Synthesis of sustainable integrated biorefinery via reaction pathway synthesis: Economic,incremental enviromental burden and energy assessment with multiobjective optimization

With the increasing attention toward sustainable development, biomass has been identified as one of the most promising sources of renewable energy. To convert biomass into value‐added products and energy, an integrated processing facility, known as an integrated biorefinery is needed. To date, various biomass conversion systems such as gasification, pyrolysis, anaerobic digestion and fermentation are well established. Due to a large number of technologies available, systematic synthesis of a sustainable integrated biorefinery which simultaneously considers economic performance, environmental impact, and energy requirement is a challenging task. To address this issue, multiobjective optimization approaches are used in this work to synthesize a sustainable integrated biorefinery. In addition, a novel approach (incremental environmental burden) to assess the environmental impact for an integrated biorefinery is presented. To illustrate the proposed approach, a palm‐based biomass case study is solved. © 2014 American Institute of Chemical Engineers AIChE J, 61: 132–146, 2015     

A hybrid optimisation model for the synthesis of sustainable gasification-based integrated biorefinery

Depletion of fossil fuels and increasing public awareness of environmental issues has stimulated the search for alternative energy sources. Biofuels are recognised as one of the most promising alternatives to fossil fuels, as they can be produced from various types of feedstock. The efficiency and sustainability of biomass-based production can be maximised by producing biofuels along with other valuable coproducts in a “biorefinery”. This concept was proposed to make the production of biofuels and biochemicals more economically viable by taking advantage of opportunities for process integration and waste recovery. In this work, a novel hybrid optimisation model that combines superstructure-based optimisation approach and insight-based automated targeting for the synthesis of a sustainable integrated biorefinery is presented. In addition, fuzzy optimisation is also adapted to synthesize such integrated facility with the simultaneous consideration of both economic and environmental performance. Note that the proposed approach is a generic synthesis strategy that can be applied even without detailed modelling of individual processes.     

Process synthesis and optimization of biorefinery configurations

Recently, there has been a growing interest in the development of cost‐effective technologies for the production of biofuels. A common approach to biofuel research is to invent or improve a biochemical or thermochemical conversion step. Subsequently, other conversion and separation steps are added to form a complete biorefinery flowsheet. Because this approach is structured around a specific conversion step, it may limit the possibilities of configuring optimal and innovative biorefineries. This article proposes a novel and systematic two‐stage approach to the synthesis and optimization of biorefinery configurations, given available feedstocks and desired products. In the synthesis stage, a systems‐based approach is developed to create a methodical way for synthesizing integrated biorefineries. This method is referred to as “forward‐backward” approach. It involves forward synthesis of biomass to possible intermediates and reverse synthesis starting with the desired products and identifying necessary species and pathways leading to them. In the optimization stage, Bellman's principle of optimality is applied to decompose the optimization problem into subproblems in which an optimal policy of available technologies is determined for every conversion step. An optimization formulation is utilized to determine the optimal configuration based on screening and connecting the optimal policies and generating the biorefinery flowsheet. A case study of alcohol‐producing pathways from lignocellulosic biomass is solved to demonstrate the merits of the proposed approach. © 2011 American Institute of Chemical Engineers AIChE J, 2012     

A multiobjective optimization framework for design of integrated biorefineries under uncertainty

A systematic approach for development of a reliable optimization framework to address the optimal design of integrated biorefineries in the face of uncertainty is presented. In the current formulation, a distributed strategy which is composed of different layers including strategic optimization, risk management, detailed mechanistic modeling, and operational level optimization is applied. In the strategic model, a multiobjective stochastic optimization approach is utilized to incorporate the tradeoffs between the cost and the financial risk. Then, Aspen Plus models are built to provide detailed simulation of biorefineries. In the final layer, an evolutionary algorithm is employed to optimize the operating condition. To demonstrate the effectiveness of the framework, a hypothetical case study referring to a multiproduct lignocellulosic biorefinery is utilized. The numerical results reveal the efficacy of the proposed approach; it provides decision makers with a quantitative analysis to determine the optimum capacity plan and operating conditions of the biorefinery. © 2015 American Institute of Chemical Engineers AIChE J, 61: 3208–3222, 2015     

