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Continuous reactor network design for rigid polyol production

CHEMICAL ENGINEERING SCIENCE 2021年 230卷 116189-116189页

作者： Wen, Yunhan Biegler, Lorenz. T. Ochoa, Maria P. Matthews, Logan Ferrio, Jeff Weston, John Nikbin, Nima Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA Dow Chem Co USA Midland MI 48674 USA

In this study, we focus on developing continuous reactor network models able to produce rigid polyols under strict product and safety specifications. At the same time, we determine the optimal decision profiles that lead to minimum capital cost. Decision variables include the feed rates of initiator, monomers and catalyst, reactor temperature, residence time, number and location of monomer injection points. Moreover, we narrow down the types of continuous reactors that can be part of the network to two: plug flow reactor (PFR) with multiple feed injection points and continuous stirred tank reactor (CSTR). The PFR model is a differential algebraic equation (DAE) optimization problem. The simultaneous collocation method is applied to transform the DAE into a mixed integer nonlinear programming (MINLP) problem. An iterative algorithm is proposed to solve the MINLP, where binary variables are manually fixed. The result of this strategy shows that the reactor configuration with minimum capital cost is a PFR with ten monomer injection points. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Polymer reactors Reactor network synthesis Process optimization mixed integer nonlinear programming

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An optimization model for the design of supply chains considering disruptions from pandemic uncertainty and infection trends

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CLEANER ENGINEERING AND TECHNOLOGY 2022年 11卷

作者： Antonio, Fernando Atayde, Juan Yamzon, Martin Sy, Charlle De La Salle Univ Ind & Syst Engn Dept 2401 Taft Ave Manila 0922 Philippines

Supply chain design has been an extensively researched area of study especially given how companies all around the world seek to optimize system performance. The past years have highlighted the importance of creating lean supply chains in order to reduce costs and improve efficiency. However, the uncertainties brought by the COVID19 pandemic have challenged global supply chains with constraints on labor and capacity. Decision makers are now focusing on creating a balance between agile and lean systems because of these disruptions. A mixed integer nonlinear programming (MINLP) model for the design of supply chains under a pandemic scenario has been developed in this regard. The model considers uncertainties brought about by the imposition of government restrictions on the operations of supply chains. Specifically, the model integrates forecasts on the likely degree of restrictions that may be imposed on a given network. It then examines the interdependency between infection trends and uncertainties on customer demand, operational capacity, and facility connections. Scenarios involving different infection trend types were used to test model behavior and variable relationships. The numerical experiments yielded results showing that supply chains need to anticipate and hedge against increasing infection trends. Failure to do so could lead to incurring as much as 18% in additional total system costs. The experiments further demonstrated that additional facilities with low setup costs but higher operating costs could be selected as insurance for possible declines in operating capacity or abrupt spikes in demand.

关键词： Supply chains Pandemic Optimization Uncertainty mixed integer nonlinear programming

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Interactive nonlinear multiobjective optimal design of water distribution systems using Pareto navigator technique

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SUSTAINABLE CITIES AND SOCIETY 2021年 73卷 103110-103110页

作者： Moazeni, Faegheh Khazaei, Javad Penn State Harrisburg Sch Sci Engn & Technol Civil & Environm Engn Dept 777 W Harrisburg Pike Middletown PA 17057 USA Penn State Harrisburg Elect Engn Dept 777 W Harrisburg Pike Middletown PA 17057 USA Penn State Univ Pk Architectural Engn Dept State Coll PA 16801 USA

Sustainable water distribution systems comprise complex combinations of critical components that are simultaneously optimized. The trade-offs and interactions that exist among these components, however, will introduce difficult challenges to optimization algorithms. In this paper, a multiobjective optimization formulation is proposed to scrupulously manage the demand, leakage, and age of water, as well as energy consumption of water distribution systems. Pareto navigator approach, a learning-oriented algorithm, is used to attain the final Pareto optimal solution for water network. The optimal power consumption, leakage, demand, and water age are used as inputs to the upper level energy resource allocation to optimize the energy demand and operational cost of integrated water-energy system. Numerical results show 76.6%, 95.4%, 13.14%, and 27.4% reduction in leakage, water age, water usage, and energy consumption of water network over 24 h, respectively, while the daily cost of electricity generation reduces by 3.7%. The energy system is designed based on isolated energy units, also known as microgrids, with minimum dependency on the fossil-fuel-based power plants. As such, the proposed multiobjective bi-level optimization model will also improve the carbon footprint of water distribution systems and their impact on climate change.

