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作者： Vlčková, Ivona Charles University of Prague

The thesis deals with the algorithms for two-stage stochastic programs. The first chapter considers the basic properties and theory. Specifically, we introduce the properites of the feasibility region and the objective function. Further, optimality conditions are discussed. In the second chapter we present algoritms which can be used to solve two-stage linear programs with fixed recourse. In the first section the basic L-shaped method is described in detail. The second section provides an explanation of the stochastic Decomposition algorithm with the inclusion of a regularization term. The last chapter presents computational results. Three practical examples are provided both with a brief description of the problem and solutions by the studied algorithms.

关键词： two-stage stochastic programming L-shaped method stochastic Decomposition

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Day-ahead stochastic scheduling model considering market transactions in smart grids

Day-ahead stochastic scheduling model considering market tra...

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Power Systems Computation Conference

作者： Joao Soares Fernando Lezama Bruno Canizes M. Ali Fotouhi Ghazvini Zita Vale Tiago Pinto GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/I PP)

The integration of renewable generation and electric vehicles (EVs) into smart grids poses an additional challenge to the stochastic energy resource management problem due to the uncertainty related to weather forecast and EVs user-behavior. Moreover, when electricity markets are considered, market price variations cannot be disregarded. In this paper, a two-stage stochastic programming approach to schedule the day-ahead operation of energy resources in smart grids under uncertainty is presented. A realistic case study is performed using a large-scale scenario with nearly 4 million variables with the goal to minimize expected operation cost of energy aggregators. Three scenarios are analyzed to understand the effect of market transactions and external suppliers on the aggregator model. The results suggest that the market transactions can reduce expected cost, while the external supplier offers risk-free price. In addition, the performance metric shows the superiority of the stochastic approach over an equivalent deterministic model.

关键词： Energy scheduling Smart grid Uncertainty Electric vehicles two-stage stochastic programming

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Development of Shale Gas Supply Chain Network under Market Uncertainties

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ENERGIES 2017年第2期10卷 246页

作者： Chebeir, Jorge Geraili, Aryan Romagnoli, Jose Louisiana State Univ Cain Dept Chem Engn Baton Rouge LA 70803 USA

The increasing demand of energy has turned the shale gas and shale oil into one of the most promising sources of energy in the United States. In this article, a model is proposed to address the long-term planning problem of the shale gas supply chain under uncertain conditions. A two-stage stochastic programming model is proposed to describe and optimize the shale gas supply chain network. Inherent uncertainty in final products' prices, such as natural gas and natural gas liquids (NGL), is treated through the utilization of a scenario-based method. A binomial option pricing model is utilized to approximate the stochastic process through the generation of scenario trees. The aim of the proposed model is to generate an appropriate and realistic supply chain network configuration as well as scheduling of different operations throughout the planning horizon of a shale gas development project.

关键词： shale gas supply chain market uncertainty two-stage stochastic programming binomial option pricing model

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Optimal design for flexible operation of the post-combustion CO₂ capture plant with uncertain economic factors

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COMPUTERS & CHEMICAL ENGINEERING 2016年 84卷 199-207页

作者： Zaman, Muhammad Jang, Hong Rizwan, Muhammad Lee, Jay H. Korea Adv Inst Sci & Technol Dept Chem & Biomol Engn Taejon 305701 South Korea PIEAS Dept Chem Engn Islamabad Pakistan

The ultimate benefit of flexible operation of the post-combustion CO2 capture (PCC) plant depends on the ability to optimally balance between many competing factors, including the additional capital investment and operating cost savings. In this work, a large number of scenarios are constructed by considering combinations of possible realizations of the uncertain economic factors such as energy cost profile, emission penalty and value of captured CO2. Then, the design choices like the size of the storage tanks and the regeneration capacity are optimized by minimizing an overall cost averaged over all the scenarios. The optimal design problem is naturally formulated as a two-stage stochastic program. This multi-scenario optimal design is compared with the design that minimizes the overall cost for just a single nominal scenario as well as the design that minimizes the cost averaged over the worst-case scenarios. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Post combustion CO2 capture Flexible operation Optimal design Uncertainties two-stage stochastic programming

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Decomposition algorithms for two-stage chance-constrained programs

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MATHEMATICAL programming 2016年第1期157卷 219-243页

作者： Liu, Xiao Kucukyavuz, Simge Luedtke, James Ohio State Univ Dept Integrated Syst Engn Columbus OH 43210 USA Univ Wisconsin Dept Ind & Syst Engn Madison WI USA

We study a class of chance-constrained two-stage stochastic optimization problems where second-stage feasible recourse decisions incur additional cost. In addition, we propose a new model, where "recovery" decisions are made for the infeasible scenarios to obtain feasible solutions to a relaxed second-stage problem. We develop decomposition algorithms with specialized optimality and feasibility cuts to solve this class of problems. Computational results on a chance-constrained resource planing problem indicate that our algorithms are highly effective in solving these problems compared to a mixed-integer programming reformulation and a naive decomposition method.

