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IEEE PES 2nd Latin American Conference on Innovative Smart Grid Technologies (ISGT Latin America)

作者： Ferreira, R. S. Borges, C. L. T. Pereira, M. V. F. PSR Rio De Janeiro RJ Brazil

ISBN: (纸本)9781467352741;9781467352727

One of the most common applications of the AC optimal power flow (ACOPF) in distribution systems is the network reconfiguration problem, which consists of altering the topology of the network in order to optimize a given objective function - usually, minimizing ohmic losses. We propose a mixed-integer linear programming reformulation of the network reconfiguration problem for distribution systems, under full modeling of the ACOPF equations. The proposed formulation captures the non-linear behavior of the electrical network via approximations of arbitrary accuracy, allows the representation of discrete decisions via integer decision variables, and can be solved to global optimality with commercially available optimization solvers. The applicability of the proposed formulation is indicated with help of case studies.

关键词： Distribution systems network reconfiguration AC optimal power flow mixed-integer linear programming

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Computing Elementary Flux Modes Involving a Set of Target Reactions

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2014年第6期11卷 1099-1107页

作者： David, Laszlo Bockmayr, Alexander Free Univ Berlin Dept Math & Comp Sci D-14195 Berlin Germany DFG Res Ctr Matheon Berlin Germany BMS Berlin Germany

Elementary flux mode (EM) computation is an important tool in the constraint-based analysis of genome-scale metabolic networks. Due to the combinatorial complexity of these networks, as well as the advances in the level of detail to which they can be reconstructed, an exhaustive enumeration of all EMs is often not practical. Therefore, in recent years interest has shifted towards searching EMs with specific properties. We present a novel method that allows computing EMs containing a given set of target reactions. This generalizes previous algorithms where the set of target reactions consists of a single reaction. In the one-reaction case, our method compares favorably to the previous approaches. In addition, we present several applications of our algorithm for computing EMs containing two target reactions in genome-scale metabolic networks. A software tool implementing the algorithms described in this paper is available at https://***/projects/caefm.

关键词： Metabolic networks constraint-based analysis elementary flux modes mixed-integer linear programming

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Reliable Capacity Planning Despite Uncertain Disassembly, Regeneration and Reassembly Workloads by Using Statistical and Mathematical Approaches – Validation in Subsidiaries of a Global MRO Company with Operations in Asia, Europe and North America

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Procedia CIRP 2014年 23卷 252-257页

作者： Steffen C. Eickemeyer Simon Steinkamp Bernhardt Schuster Frank Bodenhage Peter Nyhuis Scientific assistant in Production Management Research Group Institute of Production Systems & Logistics (IFA) Production Engineering Centre Hannover (PZH) Leibniz University Hannover An der Universität 2 30824 Garbsen Germany Temporary scientific assistant at Institute of Production Systems & Logisitcs (IFA) Production Engineering Centre Hannover (PZH) Leibniz University Hannover An der Universität 2 30824 Garbsen Germany Director of Engineering & Technical Support at MTU Maintenance Canada Ltd. 6020 Russ Baker Way Richmond BC V7B 1B4 Canada President & CEO of MTU Maintenance Zhuhai Co. Ltd. No. 1 Tianke Road Free Trade Zone Zhuhai 519030 P.R. China Head of Institute of Production Systems & Logisitcs (IFA) Leibniz University Hannover and managing director of Institut für Integrierte Produktion Hannover gGmbH An der Universität 2 30824 Garbsen Germany

The MRO industry faces substantial challenges with regard to the capacity planning of disassembly and reassembly work. This is due to the unknown workloads when regenerating complex investment goods and is caused, in particular, by the uncertain degree of disassembly and the complex challenges of reassembly. Forecasting techniques based on Bayesian networks are developed along with mathematical models which optimize capacity utilization, job order and the resulting costs. The approaches are tested and validated in conjunction with an MRO company with global operations. The results show possibilities for enhancing the planning processes and are found to be transferable on an international scale regardless of sociocultural and process differences.

