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Multi-objective optimization of biomass to biomethane system

Green Energy & Environment 2016年第2期1卷 156-165页

作者： Nana Yan Baozeng Ren Bin Wu Di Bao Xiangping Zhang Jingheng Wang State Key Laboratory of Laboratory of Green Process and Engineering Institute of Process Engineering Chinese Academy of Sciences School of Chemical Engineering and Energy Zhengzhou University

The superstructure optimization of biomass to biomethane system through digestion is conducted in this work. The system encompasses biofeedstock collection and transportation, anaerobic digestion, biogas upgrading, and digestate recycling. We propose a multicriteria mixed integer nonlinear programming(MINLP) model that seeks to minimize the energy consumption and maximize the green degree and the biomethane production constrained by technology selection, mass balance, energy balance, and environmental impact. A multi-objective MINLP model is proposed and solved with a fast nondominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The resulting Pareto-optimal surface reveals the trade-off among the conflicting objectives. The optimal results indicate quantitatively that higher green degree and biomethane production objectives can be obtained at the expense of destroying the performance of the energy consumption objective.

关键词： Multiobjective optimization Biomass to biomethane system Green degree mixed-integer nonlinear programming

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Solving Multi-period Interdiction via Generalized Bender's Decomposition

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Acta Mathematicae Applicatae Sinica 2017年第3期33卷 633-644页

作者： Maryam SOLEIMANI-ALYAR Alireza GHAFFARI-HADIGHEH Department of Applied Mathematics Azarbaijan Shahid Madani UniversityTabrizIran

This paper considers a novel formulation of the multi-period network interdiction problem. In this model, delivery of the maximum flow as well as the act of interdiction happens over several periods, while the budget of resource for interdiction is limit. It is assumed that when an edge is interdicted in a period, the evader considers a rate of risk of detection at consequent periods. Application of the generalized Benders decomposition algorithm considers solving the resulting mixed-integer nonlinear programming problem. Computational experiences denote reasonable consistency with expectations.

关键词： Bi-level programming network interdiction mixed-integer nonlinear programming generalized benders decomposition

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Optimal design and operation of energy systems under uncertainty

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JOURNAL OF PROCESS CONTROL 2015年 30卷 1-9页

作者： Li, Xiang Barton, Paul I. Queens Univ Dept Chem Engn Kingston ON K7L 3N6 Canada MIT Proc Syst Engn Lab Cambridge MA 02139 USA

This paper is concerned with integrated design and operation of energy systems that are subject to significant uncertainties. The problem is cast as a two-stage stochastic programming problem, which can be transformed into a large-scale nonconvex mixed-integer nonlinear programming problem (MINLP). The MINLP exhibits a decomposable structure that can be exploited by nonconvex generalized Benders decomposition (NGBD) for efficient global optimization. This paper extends the NGBD method developed by the authors recently, such that the method can handle non-separable functions and integer operational decisions. Both the standard NGBD algorithm and an enhanced one with piecewise convex relaxations are discussed. The advantages of the proposed formulation and solution method are demonstrated through case studies of two industrial energy systems, a natural gas production network and a polygeneration plant. The first example shows that the two-stage stochastic programming formulation can result in better expected economic performance than the deterministic formulation, and that NGBD is more efficient than a state-of-the-art global optimization solver. The second example shows that the integration of piecewise convex relaxations can improve the efficiency of NGBD by at least an order of magnitude. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Energy systems Design and operation Uncertainty Stochastic programming Global optimization mixed-integer nonlinear programming

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A facility location model with safety stock costs: analysis of the cost of single-sourcing requirements

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JOURNAL OF GLOBAL OPTIMIZATION 2012年第3期54卷 551-581页

作者： Agrali, Semra Geunes, Joseph Taskin, Z. Caner Bahcesehir Univ Dept Ind Engn Istanbul Turkey Univ Florida Dept Ind & Syst Engn Gainesville FL 32611 USA Bogazici Univ Dept Ind Engn Istanbul Turkey

We consider a supply chain setting where multiple uncapacitated facilities serve a set of customers with a single product. The majority of literature on such problems requires assigning all of any given customer's demand to a single facility. While this single-sourcing strategy is optimal under linear (or concave) cost structures, it will often be suboptimal under the nonlinear costs that arise in the presence of safety stock costs. Our primary goal is to characterize the incremental costs that result from a single-sourcing strategy. We propose a general model that uses a cardinality constraint on the number of supply facilities that may serve a customer. The result is a complex mixed-integer nonlinear programming problem. We provide a generalized Benders decomposition algorithm for the case in which a customer's demand may be split among an arbitrary number of supply facilities. The Benders subproblem takes the form of an uncapacitated, nonlinear transportation problem, a relevant and interesting problem in its own right. We provide analysis and insight on this subproblem, which allows us to devise a hybrid algorithm based on an outer approximation of this subproblem to accelerate the generalized Benders decomposition algorithm. We also provide computational results for the general model that permit characterizing the costs that arise from a single-sourcing strategy.