集成模糊安全评价的反应路径综合

为在过程早期获取本质安全性较好的反应路径,将模糊安全评价集成于反应路径综合形成有效方法。根据反应路径综合阶段信息选择指标,通过设定指标的隶属度函数,建立模糊推理系统,且应用层次分析法（analytic hierarchy process,AHP）求得指标的权重因子,形成了模糊评价方法。为消除中间变量的影响,分别建立单、双输入变量的模糊推理系统。将它集成于反应路径综合,通过原料筛选规则,模糊安全评价,建立以安全为目标的优化模型,求解得到优良的反应路径组合。应用于萘甲胺反应路径综合实例,定量得到了反应路径及其目标函数值,并对两种模糊系统的综合结果进行了比较。     

Globally optimal reactor network synthesis via the combination of linear programming and stochastic optimization approach

Reactor network synthesis based on superstructure optimization is often a complex non-linear programming problem (NLP), which is very difficult to solve by means of the traditional optimization approaches. To solve this problem, a double-level new optimization method which combines linear programming and stochastic optimization approach is proposed in this paper. In addition, a superstructure network that includes continuous stirred-tank reactor (CSTR) and plug flow reactor (PFR) which is approximated as a series of CSTRs is constructed. By the proposed method and the superstructure network, the NLP is divided into a linear programming in flow rate and reactor volume space, and a stochastic optimization problem in concentration space. We solve two cases to illustrate the feasibility of the proposed method. The results show that this new optimization method can reduce the scales and difficulties of the problem and give more suitable structure of the reactor network, as well as better reactor size than those reported in the literature.     

Sustainable biopolymer synthesis via superstructure and multiobjective optimization

Sustainable polymers derived from biomass have great potential to replace petrochemical based polymers and fulfill the ever‐increasing market demand. To facilitate their industrialization, in this research, a comprehensive superstructure reaction network comprising a large number of reaction pathways from biomass to both commercialized and newly proposed polymers is constructed. To consider economic performance and environmental impact simultaneously, both process profit and green chemistry metrics are embedded into the multiobjective optimization framework, and MINLP is used to enable the effective selection of promising biopolymer candidates. Through this proposed approach, this study identifies the best biopolymer candidates and their most profitable and environmentally friendly synthesis routes under different scenarios. Moreover, the stability of optimization results regarding the price of raw materials and polymers and the effect of process scale on the investment cost are discussed in detail. These results, therefore, pave the way for future research on the production of sustainable biopolymers. © 2017 American Institute of Chemical Engineers AIChE J, 63: 91–103, 2018     

Production of benzene,toluene, and xylenes from natural gas via methanol: Process synthesis and global optimization

A systematic global optimization‐based process synthesis framework is presented to determine the most profitable processes to produce aromatics from natural gas. Several novel, commercial, and/or competing technologies are modeled within the framework, including methanol‐to‐aromatics, toluene alkylation with methanol, selective toluene disproportionation, and toluene disproportionation and transalkylation with heavy aromatics, among others. We propose a stand‐alone chemicals facility: the main products are aromatics with allowable by‐products of gasoline, liquefied petroleum gas, and electricity. Several case studies are discussed that produce varying ratios of para‐, ortho‐, and meta‐xylene across multiple refinery capacities. The results indicate that utilizing natural gas for the production of aromatics is profitable with net present values as high as $3800 MM dollars and payback periods as low as 6 years. The required investment for these refineries represents as much as a 65% decrease compared to published estimates of similar coal‐based capacity plants. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1531–1556, 2016     

合成阿托伐他汀钙关键工艺的优化

简要介绍了阿托伐他汀钙的性质和药理作用,分析了阿托伐他汀钙的全合成路线,选择以(4R-cis)-6-[2-(2-(4-氟基苯)-5-(1-异丙基)-3-苯基-4-[(苯胺)羰基-1H-吡咯-1-基)乙基]-2,2-二甲基-1,3-二氧己环-4-乙酸叔丁酯(Ⅱ)为原料经酸解、中和得到阿托伐他汀钙(Ⅰ),并对其合成工艺进行了优化。合成过程中使用2 mol/L的盐酸,控制原料和盐酸的摩尔比在1∶2.2时,反应75 min得产物,产率高达91.29%;粗品选择二氯甲烷与正己烷为溶剂进行重结晶可以得到较好的无定形阿托伐他汀钙固体;产品经结构分析确认为阿托伐他汀钙。     

Process synthesis using block superstructure with automated flowsheet generation and optimization

