Optimal design and global sensitivity analysis of biomass supply chain networks for biofuels under uncertainty

Bio-fuels represent promising candidates for renewable liquid fuels. One of the challenges for the emerging industry is the high level of uncertainty in supply amounts, market demands, market prices, and processing technologies. These uncertainties complicate the assessment of investment decisions. This paper presents a model for the optimal design of biomass supply chain networks under uncertainty. The uncertainties manifest themselves as a large number of stochastic model parameters that could impact the overall profitability and design. The supply chain network we study covers the Southeastern region of the United States and includes biomass supply locations and amounts, candidate sites and capacities for two kinds of fuel conversion processing, and the logistics of transportation from the locations of forestry resources to the conversion sites and then to the final markets.To reduce the design problem to a manageable size the impact of each uncertain parameter on the objective function is computed for each end of the parameter's range. The parameters that cause the most change in the profit over their range are then combined into scenarios that are used to find a design through a two stage mixed integer stochastic program. The first stage decisions are the capital investment decisions including the size and location of the processing plants. The second stage recourse decisions are the biomass and product flows in each scenario. The objective is the maximization of the expected profit over the different scenarios. The robustness and global sensitivity analysis of the nominal design (for a single nominal scenario) vs. the robust design (for multiple scenarios) are analyzed using Monte Carlo simulation over the hypercube formed from the parameter ranges.     

Optimal processing network design under uncertainty for producing fuels and value‐added bioproducts from microalgae: Two‐stage adaptive robust mixed integer fractional programming model and computationally efficient solution algorithm

Fractional metrics, such as return on investment (ROI), are widely used for performance evaluation, but uncertainty in the real market may unfortunately diminish the results that are based on nominal parameters. This article addresses the optimal design of a large‐scale processing network for producing a variety of algae‐based fuels and value‐added bioproducts under uncertainty. We develop by far the most comprehensive processing network with 46,704 alternative processing pathways. Based on the superstructure, a two‐stage adaptive robust mixed integer fractional programming model is proposed to tackle the uncertainty and select the robust optimal processing pathway with the highest ROI. Since the proposed problem cannot be solved directly by any off‐the‐shelf solver, we develop an efficient tailored solution method that integrates a parametric algorithm with a column‐and‐constraint generation algorithm. The resulting robust optimal processing pathway selects biodiesel and poly‐3‐hydroxybutyrate as the final fuel and bioproduct, respectively. © 2016 American Institute of Chemical Engineers AIChE J, 63: 582–600, 2017     

Bioproduct adsorption in immobilized adsorbent: Local thermodynamic equilibrium model

A mathematical model using local thermodynamic equilibrium isotherms for adsorption on immobilized adsorbents is proposed in order to optimize the design parameters inin situ bioproduct separation process. The model accurately follows the experimental data on the adsorption of berberine, secondary metabolite produced in plant cell culture. The result shows that the lower loading capacity in immobilized adsorbents is due to the decrease in the maximum solid phase concentration and the isotherm equilibrium constant, not the effective diffusivity. Design parameters inin situ bioproduct separation process, such as the size of the beads, the ratio of beads to bulk volume and the adsorbent content of the bead, are evaluated by using the model. The decrease of bead size is the most effective parameter for adsorption of berberine in immobilized adsorbent due to a reduction in the overall diffusional resistance.     

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.     

Product design in price‐competitive markets: A case study of a skin moisturizing lotion

In this article, we apply a recently developed method for product design to the formulation of skin lotions and extend its application to consider price‐competitive markets. The method is based on the use of consumer preference functions that are in turn parameters of price‐demand relations. These relationships are then embedded in a business model that aims at determining the optimal lotion formulation from the profitability point of view. The model allows to distinguish the formulation that leads to the consumer most preferred skin lotion from the most profitably one in a quantitative fashion. In the latter case, the selling price is also determined simultaneously with the optimal formulation. The example analyzed shows that the consumer most preferred lotion is not profitable, whereas a slightly less preferred lotion is very profitable. We then extend the new product design procedure to consider a competitive environment in which prices of all competitors, change dynamically until equilibrium is established. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