关键词： mixed-integer nonlinear programming Stochastic location-inventory problem Generalized Benders decomposition Outer approximation

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Ecological Robustness-Oriented Grid Network Design for Resilience Against Multiple Hazards

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IEEE TRANSACTIONS ON POWER SYSTEMS 2024年第1期39卷 416-428页

作者： Huang, Hao Mao, Zeyu Panyam, Varuneswara Layton, Astrid Davis, Katherine R. Princeton Univ Dept Elect & Comp Engn Princeton NJ 08544 USA DRW Holdings LLC Houston TX 77056 USA Rani Therapeut San Jose CA 95131 USA Texas A&M Univ J Mike Walker Dept Mech Engn 66 College Stn TX 77843 USA Texas A&M Univ Dept Elect & Comp Engn College Stn TX 77843 USA

Power systems are critical infrastructure for reliable and secure electric energy delivery. Incidents are increasing, as unexpected multiple hazards ranging fromnatural disasters to cyberattacks threaten the security and functionality of society. Inspired by resilient ecosystems, this article presents a resilient network design approach with an ecological robustness (R-ECO)-oriented optimization to improve power systems' ability to maintain a secure operating state throughout unknown hazards. The approach uses R-ECO, a surprisal-based metric that captures key features of an ecosystem's resilient structure, as an objective to strategically design the electrical network. The approach enables solvability and practicality by introducing a stochastic-based candidate branch creation algorithm and a Taylor series expansion for relaxation of the R ECO formulation. Finally, studies are conducted on the R-ECO-oriented approach using the IEEE 24 Bus RTS and the ACTIVSg200 systems. Results demonstrate improvement of the system's reliability under multiple hazards, network properties of robust structure and equally distributed power flows, and survivability against cascading failures. From the analysis, we observe that a more redundant network structure with equally distributed power flows benefits its resilience.

关键词： Ecological robustness mixed-integer nonlinear programming power networks design power system reliability power system resilience

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Modeling of discrete/continuous optimization problems: characterization and formulation of disjunctions and their relaxations

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COMPUTERS & CHEMICAL ENGINEERING 2003年第3期27卷 433-448页

作者： Vecchietti, A Lee, S Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA UTN INGAR Inst Desarrollo & Diseno Fac Reg Santa Fe Santa Fe Argentina

This paper addresses the relaxations in alternative models for disjunctions, big-M and convex hull model, in order to develop guidelines and insights when formulating mixed-integer Non-Linear programming (MINLP), Generalized Disjunctive programming (GDP), or hybrid models. Characterization and properties are presented for various types of disjunctions. An interesting result is presented for improper disjunctions where results in the continuous space differ from the ones in the mixed-integer space. A cutting plane method is also proposed that avoids the explicit generation of equations and variables of the convex hull. Several examples are presented throughout the paper, as well as a small process synthesis problem, which is solved with the proposed cutting plane method. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： discrete-continuous optimization mixed-integer nonlinear programming generalized disjunctive programming big-M relaxation convex hull relaxation

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Fair bandwidth allocation and end-to-end delay routing algorithms for wireless mesh networks

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IEICE TRANSACTIONS ON COMMUNICATIONS 2007年第5期E90B卷 1042-1051页

作者： Wen, Yean-Fu Lin, Yeong-Sung Frank Natl Taiwan Univ Dept Informat Management Taipei Taiwan

Quality-of-service (QoS) is essential for multimedia applications, such as video-conferencing and voice over IP (VoIP) services, in wireless mesh networks (WMNs). A consequence of many clients accessing the Internet via the same backhaul is that throughput depends on the number of hops from the backhaul. This spatial bias problem is formulated as a mixed-integer nonlinear programming problem that considers end-to-end delay in terms of gateway selection, least-hop and load-balanced routing, and link capacity constraints. In this paper, we propose a routing algorithm for the network layer and a bandwidth allocation scheme for the medium access control (MAC) layer. The latter achieves fairness in both throughput and end-to-end delay in orthogonal mesh backbone networks with a distributed scheme, thereby minimizing the objective function. Our experiment results show that the proposed algorithm achieves throughput fairness, reduces end-to-end delay, and outperforms other general schemes and algorithms by at least 10.19%.