关键词： Multiobjective optimization Pareto optimal solution Water-energy nexus Bi-level optimization model mixed integer nonlinear programming Sustainable systems

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Co-optimization of wastewater treatment plants interconnected with smart grids

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APPLIED ENERGY 2021年 298卷 117150-117150页

作者： Moazeni, Faegheh Khazaei, Javad Penn State Harrisburg Civil Engn Dept Sch Sci Engn & Technol 777 W Harrisburg Pike Middletown PA 17057 USA Penn State Harrisburg Elect Engn Dept 777 W Harrisburg Pike Middletown PA 17057 USA Penn State Univ Pk Architectural Engn Dept State Coll PA 16801 USA

Wastewater treatment plants (WWTPs) and smart grids of urban systems are in a strong nexus. Energy consumption of WWTPs will directly impact the economy of the smart grids, while the energy forecast, marketing, and resource allocation of smart grids will affect the economy of WWTPs. As such, these two critical infrastructures need to be operated and managed cooperatively to maximize the mutual economic benefits. In this paper, a mixed integer nonlinear programming (MINLP) co-optimization model is developed to address the day-ahead economic dispatch problem of smart grids embedded with interdependent links among wastewater treatment plants and smart grids. The energy demand of WWTPs is optimized by minimizing the energy consumption of the aeration module, mixed liquor pumping, primary clarifier's influent pumping, secondary clarifier's sludge pumping, and mixing devices that are integrated in the dynamic economic dispatch problem of smart grid. Additionally, biochemical oxygen demand (BOD) and total Kjedhal nitrogen (TKN) concentrations of the treated wastewater is also incorporated in the economic dispatch problem to ensure of the high quality of the WWTP's effluent. Electricity consumption of the buildings is also added as a constraint to the economic dispatch, serving as a dynamic load for smart grid. Case studies are conducted to examine the impact of wastewater flow rate, influent BOD and TKN concentrations, battery efficiency, and end-of-day battery's state of the charge constraints on economic dispatch of the smart grid. The results show that total operational cost and energy consumption of the integrated WWTP-smart grid is increased only by 3.4% and 1.75%, respectively, as the daily influent flow rate and BOD & TKN concentrations are increased from their minimum to maximum thresholds.

关键词： Economic dispatch formulation Demand response mixed integer nonlinear programming Critical infrastructure Energy management Resource allocation

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Optimal energy management of water-energy networks via optimal placement of pumps-as-turbines and demand response through water storage tanks

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APPLIED ENERGY 2021年 283卷 116335-116335页

A sustainable water infrastructure cannot be made possible without improving its energy efficiency in terms of the consumption value and the type of supplying resources. One solution to reduce the external energy requirement of the water systems is to decrease the energy consumption, while the internal energy recovery capacity is increased. Such is achieved by the present work through (1) optimizing the water demand and tanks' and pumps' scheduling and operations and (2) installing pumps-as-turbines (PATs) where there is excess pressure head in the water. In this paper, two optimization models are developed. The first optimization problem is designed to find the optimal number and location of the PATs among the eligible positions across a water system. The optimal solution will be incorporated in the second optimization problem, i.e., an economic dispatch problem, where the cost of energy generation of an integrated water-energy system is minimized while the water and electrical load demands, as well as the hydraulic integrity of the system are satisfied. The energy system consists of conventional power generation units aggregated of natural gas and diesel based generators, solar photovoltaic units, wind generators, and battery energy storage systems. The proposed models are verified with case studies, and the numerical results show more than 30% reduction in the daily electricity consumption of water systems and $79 in daily operating cost of energy generation in water-energy systems when 3 PATs were installed at optimal locations.