关键词： Bayesian networks capacity planning complex capital goods damage library data mining disassembly forecast maintenance mixed-integer linear programming MRO reassembly regeneration

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Taxing Strategies for Carbon Emissions Based on Stackelberg Game 33

Taxing Strategies for Carbon Emissions Based on Stackelberg ...

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33rd Chinese Control Conference (CCC)

作者： Tian Fang Zhang Xing Liang Yile Wei Wei Liu Feng Mei Shengwei Elect Power Res Inst China Beijing 100192 Peoples R China Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9781479947249

This paper presents a method to determine carbon tax on different generating units based on Stackelberg game, which can strike a balance between carbon emission reduction and the profit of energy industry. The upper-level decision maker is the government agency, he aims to limit total carbon emissions within a certain level with minimal additional cost by setting optimal tax rates for different generating units. The lower-level decision maker is the grid operator, he wants to minimize the total production cost through executing an economic dispatch while considering the tax levied by the government. The Stackelberg game model is finally formulated as a mixed integer linear program and solved by CPLEX. Case studies on a 10 unit system demonstrate the validity of the proposed model and method.

关键词： Stackelberg game Power systems Carbon emission tax mixed-integer linear programming

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Stochastic Optimization Formulations for Reliability Unit Commitment Runs

Stochastic Optimization Formulations for Reliability Unit Co...

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IEEE Power and Energy Society General Meeting

作者： Kai Pan Yang Lu Yongpei Guan Jean-Paul Watson Department of Industrial and Systems Engineering University of Florida Discrete Math and Complex Systems Department Sandia National Laboratories

ISBN: (纸本)9781479964161

To address the uncertainties caused by the penetration of intermittent renewable energy, most ISOs/RTOs perform day-ahead and look-ahead reliability unit commitment (RUC) runs, ensuring sufficient generation capacity available in real time to accommodate the uncertainties. Two-stage stochastic optimization models have been studied extensively to strengthen the RUC runs, while multi-stage stochastic optimization models were barely studied. In this paper, we investigate the unit commitment and economic dispatch decision differences generated by these two approaches considering the load uncertainties in the system. The stochasticity is represented by a set of scenarios for the two-stage model and a scenario tree for the multi-stage case.

关键词： Unit commitment mixed-integer linear programming Two-stage stochastic optimization Multi-stage stochastic optimization

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Scenario analysis of the new energy policy for Taiwan's electricity sector until 2025

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ENERGY POLICY 2013年 61卷 162-171页

作者： Chen, Fung-Fei Chou, Seng-Cho Lu, Tai-Ken Taiwan Power Co Res Inst Taipei 100 Taiwan Natl Taiwan Univ Dept Informat Management Taipei 106 Taiwan Natl Taiwan Ocean Univ Dept Elect Engn Keelung 202 Taiwan

For this study, we constructed the following three case scenarios based on the Taiwanese government's energy policy: a normal scenario, the 2008 "Sustainable Energy Policy Convention" scenario, and the 2011 "New Energy Policy" scenario. We then employed a long-term Generation Expansion Planning (GEP) optimization model to compare the three case scenarios' energy mix for power generation for the next (a) over circle 15 years to further explore their possible impact on the electricity sector. The results provide a reference for forming future energy policies and developing strategic responses. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Scenario analysis Energy policy mixed-integer linear programming

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Reactive scheduling in a make-to-order flexible job shop with re-entrant process and assembly: a mathematical programming approach

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第17期51卷 5120-5141页

作者： Gomes, Marta Castilho Barbosa-Povoa, Ana Paula Novais, Augusto Queiroz Univ Tecn Lisboa Inst Super Tecn CESUR P-1049001 Lisbon Portugal Univ Tecn Lisboa Inst Super Tecn CEG IST P-1049001 Lisbon Portugal Natl Lab Energy & Geol UMOSE Unit Energy Syst Modelling & Optimizat P-1649038 Lisbon Portugal

A mixed-integer linear programming model is presented for the scheduling of flexible job shops, a production mode characteristic of make-to-order industries. Re-entrant process (multiple visits to the same machine group) and a final assembly stage are simultaneously considered in the model. The formulation uses a continuous time representation and optimises an objective function that is a weighted sum of order earliness, order tardiness and in-process inventory. An algorithm for predictive-reactive scheduling is derived from the proposed model to deal with the arrival of new orders. This is illustrated with a realistic example based on data from the mould making industry. Different reactive scheduling scenarios, ranging from unchanged schedule to full re-scheduling, are optimally generated for order insertion in a predictive schedule. Since choosing the most suitable scenario requires balancing criteria of scheduling efficiency and stability, measures of schedule changes were computed for each re-scheduling solution. The short computational times obtained are promising regarding future application of this approach in the manufacturing environment studied.

