreased by 11.9%. Therefore, the operational optimization of the HDT units in refineries should be imposed to determine the parameters of hydrogen sinks base on the characteristics of reaction kinetics of the hydrogenation processes before the optimization of the hydrogen network is performed through the source-sink matching methods.     

Optimization-based identification of CO2 capture and utilization processing paths for life cycle greenhouse gas reduction and economic benefits

This paper introduces a mathematical formulation to identify promising CO₂ capture and utilization (CCU) processing paths and assess their production rates by solving an optimization problem. The problem is cast as a multi-objective one by simultaneously maximizing a net profit and life cycle greenhouse gas (GHG) reduction. Three case studies are illustrated using an exemplary CCU processing network. The results indicate the optimal solution is greatly influenced by the scale of CO₂ emission source, market demand, and hydrogen availability. Moreover, with the current system of measuring the GHG reduction regarding a business-as-usual level, if the aim is to achieve a GHG reduction within a national boundary, the question of whether CCU plants producing a product of same functionality through conventional means, which the CO₂-based product can replace, exists in the country can come into consideration. This systematic identification will assist decision-making regarding future R&D investment and construction of large-scale CCU plants.     

Analyzing the energy intensity and greenhouse gas emission of Canadian oil sands crude upgrading through process modeling and simulation

This paper presents an evaluation of the energy intensity and related greenhouse gas/CO₂ emissions of integrated oil sands crude upgrading processes. Two major oil sands crude upgrading schemes currently used in Canadian oil sands operations were investigated: cokingbased and hydroconversion-based. The analysis, which was based on a robust process model of the entire process, was constructed in Aspen HYSYS and calibrated with representative data. Simulations were conducted for the two upgrading schemes in order to generate a detailed inventory of the required energy and utility inputs: process fuel, steam, hydrogen and power. It was concluded that while hydroconversion-based scheme yields considerably higher amount of synthetic crude oil (SCO) than the cokerbased scheme (94 wt-% vs. 76 wt-%), it consumes more energy and is therefore more CO₂-intensive (413.2 kg CO₂/m³ SCO vs. 216.4 kg CO₂/m³ SCO). This substantial difference results from the large amount of hydrogen consumed in the ebullated-bed hydroconverter in the hydroconversion-based scheme, as hydrogen production through conventional methane steam reforming is highly energy-intensive and therefore the major source of CO₂ emission. Further simulations indicated that optimization of hydroconverter operating variables had only a minor effect on the overall CO₂ emission due to the complex trade-off effect between energy inputs.     

Large‐scale optimization strategies for pressure swing adsorption cycle synthesis

Pressure swing adsorption (PSA) is an efficient method for gas separation and is a potential candidate for carbon dioxide (CO₂) capture from power plants. However, few PSA cycles have been designed for this purpose; the optimal design and operation of PSA cycles for CO₂ capture, as well as other systems, remains a very challenging task. In this study, we present a systematic optimization‐based formulation for the synthesis and design of novel PSA cycles for CO₂ capture in IGCC power plants, which can simultaneously produce hydrogen (H₂) and CO₂ at high purity and high recovery. Here, we apply a superstructure‐based approach to simultaneously determine optimal cycle configurations and design parameters for PSA units. This approach combines automatic differentiation, efficient ODE solvers for the state and sensitivity equations of the PSA model, and state of the art nonlinear programming solvers. Three optimization models are proposed, and two PSA case studies are considered. The first case study considers a binary separation of H₂ and CO₂ at high purity, where specific energy is minimized, whereas the second case study considers a larger five component separation. © 2012 American Institute of Chemical Engineers AIChE J, 58: 3777–3791, 2012     

Optimization of post-combustion CO2 process using DEA-MDEA mixtures

This paper presents optimal operating conditions for the post-combustion CO₂ capture process utilizing aqueous amine solutions obtained using a process simulator (HYSYS). Three alkanolamine solutions (Methyldiethanolamine MDEA, DiEthanolAmine DEA and MDEA-DEA mixture) are considered to study the performance of the capture process.The design problem addressed in this paper requires specifying the optimal operating conditions (inlet and outlet temperature of the lean solution stream on the absorber, CO₂ loading, amine composition and flow rates, among others) to achieve the given CO₂ emission targets at a minimum total annual cost. A detailed objective function including total operating costs and investment is considered.The influence of the variation of CO₂ reduction targets and the mixing proportion of amines on the total annual cost is analyzed in detail. Numerical results are presented and discussed using different case studies.The results demonstrate that process simulators can be used as a powerful tool not only to simulate but also to optimize the most important design parameters of the post-combustion CO₂ capture process.     