关键词： two-stage stochastic programming Chance constraints Benders decomposition Cutting planes

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stochastic risk-averse coordinated scheduling of grid integrated energy storage units in transmission constrained wind-thermal systems within a conditional value-at-risk framework

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ENERGY 2016年第0期113卷 762-775页

作者： Hemmati, Reza Saboori, Hedayat Saboori, Saeid Kermanshah Univ Technol Dept Elect Engn POB 63766-67178 Kermanshah Iran Sahand Univ Technol Fac Elect Engn Tabriz Iran

In recent decades, wind power resources have been integrated in the power systems increasingly. Besides confirmed benefits, utilization of large share of this volatile source in power generation portfolio has been faced system operators with new challenges in terms of uncertainty management. It is proved that energy storage systems are capable to handle projected uncertainty concerns. Risk-neutral methods have been proposed in the previous literature to schedule storage units considering wind resources uncertainty. Ignoring risk of the cost distributions with non-desirable properties may result in experiencing high costs in some unfavorable scenarios with high probability. In order to control the risk of the operator decisions, this paper proposes a new risk-constrained two-stage stochastic programming model to make optimal decisions on energy storage and thermal units in a transmission constrained hybrid wind-thermal power system. Risk-aversion procedure is explicitly formulated using the conditional value-at-risk measure, because of possessing distinguished features compared to the other risk measures. The proposed model is a mixed integer linear programming considering transmission network, thermal unit dynamics, and storage devices constraints. The simulations results demonstrate that taking the risk of the problem into account will affect scheduling decisions considerably depend on the level of the risk-aversion. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Risk-averse programming Conditional value-at-risk two-stage stochastic programming Unit commitment Wind uncertainty management Energy storage system

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Short-circuit level control through a multi-objective feeder reconfiguration using fault current limiters in the presence of distributed generations

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IET GENERATION TRANSMISSION & DISTRIBUTION 2016年第14期10卷 3458-3469页

作者： Esmaeili, Abbas Esmaeili, Saeid Hojabri, Hossein Shahid Bahonar Univ Kerman Dept Elect Engn Kerman Iran

Despite the advantages of distributed generations (DGs) in electrical networks, they make some unwanted changes in network short-circuit levels which make new security risks arise. This imposes several new scenarios on the network operation in the presence of DGs. In addition to the mentioned security concerns, reducing network loss is among the objectives constantly sought by system operators. Therefore, this study discusses both the reconfiguration of a distribution network for efficient operation and protection coordination in the form of a multi-objective optimisation problem. The aforementioned objectives include reducing losses and maintaining short-circuit levels under several utilisation scenarios of DGs. Thus, the optimal reconfiguration of the network is simultaneously considered along with the optimal planning of fault current limiters through a two-stage stochastic programming. A fuzzy system is utilised to solve the multi-objective problem and a fuzzy imperialism competitive algorithm is proposed to reach the global optimum. The proposed model is implemented on IEEE 69-bus and a real life 77-bus system. Simulation results confirm that implementing the proposed technique not only reduces power losses, but also maintains a short-circuit level of the network under probable utilisation scenarios which in turn the protection coordination of system is improved.

关键词： fault current limiters short-circuit currents distributed power generation power generation control power system security power generation planning stochastic programming fuzzy systems short-circuit level control multiobjective feeder reconfiguration fault current limiter optimal planning distributed generations electrical networks DGs network short-circuit levels security risks network loss reduction protection coordination multiobjective optimisation problem two-stage stochastic programming fuzzy system fuzzy imperialism competitive algorithm multiobjective problem global optimum IEEE-bus system power losses reduction distribution network

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Modeling Demand Uncertainty in two-Tier City Logistics Tactical Planning

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TRANSPORTATION SCIENCE 2016年第2期50卷 559-578页

作者： Crainic, Teodor Gabriel Errico, Fausto Rei, Walter Ricciardi, Nicoletta Univ Quebec Dept Management & Technol Ecole Sci Gest Montreal PQ H3C 3P8 Canada Univ Montreal Ctr Interuniv Rech Reseaux Entreprise Logist & Tr Montreal PQ H3C 3J7 Canada Ecole Technol Super Dept Genie Construct Montreal PQ H3C 1K3 Canada Univ Roma La Sapienza Dept Sci Stat I-00185 Rome Italy