关键词： reactive scheduling flexible job shop re-entrant process assembly mixed-integer linear programming

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Economic and environmental aspects Of the component sizing for a stand-alone building energy system: A case study

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RENEWABLE ENERGY 2013年第Jul.期55卷 438-447页

作者： Fux, Samuel F. Benz, Michael J. Guzzella, Lino ETH Dept Mech & Proc Engn CH-8092 Zurich Switzerland

When designing a building energy system based on renewable energy sources, a major challenge is the suitable sizing of its components. In this paper, a simulation tool is presented for determining the optimal sizes of the main components of a stand-alone building energy system which integrates both thermal and electric renewable energy sources. Since the control of this multisource energy system is a non-trivial, multivariable control problem, particular emphasis is placed on the energy management system. A control structure based on model predictive control is proposed, whereas the underlying optimal control problem is formulated as a mixed-integer linear programming problem. The simulation tool developed is successfully applied on the specific case of an alpine lodge. A set of potential configurations, each being optimal with respect to both the net present costs and the global warming potential, is generated by analyzing the system for various component sizes. Out of this set, the decision makers can choose the most cost efficient configuration fulfilling their specifications. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Stand-alone energy system Renewable energy sources Optimal component sizing Model predictive control mixed-integer linear programming Global warming potential

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A dynamic pricing approach for returned products in integrated forward/reverse logistics network design

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APPLIED MATHEMATICAL MODELLING 2013年第24期37卷 10182-10202页

作者： Keyvanshokooh, E. Fattahi, M. Seyed-Hosseini, S. M. Tavakkoli-Moghaddam, R. Iran Univ Sci & Technol Dept Ind Engn Tehran Iran Amirkabir Univ Technol Dept Ind Engn & Management Syst Tehran Iran Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

During the last decade, the stringent pressures from environmental and social requirements have spurred an interest in designing a reverse logistics network. In this paper, we address the problem of designing and planning a multi-echelon, multi-period, multi-commodity and capacitated integrated forward/reverse logistics network. Returned products are categorized with respect to their quality levels, and a different acquisition price is offered for each return type. Furthermore, the reservation incentive of customers, the expected price of customers for one unit of used product described by uniform distribution, is applied to model the customers' return willingness. Due to the fact that the remaining worthwhile value in the used products is the corporation's key motivation for buying them from customers, a dynamic pricing approach is developed to determine the acquisition price for these products and based on it determine the percentage of returned products collected from customer zones. The used products' acquisition prices at each time period are determined based on the customers' return willingness by each collection center. A novel mixed-integer linear programming is developed to consider dynamic pricing approach for used products, forward/reverse logistics network configuration and inventory decisions, concurrently. The presented model is solved by commercial solver CPLEX for some test problems. Computational results indicate that the effect of a dynamic pricing approach for used products versus a static pricing one, and the linearization of pricing concept for this model have the acceptable solution. In addition, sensitivity analysis is conducted to show the performance of the proposed model. (C) 2013 Elsevier Inc. All rights reserved.

关键词： Supply chain management Integrated forward/reverse logistics Quality levels Dynamic pricing approach mixed-integer linear programming

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A continuous-time MILP model for short-term scheduling of make-and-pack production processes

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2013年第6期51卷 1707-1727页

作者： Baumann, Philipp Trautmann, Norbert Univ Bern Dept Business Adm CH-3012 Bern Switzerland

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. . The curse of reality why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

关键词： make-and-pack production mixed-integer linear programming symmetry-breaking constraints preprocessing real-world production process

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