Techno-economic optimization of IGCC integrated with utility system for CO2 emissions reduction—Maximum power production in IGCC

Environmental legislation, with its increasing pressure on the energy sector to control greenhouse gases, is a driving force to reduce CO₂ emissions. In this paper, pre-combustion CO₂ capture through integration of a site utility system with an integrated gasification combined cycle (IGCC) is investigated as an option to provide a compressed CO₂-rich stream from a process site for sequestration. This work presents a two-step procedure for integration and optimization of a site utility system with an IGCC plant: (i) screening and optimization of IGCC plant performance parameters; (ii) integration and optimization of the utility system of the site with the IGCC plant. In the first step, an optimization approach applies the results of screening studies based on rigorous simulation of the IGCC. Having fixed the inlet fuel flow rate, the IGCC design parameters (including oxygen consumption, diluent flow rate and turbine exit pressure) are optimized for maximum power generation. Energy flows between the IGCC and CO₂ compression train are considered. In the second step, the economic and operating performance of the utility system integrated with the IGCC plant are modeled and optimized for minimum operating cost to find the most appropriate level of integration. In a case study illustrating the approach, 94% of the fuel is gasified; additional power generation offsets the operating costs of pre-combustion CO₂ capture.     

Discovery of novel zeolites for natural gas purification through combined material screening and process optimization

An efficient computational screening approach is proposed to select the most cost‐effective materials and adsorption process conditions for CH₄/CO₂ separation. The method identifies eight novel zeolites for removing CO₂ from natural gas, coalbed methane, shale gas, enhanced oil recovery gas, biogas, and landfill gas sources. The separation cost is minimized through hierarchical material screening combined with rigorous process modeling and optimization. Minimum purity and recovery constraints of 97 and 95%, respectively, are introduced to meet natural gas pipeline specifications and minimize losses. The top zeolite, WEI, can recover methane as economically as $0.15/MMBTU from natural gas with 5% CO₂ to $1.44/MMBTU from natural gas with 50% CO₂, showing the potential for developing natural gas reservoirs with higher CO₂ content. The necessity of a combined material selection and process optimization approach is demonstrated by the lack of clear correlation between cost and material‐centric metrics such as adsorption selectivity. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1767–1785, 2014     

Synthesis of multipass heat exchanger networks using genetic algorithms

In this work, a methodology based on genetic algorithms (GAs) is developed for the optimal synthesis of multipass heat exchanger networks (HENs). The network model is based on a stagewise superstructure, and the problem of finding the optimum number of 1–2 shells in series of multipass heat exchangers is aided by an efficient optimization model that uses the standard F_T design method. The proposed methodology allows for proper handling of the trade-offs involving energy consumption, number of units, number of 1–2 shells and network area to provide a network with the minimum total annual cost. The results of the examples show that the new approach is able to find more economical networks than those generated by other methods.     

Optimization of refinery hydrogen network based on chance constrained programming

Deterministic optimization approaches have been developed and used in the optimization of hydrogen network in refinery. However, uncertainties may have a large impact on the optimization of hydrogen network. Thus the consideration of uncertainties in optimization approaches is necessary for the optimization of hydrogen network. A novel chance constrained programming (CCP) approach for the optimization of hydrogen network in refinery under uncertainties is proposed. The stochastic properties of the uncertainties are explicitly considered in the problem formulation in which some input and state constraints are to be complied with predefined probability levels. The problem is then transformed to an equivalent deterministic mixed-integer nonlinear programming (MINLP) problem so that it can be solved by a MINLP solver. The solution of the optimization problem provides comprehensive information on the economic benefit under different confidence levels by satisfying process constraints. Based on this approach, an optimal and reliable decision can be made, and a suitable compensation between the profit and the probability of constraints violation can be achieved. The approach proposed in this paper makes better use of resources and can provide significant environmental and economic benefits. Finally, a case study from a refinery in China is presented to illustrate the applicability and efficiency of the developed approach.     