关键词： Pumps-as-turbines Water distribution network Water-energy nexus Economic dispatch formulation Demand response mixed integer nonlinear programming

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A Multi-Objective Life Cycle Optimization Model of an Integrated Algal Biorefinery toward a Sustainable Circular Bioeconomy Considering Resource Recirculation

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ENERGIES 2021年第5期14卷 1416页

作者： Solis, Celine Marie A. San Juan, Jayne Lois G. Mayol, Andres Philip Sy, Charlle L. Ubando, Aristotle T. Culaba, Alvin B. De La Salle Univ Ind Engn Dept Manila 0922 Philippines De La Salle Univ Ctr Engn & Sustainable Dev Res Manila 0922 Philippines De La Salle Univ Mech Engn Dept Manila 0922 Philippines

Biofuel production from microalgae biomass has been considered a viable alternative to harmful fossil fuels;however, challenges are faced regarding its economic sustainability. Process integration to yield various high-value bioproducts is implemented to raise profitability and sustainability. By incorporating a circular economy outlook, recirculation of resource flows is maximized to yield economic and environmental benefits through waste minimization. However, previous modeling studies have not looked into the opportunity of integrating productivity reduction related to the continuous recirculation and reuse of resources until it reaches its end of life. In this work, a novel multi-objective optimization model is developed centered on an algal biorefinery that simultaneously optimizes cost and environmental impact, adopts the principle of resource recovery and recirculation, and incorporates the life cycle assessment methodology to properly account for the environmental impacts of the system. An algal biorefinery involving end-products such as biodiesel, glycerol, biochar, and fertilizer was used for a case study to validate the optimization model. The generated optimal results are assessed and further analyzed through scenario analysis. It was seen that demand fluctuations and process unit efficiencies have significant effect on the optimal results.

关键词： algal biofuel algal biorefinery life cycle optimization mixed integer nonlinear programming

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Optimal Transmission Line Switching to Improve the Reliability of the Power System Considering AC Power Flows

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ENERGIES 2021年第11期14卷 3281页

作者： Masache, Paul Carrion, Diego Cardenas, Jorge Univ Politecn Salesiana Grp Invest Redes Elect Inteligentes GIREI EC-170702 Quito Ecuador Univ Politecn Salesiana Grp Invest Educ Inclus GEI EC-170702 Quito Ecuador

The reliability of the electrical system is a fundamental study that is carried out to determine the possible deficiencies that an electrical system can have in case of failures, since a failure can cause disturbances, power cuts, and load disconnections. For this reason, Optimal Transmission Switching (OTS) with Optimal AC Power Flows (OPF-AC) is used to reduce disturbances when faults occur and minimize equipment load and disconnections, but OTS offers possible switches in order to make it possible to reduce the damage that can be done for a fault with operating limitations in voltage, power, and angular deviation. However, to have a complete study, it is proposed to use a reliability analysis through contingency ranking to know the risks that a switched system may have at the time of simultaneous or consecutive failures. In addition, a load capacity investigation is conducted to determine if the transmission lines are within their operating limits. The study presents an analysis of the behavior of the switched system and an adequate operation for the mitigation of failures in the system through the switching of transmission lines with analysis of load capacity and reliability. The results presented by the proposed methodology will be compared with Matlab's Matpower simulation package.

关键词： contingency analysis line switching mixed integer nonlinear programming optimal power flows optimal transmission switching

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Surface Gateway Placement Optimization for Underwater Sensor Networks 28

Surface Gateway Placement Optimization for Underwater Sensor...