丁辛醇市场和投资经济性系统分析

通过对国外与国内市场现状的分析,预测了世界特别是中国未来供需状况;分析了国内丁辛醇长期和短期价格数据,预测了未来价格走势;重点用定量分析方法,分析和评价了在目前情况下建设丁辛醇装置的经济性;对比分析了金属铑价格、原油价格、股价走势,测算了金属铑价格大幅波动给丁辛醇装置效益带来的影响;提出了短时间内建设多套丁辛醇装置存在一定风险,建议投资者谨慎。     

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     

Capacity Investment Planning for Multiple Vaccines Under Uncertainty: 1: Capacity Planning

In the coming years, competition in the vaccine market is likely to increase and vaccines will begin to resemble the model for conventional pharmaceutical products, requiring rapid market entry in order to gain maximum financial return and avoid the threat of competition. Therefore, companies will need to enhance their manufacturing capabilities, in terms of capacity investment and efficiency, in order to compete effectively within this market. The focus of this work is to describe a scenario-based approach to support capacity-related decision-making and the investment strategy subject to uncertainty of demands for multiple vaccines given the details of processing time, investment costs and production scale. Our model is appropriate for products in different stages of R&D and development, since they may have different expected clinical trial outcomes. These outcomes may have different probabilities of occurrence and because the information from different trials will become available at different times, this means that the investment planning model becomes a stochastic multi-period, multi-stage and multi-scenario mixed integer optimisation model. A probabilistic analysis is also used to find an approximate expression for the expected net present value (eNPV) for vaccine production with different scenarios. To complement the use of financial risk management, definitions of some classical risk measures are developed and applied in Part 2 of this paper.     

Removing of light hydrocarbons from gas mixtures using polymeric composite membranes based on poly(1-trimethylsilylpropyne)

Usually the methodologies used to analyse the feasibility of water reuse projects are focused on the internal costs. The aim of this paper is to show a methodology to assess the feasibility of a water reuse project taking into account not just the internal impact, but also the external impact (environmental and social, for example) and the opportunity cost derived from the project. Internal benefit is obtained from the difference between internal income and internal costs. Internal income is obtained by multiplying the selling price of reclaimed water and the volume obtained. Internal costs are made up of the sum of investment costs, operating costs, financial costs and taxes. While some of these factors identified can be calculated directly in terms of money, biophysical and social aspects demand the definition of units of measurement. In order to homogenize results, an annual reference is proposed. A monetary value can be obtained from the calculation of each impact. However, there are a series of externalities for which no explicit market exists. In these cases economic valuation methods are used, based on hypothetical scenarios or patterns observed in related markets.     

Texaco水煤浆气化装置配煤模型及其优化

优化配煤对Texaco水煤浆加压气化装置的优化运行具有重要的意义。针对Texaco水煤浆气化装置优化配煤问题,建立了一个管理决策级视角下的配煤优化模型。模型综合考虑了混煤指标、库存成本、市场价格、操作成本、堆存和转运消耗。采用预交叉差分进化粒子群优化算法对模型进行求解,算法将粒子群和差分进化相结合,避免算法早熟,提高了全局搜索能力和收敛精度。最后,以某化肥厂水煤浆配煤优化过程为研究实例进行仿真,计算结果验证了模型和算法的可行性。     

Investment portfolios under uncertainty for utilizing natural gas resources

Numerous reasons including lower carbon and sulfur emissions have led to the rapid growth of natural gas (NG) demand. However, more than one-third of world NG reserves are stranded, i.e., either remote (e.g., offshore) or in regions with saturated markets. This reality makes the investment decisions complex and uncertain for NG field developers. In this study, we consider the case of a company that wishes to develop a stranded natural gas reserve for some potential nearby markets under uncertain prices of crude oil and feed gas, and demands of liquefied NG (LNG), compressed NG (CNG), and gas-to-liquid (GTL) products. We present a 2-stage stochastic mixed-integer linear program (MILP) that yields maximum-ENPV (expected NPV) decisions on production capacities, market allocations, and delivery vessels. The small model size allows us to consider many stochastic scenarios in our scenario-based approach. We illustrate our approach using several examples.     