CO2 utilization for methanol production; Optimal pathways with minimum GHG reduction cost

Mitigating CO₂ emissions from industries and other sectors of our economy is a critical component of building a sustainable economy. This paper investigates two different methanol synthesis routes based on CO₂ utilization (CO₂ capture and utilization [CCU], and tri-reforming of methane [TRM]), and compares the results with the conventional methanol production using natural gas as the feedstock (NG-MeOH). A comprehensive techno-economic analysis (TEA) model that includes the findings of the life cycle assessment (LCA) models of methanol production using various CO₂ utilization pathways is conducted. Economic analysis is conducted by developing a cost model that is connected to the simulation models for each production route. Compared to the conventional process (with a GHG emission of 0.6 kg CO₂/kg MeOH), the lifecycle GHG reduction of 1.75 and 0.41 kg CO₂/kg MeOH are achievable in the CCU and TRM pathways, respectively. Furthermore, the results indicate that, under current market conditions and hydrogen production costs, methanol production via CO₂ hydrogenation will result in a cost approximately three times higher than that of the conventional process. The integrated TEA–LCA model shows that this increased cost of production equates to a required life cycle GHG reduction credit of $279 to $422 per tonne of CO₂ utilized, depending on construction material and selected pathway. Additionally, when compared to the CO₂ hydrogenation route, the tri-reforming process (TRM-MeOH) can result in a 42% cost savings. Furthermore, a minimum financial support of $56 per tonne utilized CO₂ will be required to make the TRM-MeOH process economically viable.     

Global optimization for sustainable design and synthesis of algae processing network for CO2 mitigation and biofuel production using life cycle optimization

Global optimization for sustainable design and synthesis of a large‐scale algae processing network under economic and environmental criteria is addressed. An algae processing network superstructure including 7800 processing routes is proposed. Based on the superstructure, a multiobjective mixed‐integer nonlinear programming (MINLP) model is developed to simultaneously optimize the unit cost and the unit global warming potential (GWP). To efficiently solve the nonconvex MINLP model with separable concave terms and mixed‐integer fractional terms in the objective functions, a global optimization strategy that integrates a branch‐and‐refine algorithm based on successive piecewise linear approximations is proposed and an exact parametric algorithm based on Newton's method. Two Pareto‐optimal curves are obtained for biofuel production and biological carbon sequestration, respectively. The unit annual biofuel production cost ranges from $7.02/gasoline gallon equivalent (GGE) to $9.71/GGE, corresponding to unit GWP's of 26.491 to 16.52 kg CO₂‐eq/GGE, respectively. © 2014 American Institute of Chemical Engineers AIChE J, 60: 3195–3210, 2014     

Targeting climate-neutral hydrogen production: Integrating brown and blue pathways with green hydrogen infrastructure via a novel superstructure and simulation-based life cycle optimization

This article addresses the sustainable design of hydrogen (H₂) production systems that integrate brown and blue pathways with green hydrogen infrastructure. We develop a systematic framework to simultaneously optimize the process superstructure and operating conditions of steam methane reforming (SMR)-based hydrogen production systems. A comprehensive superstructure that integrates SMR with multiple carbon dioxide capture technologies, electrolyzers, fuel cells, and working fluids in the organic rankine cycle is proposed under varying operating conditions. A life cycle optimization model is then developed by integrating superstructure optimization, life cycle assessment approach, techno-economic assessment, and process optimization using extensive process simulation models and formulated as a mixed-integer nonlinear program. We find that the optimal unit-levelized cost of hydrogen ranges from $1.49 to $3.18 per kg H₂. Moreover, the most environmentally friendly process attains net-zero life cycle greenhouse gas emissions compared to 10.55 kg CO₂-eq per kg H₂ for the most economically competitive process design.     

Off‐Gases Optimization in a Hydrogen Network Refinery

For optimization of a hydrogen network, a steam reformer is associated to the feedstock and linear programming (LP) is applied. The investigated network consists of one steam reformer and two feedstocks. By exerting LP and the mentioned association, total annual cost decreasing is achieved in a case study in which natural gas and off‐gas were considered as feedstocks. The optimization problems of the hydrogen network comprise the hydrogen network retrofit design and the feedstock selection with respect to their cost. Nonlinear programming (NLP) and mixed‐integer nonlinear programming (MINLP) models are developed for optimization based on a two‐case study: for the first one, an existent optimization method on hydrogen networks is investigated and for the second one, revision of a recent optimization method on hydrogen networks associated by an LP model in the steam reformer unit is applied. These two cases resulted in total annual cost reductions of 34 % and 45.9 %, respectively.     