An alternative method for chemical process synthesis using a block‐based superstructure representation is proposed. The block‐based superstructure is a collection of blocks arranged in a two‐dimensional grid. The assignment of different equipment on blocks and the determination of their connectivity are performed using a mixed‐integer nonlinear formulation for automated flowsheet generation and optimization‐based process synthesis. Based on the special structure of the block representation, an efficient strategy is proposed to generate and successively refine feasible and optimized process flowsheets. Our approach is demonstrated using two process synthesis case studies adapted from the literature and one new process synthesis problem for methanol production from biogas © 2018 American Institute of Chemical Engineers AIChE J, 64: 3082–3100, 2018     

Sustainable design and synthesis of algae‐based biorefinery for simultaneous hydrocarbon biofuel production and carbon sequestration

The superstructure optimization of algae‐based hydrocarbon biorefinery with sequestration of CO₂ from power plant flue gas is proposed. The major processing steps include carbon capture, algae growth, dewatering, lipid extraction and power generation, and algal biorefinery. We propose a multiobjective mixed‐integer nonlinear programming (MINLP) model that simultaneously maximizes the net present value (NPV) and minimizes the global warming potential (GWP) subject to technology selection constraints, mass balance constraints, energy balance constraints, technoeconomic analysis constraints, and environmental impact constraints. The model simultaneously determines the optimal decisions that include production capacity, size of each processing unit, mass flow rates at each stage of the process, utility consumption, economic, and environmental performances. We propose a two‐stage heuristic solution algorithm to solve the nonconvex MINLP model. Finally, the bicriteria optimization problem is solved with ε‐constraint method, and the resulting Pareto‐optimal curve reveals the trade‐off between the economic and environmental criteria. The results show that for maximum NPV, the optimal process design uses direct flue gas, a tubular photobioreactor for algae growth, a filtration dewatering unit, and a hydroprocessing pathway leading to 47.1 MM gallons of green diesel production per year at $6.33/gal corresponding to GWP of 108.7 kg CO₂‐eq per gallon. © 2013 American Institute of Chemical Engineers AIChE J, 59: 1599–1621, 2013     

Supply chain management using an optimization driven simulation approach

In this work, we propose a hybrid simulation‐based optimization framework to solve the supply chain management problem. The hybrid approach combines a mathematical programming model with an agent‐based simulation model and uses them in an iterative framework. The optimization model is used to guide the decisions toward an optimal allocation of resources given the realistic supply chain representation given by the simulation. Thus, the proposed approach provides a more realistic solution compared to a stand‐alone optimization model, often a simplified representation of the actual system, by making use of the simulation model, which captures the detailed dynamic behavior of the system. A multiobjective problem has been formulated by taking into consideration the environmental impact of supply chain operations. The proposed framework has been applied to small‐scale case studies to study the effectiveness of the approach for such problems. © 2013 American Institute of Chemical Engineers AIChE J, 59: 4612–4626, 2013     

Heuristic framework for the debottlenecking of a palm oil-based integrated biorefinery

This paper presents a heuristic framework that can be used for the debottlenecking of a palm oil-based integrated biorefinery with multiple processes and products. In current industrial practice, any individual unit within these systems is generally designed for a required size. Besides, it also takes into account of an additional margin for safety to meet the requirement of the baseline state of the process. In case there is a variation in the quality of the supplied feedstock or an increase for product demand, it becomes necessary to identify the bottleneck process unit in order to handle the new variation and meet all requirements. In response, the system has to be debottlenecked by altering important operating parameters from the baseline state that limits the change. This stage entails formulating and solving a detailed model for this particular process. In this paper, frameworks are presented to aid decision makers to first identify a bottleneck and subsequently debottleneck the process. The frameworks are essentially a guide for design and safety engineers for decision making at conceptual design stage. A design stage palm oil-based integrated biorefinery case study is solved to demonstrate the proposed approach.     