关于海外石油工程财务统一管理的实践与思考

近几年低油价的背景下,世界各主要产油国勘探开发投资逐年减少,海外石油工程市场面临生存发展的巨大挑战,为全面提升海外市场的国际竞争力,实现海外项目的规模化和效益化发展,海外石油工程企业必须构建高效的海外财务管理体系。文章围绕近几年来中国石化石油工程公司在海外推行财务统一管理方面的实践,结合中国石化集团海外战略发展目标,就下一步海外财务管理向价值管理转型做深入探讨。     

MODELING AND OPTIMIZATION FOR DESIGN UNDER PRODUCTION PLANNING CRITERIA IN MULTIPRODUCT DEHYDRATION PLANTS

ABSTRACT

The design problem of a multiproduct dehydration plant involving continuous conveyor-belt dryers utilised for the dehvdration of agricultural products over a fmite tim horizon, is presented. The peculiarities of the problem under demand-varying market patterns and time-variable market prices of raw materials are underlined. Limitations imposed by storage capacity, custormer orders, and constraints dictated by the process itself, are also taken into consideration. The overall problem is cast into a MINLP formulation involving the total annual cost of the plant as its objective function. This was infered by deducing the mathematical model of conveyor-belt dryers. Repeated evaluation of the total annual cost for various structures and operating points, allowed the determination of overall performance characteristic operational and structural curves. approximated by suitable mathematical expressions. A test case is presented in order to demonstrate the effectiveness of the proposed approach.     

MODELING AND OPTIMIZATION FOR DESIGN UNDER PRODUCTION PLANNING CRITERIA IN MULTIPRODUCT DEHYDRATION PLANTS

The design problem of a multiproduct dehydration plant involving continuous conveyor-belt dryers utilised for the dehvdration of agricultural products over a fmite tim horizon, is presented. The peculiarities of the problem under demand-varying market patterns and time-variable market prices of raw materials are underlined. Limitations imposed by storage capacity, custormer orders, and constraints dictated by the process itself, are also taken into consideration. The overall problem is cast into a MINLP formulation involving the total annual cost of the plant as its objective function. This was infered by deducing the mathematical model of conveyor-belt dryers. Repeated evaluation of the total annual cost for various structures and operating points, allowed the determination of overall performance characteristic operational and structural curves. approximated by suitable mathematical expressions. A test case is presented in order to demonstrate the effectiveness of the proposed approach.     

Optimal Simultaneous Design and Operational Planning of Vegetable Extraction Processes

A general multiperiod linear optimization model is proposed in this study that targets the simultaneous design and operation planning decisions of a multiproduct batch plant for the production of vegetable extracts. A multiperiod environment is considered because of the market and/or seasonal fluctuations. Thereby, the model considers changes from period to period of demands, costs, prices and raw materials supplies. The objective function maximizes the net present value of the profit considering incomes, investments and resources costs, and both product and raw material inventory costs. In the plant design problem, the sequence of operations is already defined and the pursued goal is to determine both unit sizes and its configuration in the plant. Besides the usual duplication in parallel option, a novel design alternative is included which allows adding units in series to perform a given operation. The optimal design is determined by taking into account available discrete sizes of units which corresponds to the real procurement of equipments. The model is formulated by using the linear generalized disjunctive programming (LGDP). A particular plant that produces oleoresins (solvent extracts of herbs and spices) is used to illustrate the proposed approach. Nevertheless, the developed model is general and can thus be applied to any vegetable extraction process.     

Commodity oil markets and how they work

Basic steps in the operation of commodity oil markets are described, from relatively simple markets (palm, coconut, and corn) through the sophisticated soybean oil market that affects prices of fats and oils worldwide. Also discussed are basic trading and economic functions provided by changing prices.     