关键词： delay fairness mixed-integer nonlinear programming performance wireless networks

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Reactive Power and Voltage Control in Distribution Systems With Limited Switching Operations

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IEEE TRANSACTIONS ON POWER SYSTEMS 2009年第2期24卷 889-899页

作者： Liu, M. B. Canizares, Claudio A. Huang, W. S China Univ Technol Elect Power Coll Guangzhou Guangdong Peoples R China Univ Waterloo Dept Elect & Comp Engn Waterloo ON N2L 3G1 Canada Guangdong Power Grid Inc Foshan Power Supply Bur Foshan Guangdong Peoples R China

An algorithm based on a nonlinear interior-point method and discretization penalties is proposed in this paper for the solution of the mixed-integer nonlinear programming (MINLP) problem associated with reactive power and voltage control in distribution systems to minimize daily energy losses, with time-related constraints being considered. Some of these constraints represent limits on the number of switching operations of transformer load tap changers (LTCs) and capacitors, which are modeled as discrete control variables. The discrete variables are treated here as continuous variables during the solution process, thus transforming the MINLP problem into an NLP problem that can be more efficiently solved exploiting its highly sparse matrix structure;a strategy is developed to round these variables off to their nearest discrete values, so that daily switching operation limits are properly met. The proposed method is compared with respect to other well-known MINLP solution methods, namely, a genetic algorithm and the popular GAMS MINLP solvers BARON and DICOPT. The effectiveness of the proposed method is demonstrated in the well-known PG&E 69-bus distribution network and a real distribution system in the city of Guangzhou, China, where the proposed technique has been in operation since 2003.

关键词： Distribution systems genetic algorithms interior-point methods mixed-integer nonlinear programming nonlinear programming optimal switching operations optimization solvers reactive power control voltage control

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Alternative representations and formulations for the economic optimization of multicomponent distillation columns

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COMPUTERS & CHEMICAL ENGINEERING 2003年第3期27卷 363-383页

作者： Barttfeld, M Aguirre, PA Grossmann, IE Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA INGAR Inst Desarrollo & Diseno RA-3000 Santa Fe Argentina

This paper examines alternative models for the economic optimization of multicomponent distillation columns. Different column representations are modeled involving rigorous mixed integer nonlinear programming (MINLP) and General Disjunctive programming (GDP) formulations. The different representations involve various ways of representing the choices for the number of trays and feed tray location. Also, alternatives are considered for modeling the heat exchange when the number of trays of the column must be determinated. A preprocessing procedure developed in a previous paper [Ind. Eng. Chem. Res. (2002a)] is extended in this work to provide good initial values and bounds for the variables involved in the economic models. This initialization scheme increases the robustness and usefulness of the optimization models. Numerical results are reported on problems involving the separation of zeotropic and azeotropic mixtures. Trends about the behavior of the different proposed alternative models are discussed. (C) 2002 Elsevier Science Ltd. All rights reserved.

关键词： distillation column optimization mixed-integer nonlinear programming disjunctive programming initialization

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Simultaneous chemical process synthesis and heat integration with unclassified hot/cold process streams

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COMPUTERS & CHEMICAL ENGINEERING 2017年 101卷 210-225页

作者： Kong, Lingxun Avadiappan, Venkatachalam Huang, Kefeng Maravelias, Christos T. Univ Wisconsin Dept Chem & Biol Engn 1415 Engn Dr Madison WI 53706 USA

We propose a mixed-integer nonlinear programming (MINLP) model for the simultaneous chemical process synthesis and heat integration with unclassified process streams. The model accounts for (1) streams that cannot be classified as hot or cold, and (2) variable stream temperatures and flow rates, thereby facilitating integration with a process synthesis model. The hot/cold stream "identities" are represented by classification binary variables which are (de)activated based on the relative stream inlet and outlet temperatures. Variables including stream temperatures and heat loads are disaggregated into hot and cold variables, and each variable is (de)activated by the corresponding classification binary variable. Stream inlet/outlet temperatures are positioned onto "dynamic" temperature intervals so that heat loads at each interval can be properly calculated. The proposed model is applied to two illustrative examples with variable stream flow rates and temperatures, and is integrated with a superstructure-based process synthesis model to illustrate its applicability. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： mixed-integer nonlinear programming Superstructure optimization

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