Life cycle optimization for sustainable design and operations of hydrocarbon biorefinery via fast pyrolysis,hydrotreating and hydrocracking

This paper addresses the optimal design and operation of hydrocarbon biorefinery via fast pyrolysis, hydrotreating and hydrocracking of hybrid poplar feedstock under economic and environmental criteria. The hydrocarbon biorefinery encompasses fast pyrolysis for crude bio-oil production, upgrading of the bio-oil through hydrotreating, separation and hydrocracking of long chained hydrocarbons into gasoline and diesel range products, and steam reforming for hydrogen production. We propose a bi-criteria nonlinear programming (NLP) model that seeks to maximize the economic performance measured by the net present value (NPV) and to minimize the environmental impacts. The environmental objective is measured with the global warming potential (GWP) metric according to the life cycle assessment procedures, which covers gate-to-gate environmental impacts of the hydrocarbon biorefinery. The multiobjective NLP model simultaneously determines the production capacity, size of each process units, operational conditions, the flow rates of species and streams at each stage of the process, hydrocarbon biofuel yields, and consumption rate of feedstock, steam, electricity, and natural gas. The bi-criteria NLP model is solved with the ɛ-constraint method, and the resulting Pareto-optimal curve reveals the trade-off between the economic and environmental dimensions of the sustainable hydrocarbon biorefinery. The optimization results reveal that the unit production cost of the hydrocarbon biofuels is $2.31 per gallon of gasoline equivalent (GGE) for the maximum NPV solution and $3.67/GGE for the minimum GWP design. The corresponding greenhouse emission is 8.07 kgCO_2-eq/GGE.     

Role of lignin in a biorefinery: separation characterization and valorization

Lignin, a major component of the cell wall of vascular plants, has long been recognized for its negative impact and treated as a by‐product in a biorefinery. This highly abundant by‐product of the biorefinery is undervalued and underdeveloped due to its complex nature. The development of value‐added products from lignin would greatly improve the economics of the biorefinery. The inherent properties of lignin significantly affect the productivity of the biorefinery processes and its potential applications. Although the structure and biosynthetic pathway of lignin have been studied for more than a century, they have not yet been completely elucidated. In this mini‐review, the primary obstacles to elucidating the structure of native lignin, including separation and characterization, are highlighted. Several classical methods for separation and various NMR techniques, especially 2D HSQC NMR, for characterization of lignin are reviewed. Some potential applications of lignin are introduced. It is believed that a knowledge of the method to separate lignin from the cell wall and structural features of the lignin polymer from lignocellulosic materials will help to maximize the exploitation of lignocelluloses for the biorefinery as well as the utilization of lignin for novel materials and chemicals. © 2012 Society of Chemical Industry     

甲醇合成及精馏单元的能效优化

甲醇生产工艺普遍存在能耗、水耗过高的问题,对该工艺进行过程集成节能研究,具有重要的意义。以60万t/a煤制甲醇装置为背景,将处于上下游关系的甲醇合成及精馏单元作为一个系统考虑。利用夹点技术对该系统的用能现状和换热网络进行了分析,找出了违背夹点设计原则的不合理换热匹配。在此基础上,通过充分回收系统高温热源尤其是甲醇合成塔出塔合成气的能量,提出了2种现行换热网络的优化方案。方案1:节约低压蒸汽34.8%,节约脱盐水和循环冷却水21.1%,其中节约1.2 MPa低压蒸汽2 277.7 kW,节约0.3 MPa低压蒸汽20 544.4 kW;方案2:节约低压蒸汽30.8%,节约脱盐水和循环冷却水18.7%,其中节约1.2 MPa低压蒸汽6 027.0 kW,节约0.3 MPa低压蒸汽14 157.5 kW。当1.2 MPa与0.3 MPa低压蒸汽价格差距较大时,选择方案2较合理。     

A modeling framework for design of nonlinear renewable energy systems through integrated simulation modeling and metaheuristic optimization: Applications to biorefineries

This study presents the development and implementation of a novel framework for optimal design of new and emerging renewable energy production systems by considering an iterative strategy which integrates the Net Present Value optimization along with detailed mechanistic modeling, simulation, and process optimization which yields optimal capacity plan, and operating conditions for the process. Due to the non-linear nature of process conversion mechanisms, metaheuristic algorithms are implemented in the framework to optimize operating conditions of process. Further, to apply complex kinetics in the process, we have made a linkage between process simulator (Aspen Plus) and Matlab. To demonstrate the effectiveness of the proposed methodology, a hypothetical case study of a lignocellulosic biorefinery is utilized. The proposed framework results reveal a deviation in optimal process yields and production capacities from initial literature estimates. These results indicate the importance of developing a multi-layered framework to optimally design a renewable energy production system.