基于(火用)经济评价的换热器最优传热温差

换热器选型是化工过程设计工作的重要部分。换热器的传热温差ΔT设计取值,左右着一次投资与能量回收效率之间的优化权衡。其结果强烈取决于因资源有限性和制造科技进步所决定的、不断增加的能源与设备的比价。本文在运用火用 经济学理论对换热过程的热火用 损失计价和换热器投资估算方法进行深入的分析、探讨和回归的基础上,发展了换热器最优传热温差的数学模型,开发了可实用于工程设计的换热器ΔT计算机辅助优化计算软件。此项研究的应用实例表明,采用优化的换热器的传热温差ΔTopt的设计,能够取得显著的节能和经济效益。     

Optimization of steel production scheduling with complex time-sensitive electricity cost

Energy-intensive industries can take advantage of process flexibility to reduce operating costs by optimal scheduling of production tasks. In this study, we develop an MILP formulation to extend a continuous-time model with energy-awareness to optimize the daily production schedules and the electricity purchase including the load commitment problem. The sources of electricity that are considered are purchase on volatile markets, time-of-use and base load contracts, as well as onsite generation. The possibility to sell electricity back to the grid is also included. The model is applied to the melt shop section of a stainless steel plant. Due to the large-scale nature of the combinatorial problem, we propose a bi-level heuristic algorithm to tackle instances of industrial size. Case studies show that the potential impact of high prices in the day-ahead markets of electricity can be mitigated by jointly optimizing the production schedule and the associated net electricity consumption cost.     

市场不确定条件下煤制烯烃技术经济分析方法

建立了一种用于市场不确定条件下现代煤化工项目技术经济分析的方法。以煤制烯烃投资项目内部收益率、投资回收期、财务净现值、税后利润和单位利润CO₂排放量为主要目标,以聚烯烃价格、煤炭价格、建设投资及碳税税率为表征市场不确定性的4个变量,建立煤制烯烃技术经济分析模型。根据该模型,绘制了预测公式曲面图和等高线图,并在此基础上开展了敏感性分析和不确定性分析。敏感性分析表明聚烯烃价格变化与煤炭价格变化对各评价指标的影响最显著;利用Monte Carlo模拟的方法量化考察了市场不确定条件下煤制烯烃技术的经济性以及各风险因素对评价指标的影响,分析结果表明,在市场低迷情况下,当聚烯烃价格处于6000~8000元/吨、煤炭价格处于100~300元/吨的低位时,煤制烯烃仍可盈利。     

Development and optimization of ME-TVC desalination system

Significant and rapid developments have taken place recently in the multi-effect thermal vapor compression (ME-TVC) desalination system of SIDEM Company, particularly in enlarging the unit capacity. The new trend of combining ME-TVC with conventional multi-effect has allowed this unit capacity to increase from two to eight million imperial gallons per day (MIGD) in the last decade. This considerable increase in capacity, poses a real competition to the multi stage flash system (MSF) as a large-scale production plant with lower operation temperatures.A steady state mathematical model of the ME-TVC desalination system is developed in this paper using Engineering Equations Solver (EES) to evaluate the model system performance. The model validity is examined against three commercial ME-TVC units which showed good results. The main improvements in the performance during the past ten years are also outlined and discussed. Another purpose of this paper is to determine the optimum operating and design conditions of the ME-TVC desalination system through mathematical modeling optimization. A MATLAB algorithm solution is developed and used to solve model equations, where a different number of effects were tested to maximize the gain ratio using (1) Smart Exhaustive Search Method and (2) Sequential Quadratic Programming. Results showed that the maximum gain ratio varied between 8.5 and 18.5 for 4 and 12 effects with the optimal top brine temperature ranging between 55.8 and 67.5 °C and a reasonable specific heat transfer area. The optimal ranges of compression and entrainment ratios are between 1.81 to 3.68 and 0.73 to 1.65 respectively. The optimal results of 4-effect TVC unit are also compared with three commercial 4-effect units having almost the same input, which showed that further improvement in the distillate output production, compression and entrainment ratio can be achieved by combining the ME-TVC system with conventional multi-effect unit.