We consider the complex and not-yet-studied issue of building the tactical plan of a two-tiered city logistics system while explicitly accounting for the uncertainty in the forecast demand. We describe and formally define the problem and then propose a general modeling framework, which takes the form of a two-stage stochastic programming formulation, the first stage selecting the first-tier service network design and the general workloads of the intertier transfer facilities, and the second stage determines the actual vehicle routing on the second tier as well as some limited adjustments of the first-stage service design decisions. Four different strategies of adapting the plan to the observed demand are introduced together with the associated recourse formulations. These strategies are then experimentally compared through an evaluation procedure that, based on Monte Carlo principles, mimics the decision process of a priori planning followed by repetitively applying the adjusted plan to the periods of the planning horizon. The performances of the city logistics system under the adjustment strategies are contrasted through performance measures relative to the costs of operating the system, including those of additional vehicle capacity and movements required when the plan does not provide sufficient transportation means, the utilization of the various types of vehicles, the intensity of the vehicle presence within the city, and the utilization of the intertier transfer facilities. The comparisons are discussed both based on the numerical figures obtained through simulation and from the point of view of managerial insights into the implication for managing city logistics physical and human resources. The analysis emphasizes the interest of flexibility in managing resources and operations for the overall performance of the system, discusses the associated trade-offs, and underlines the benefits of consolidation in terms of system efficiency and impact on the city. The

关键词： city logistics advanced urban freight transportation demand uncertainty tactical planning two-stage stochastic programming Monte Carlo simulation

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Hybrid manufacturing and remanufacturing lot-sizing problem with stochastic demand, return, and setup costs

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2016年第5-8期82卷 1241-1257页

作者： Macedo, Pedro Belluco Alem, Douglas Santos, Maristela Lage Junior, Muris Moreno, Alfredo Oracle Brasil Sistemas Ltda Rua Doutor Jose Aureo Bustamante 455 Sao Paulo Brazil Univ Fed Sao Carlos Dept Prod Engn Rodovia Joao Leme dos SantosKm 110SP-264 BR-18052780 Sao Paulo Brazil Univ Sao Carlos Inst Ciencias Matemat & Comp Av Trabalhador Sao Carlense 400 BR-13560970 Sao Carlos SP Brazil Univ Fed Sao Carlos Dept Prod Engn Rodovia Washington LuisKm 235SP-310 BR-13565905 Sao Carlos SP Brazil

This paper presents mixed-integer programming models to hybrid manufacturing and remanufacturing lot-sizing problems in which remanufactured products are treated as new ones, so that both manufactured and remanufactured products compete to meet the demands. Differently from previous studies, we consider an environment with multiple products, both manufacturing and remanufacturing costs, disposal, backlogging, and the inherent uncertainties of demands, return rates of usable products, and setup costs. In order to deal with these uncertainties, we propose a scenario-based two-stage stochastic programming model that assumes production and setup as first-stage decision variables, whereas inventory, disposal, and backlogging are defined as second-stage decision variables. We also analyze a risk-averse model in an attempt to reduce the dispersion of the second-stage costs. The main results of the present study indicate that setup costs for remanufacturing can be decisive in choosing between manufacturing or remanufacturing. Even though remanufacturing costs are lower, the process is still largely dependent on return rates and low storage costs for returned products.

关键词： Lot sizing Remanufacturing two-stage stochastic programming Risk aversion Mean risk

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stochastic network models for logistics planning in disaster relief

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2016年第1期255卷 187-206页

作者： Alem, Douglas Clark, Alistair Moreno, Alfredo Univ Fed Sao Carlos Dept Prod Engn Sorocaba Brazil Univ West England Dept Engn Design & Math Bristol BS16 1QY Avon England

Emergency logistics in disasters is fraught with planning and operational challenges, such as uncertainty about the exact nature and magnitude of the disaster, a lack of reliable information about the location and needs of victims, possible random supplies and donations, precarious transport links, scarcity of resources, and so on. This paper develops a new two-stage stochastic network flow model to help decide how to rapidly supply humanitarian aid to victims of a disaster within this context The model takes into account practical characteristics that have been neglected by the literature so far, such as budget allocation, fleet sizing of multiple types of vehicles, procurement, and varying lead times over a dynamic multiperiod horizon. Attempting to improve demand fulfillment policy, we present some extensions of the model via state-of-art risk measures, such as semideviation and conditional value-at-risk. A simple two-phase heuristic to solve the problem within a reasonable amount of computing time is also suggested. Numerical tests based on the floods and landslides in Rio de Janeiro state, Brazil, show that the model can help plan and organise relief to provide good service levels in most scenarios, and how this depends on the type of disaster and resources. Moreover, we demonstrate that our heuristic performs well for real and random instances. (C) 2016 Elsevier B.V. All rights reserved.

关键词： OR in disaster relief Humanitarian logistics Emergency logistics planning two-stage stochastic programming Risk-aversion

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