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28th Telecommunications Forum (TELFOR)

作者： Kahriman, Berkay Demirtas, Ali Murat Tavli, Bulent TOBB Univ Econ & Technol TR-06560 Ankara Turkey

ISBN: (纸本)9780738142432

Research on Underwater Sensor Networks (UWSNs) have been increasing drastically due to their significant potential for solving technically challenging problems. However, the challenging operating conditions such as underwater transmission delay, severe path loss, noise, and limited operating frequency render the realization of efficient UWSNs challenging. Surface Gateway (SG) deployment becomes one of the promising solutions to mitigate such challenges. In this paper, the optimal positioning of an SG to maximize the sensor coverage is investigated. The optimal location is compared with the benchmark location computed by averaging the location of underwater sensors. The coverage performances of solutions by using both of these approaches are comparatively investigated in terms of different numbers of underwater sensor nodes and transmission power levels.

关键词： Coverage Optimization Surface Gateway Deployment mixed integer nonlinear programming Underwater Sensor Network

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Incremental design of water symbiosis networks with prior knowledge: The case of an industrial park in Kenya

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SCIENCE OF THE TOTAL ENVIRONMENT 2021年 751卷 141706-141706页

作者： Ramin, Elham Bestuzheva, Ksenia Gargalo, Carina L. Ramin, Danial Schneider, Carina Ramin, Pedram Flores-Alsina, Xavier Andersen, Maj M. Gernaey, Krist V. Tech Univ Denmark Dept Chem & Biochem Engn Lyngby Denmark Konrad Zuse Ctr Comp Sci & Appl Math Berlin ZIB Berlin Germany CNR Inst Intelligent Ind Technol & Syst Adv Mfg Milan Italy Tech Univ Denmark Dept Environm Engn Lyngby Denmark Univ Copenhagen Dept Geosci & Nat Resource Management Copenhagen Denmark

Industrial parks have a high potential for recycling and reusing resources such as water across companies by creating symbiosis networks. In this study, we introduce a mathematical optimization framework for the design of water network integration in industrial parks formulated as a large-scale standard mixed-integer non-linear programming (MINLP) problem. The novelty of our approach relies on i) developing a multi-level incremental optimization framework for water network synthesis, ii) including prior knowledge of water demand growth and projected water scarcity to evaluate the significance of water-saving solutions, iii) incorporating a comprehensive formulation of the water network synthesis problem including multiple pollutants and different treatment units and iv) performing a multi-objective optimization of the network including freshwater savings and relative cost of the network. The significance of the proposed optimization framework is illustrated by applying it to an existing industrial park in a water-scarce region in Kenya. Firstly, we illustrated the benefits of including prior knowledge to prevent an over-design of the network at the early stages. In the case study, we achieved a more flexible and expandable water network with 36% lower unit cost at the early stage and 15% lower unit cost at later stages for overall maximum freshwater savings of 25%. Secondly, multi-objective analysis suggests an optimum freshwater savings of 14% to reduce the unit cost of the network by half. Moreover, the significance of symbiosis networks is highlighted by showing that intra-company connections can only achieve a maximum freshwater savings of 17% with significantly higher unit cost (+45%). Finally, we showed that the values of symbiosis connectivity index in the Pareto front correspond to higher freshwater savings, indicating the significant role of the symbiosis network in the industrial park under study. This is the first study, where all the above elements have

关键词： Wastewater treatment Water scarcity Membranes Circular economy mixed integer nonlinear programming Water network integration

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Synthetic Gene Circuit Analysis and Optimization

Synthetic Gene Circuit Analysis and Optimization

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作者： Irene Otero-Muras Julio R. Banga

Synthetic biology aims at engineering synthetic circuits with pre-defined target functions. From a systems (model-based) perspective, the following problems are of central importance: (1) given the model of a biomolecular circuit, elucidate whether it is capable of a certain behavior/functionality; and (2) starting from a pre-defined required functionality and a library of biological parts, find the biomolecular circuit that, built as a combination of such parts, achieves the desired behavior. These two problems, framed, respectively, as nonlinear analysis and automated design problems, are tackled here by efficient optimization methods. We illustrate these methods with case studies considering the analysis and design of biocircuits capable of bistability (bistable switches). Bistability is of particular interest in the context of systems and synthetic biology because it endows cells with the capacity to make decisions. less

关键词： Synthetic biology Global optimization Automated design Bistability Cell decision making mixed integer nonlinear programming Multiobjective optimization

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