A multi-scale framework for CO2 capture,utilization, and sequestration: CCUS and CCU

We present a multi-scale framework for the optimal design of CO₂ capture, utilization, and sequestration (CCUS) supply chain network to minimize the cost while reducing stationary CO₂ emissions in the United States. We also design a novel CO₂ capture and utilization (CCU) network for economic benefit through utilizing CO₂ for enhanced oil recovery. Both the designs of CCUS and CCU supply chain networks are multi-scale problems which require decision making at material, process and supply chain levels. We present a hierarchical and multi-scale framework to design CCUS and CCU supply chain networks with minimum investment, operating and material costs. While doing so, we take into consideration the selection of source plants, capture processes, capture materials, CO₂ pipelines, locations of utilization and sequestration sites, and amounts of CO₂ storage. Each CO₂ capture process is optimized, and the best materials are screened from large pool of candidate materials. Our optimized CCUS supply chain network can reduce 50% of the total stationary CO₂ emission in the U.S. at a cost of $35.63 per ton of CO₂ captured and managed. The optimum CCU supply chain network can capture and utilize CO₂ to make a total profit of more than 555 million dollars per year ($9.23 per ton). We have also shown that more than 3% of the total stationary CO₂ emissions in the United States can be eliminated through CCU networks at zero net cost. These results highlight both the environmental and economic benefits which can be gained through CCUS and CCU networks. We have designed the CCUS and CCU networks through (i) selecting novel materials and optimized process configurations for CO₂ capture, (ii) simultaneous selection of materials and capture technologies, (iii) CO₂ capture from diverse emission sources, and (iv) CO₂ utilization for enhanced oil recovery. While we demonstrate the CCUS and CCU networks to reduce stationary CO₂ emissions and generate profits in the United States, the proposed framework can be applied to other countries and regions as well.     

炼油厂氢气网络柔性优化

随着炼油厂对氢气的需求量不断扩大,氢气系统已成为炼油厂的重要组成部分。炼油厂氢气网络的优化设计既要实现总成本最小的经济性目标,还要保证各种工况下氢气系统的安全稳定运行。针对炼油厂氢气系统不断变化的工况和氢气需求,提出了炼油厂氢气网络柔性优化策略,建立了多工况下的氢气网络柔性优化混合整数非线性规划(MINLP)模型,并对优化模型进行了线性化处理,采用优化建模工具Lingo建模求解。采用本文提出的柔性优化策略对某炼油厂氢气网络进行了柔性优化设计,与炼油厂的原始氢气网络对比表明,柔性优化后的网络可操作性强且具有较好的柔性调节能力,既节省了大量的运行成本,又为各种工况下氢气系统的安全稳定运行提供了保障,对实际炼油厂氢气网络的优化管理起了指导作用。     

Improvements in the performance of a medium-pressure-boiler through the adjustment of inlet fuels in a refinery plant

Hydrogen has been considered as a promising alternative for fossil fuel in recent years because it is very “clean”. Fossil fuel generates CO₂, CO, SO_x, unburned hydrocarbon and particles during combustion, while hydrogen only yields NO_x. In this study, a medium-pressure boiler with 130 ton/h boiler loading in a full-scale plant was studied with two inlet hydrogen-rich refinery gas (RG)/fuel oil (FO) volumetric flow rate ratios (inlet RG/FO ratio) and two residual O₂ concentration (vol.%) in flue gases (2%, 4%) to evaluate their influence on the emissions of NO_x and CO₂, flue gas temperatures and boiler efficiencies. The result shows significant improvements in both boiler efficiencies and emissions of air pollutants. By increasing the inlet RG/FO ratio from 1:5 to 1:1.5, the fuel cost was reduced by 11%, NO_x emission down by 12%, and the CO₂ emission 20,200 ton lower per year was achieved. Thus, better economic operating conditions for the boiler are suggested at inlet RG/FO ratio = 1:1.5 with the residual O₂ concentration in flue gases = 2%.