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IEEE-Power-and-Energy-Society General Meeting (PESGM)

作者： Badesa, Luis Teng, Fei Strbac, Goran Imperial Coll London Dept Elect & Elect Engn London SW7 2AZ England

ISBN: (纸本)9781538677032

Low levels of inertia due to increasing renewable penetration bring several challenges, such as the higher need for Primary Frequency Response (PFR). A potential solution to mitigate this problem consists on reducing the largest possible power loss in the grid. This paper develops a novel modelling framework to analyse the benefits of such approach. A new frequency-constrained stochastic Unit Commitment (SUC) is proposed here, which allows to dynamically reduce the largest possible loss in the optimisation problem. Furthermore, the effect of load damping is included by means of an approximation, while its effect is typically neglected in previous frequency-secured-UC studies. Through several case studies, we demonstrate that reducing the largest loss could significantly decrease operational cost and carbon emissions in the future Great Britain's grid.

关键词： Frequency services stochastic linear programming unit commitment wind energy

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Bendersova dekompozice v optimalizaci

Bendersova dekompozice v optimalizaci

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作者： Minaříková, Michaela Charles University of Prague

The Bachelor thesis is dealing with Benders decomposition in optimization, especially in stochastic linear programming. In the begining the reader will be introduced to the important terms used in the decomposition algorithm. Con- sequently it is demonstrated how to reformulate the problem of stochastic linear programming to a special structure suitable for Benders decomposition. In the third chapter, the decomposition algorithm, using the feasibility and optimality cuts, is explained including conditions of convergence of the algorithm. There follows modification of algorithm for two stage stochastic linear programming. Finally, we illustrate Benders algorithm on two smaller problems. 1

关键词： Benders decomposition stochastic linear programming feasibility cut optimality cut

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Container fleet renewal considering multiple sulfur reduction technologies and uncertain markets amidst COVID-19

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JOURNAL OF CLEANER PRODUCTION 2021年 317卷 128361-128361页

作者： Zhao, Yuzhe Ye, Jiajun Zhou, Jingmiao Dalian Maritime Univ Collaborat Innovat Ctr Transport Studies Dalian Peoples R China Dalian Univ Foreign Languages Business Sch Dalian Peoples R China

The onset of 2020 is marked by stricter restrictions on maritime sulfur emissions and the spread of Coronavirus Disease 2019 (COVID-19). In this background, liner companies now face the challenge to find suitable sulfur reduction technologies, make reasonable decisions on fleet renewal, and prepare stable operation plans under the highly uncertain shipping market. Considering three sulfur reduction technologies, namely, fuel-switching, scrubber, and liquefied natural gas (LNG) dual-fuel engine, this paper develops a robust optimization model based on two-stage stochastic linear programming (SLP) to formulate a decision plan for container fleet, which can deal with various uncertainties in future: freight demand, ship charter rate, fuel price, retrofit time and Sulfur Emission Control Area (SECA) ratio. The main decision contents include ship acquisition, ship retrofit, ship sale, ship charter, route assignment, and speed optimization. The effectiveness of our plan was verified through a case study on two liner routes from the Far East to Northwest America, operated by COSCO Shipping Lines. The results from SLP model show that large-capacity fuel-switching ships and their LNG dual-fuel engine retrofits should be included in the long-term investment and operation plan;slow-steaming is an important operational decision for ocean liner shipping;if the current SECA boundary is not further expanded or the sulfur emission restrictions not further tightened, the scrubber ship will have no advantage in investment cost and operation. However, considering the probabilities of more flexible scenarios, the results from the robust model suggest that it is beneficial to install scrubber on medium-capacity fuel-switching ships, and carry out more LNG dual-fuel engine retrofits for large-capacity fuel-switching ships. Compared with SLP, this robust strategy greatly reduces sulfur emissions while slightly pushing up carbon emissions.

关键词： Maritime fleet renewal problem (MFRP) Sulfur reduction technologies stochastic linear programming Robust optimization Sulfur emission control area (SECA)

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Scenario Based Global Supply Chain Planning Process Considering Demand Uncertainty

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Journal of International Logistics and Trade 2013年第1期11卷 67-86页

作者： Hongjoo Lee Hosang Jung

In this paper, we propose a scenario based global supply chain planning (GSCP) process considering demand uncertainty originated from various global supply chain risks. To generate the global supply chain plan, we first formulate a GSCP model. Then, we need to generate several scenarios which can represent various demand uncertainties. Lastly, a planning procedure for considering those defined scenarios is applied. Unlike the past related researches, we adopt the fuzzy set theory to represent the demand scenarios. Also, a scenario voting process is added to calculate a probability (possibility) of each scenario. An illustrative example based on a real world case is presented to show the feasibility of the proposed planning process.

关键词： Global supply chain planning Demand uncertainty Scenario Fuzzy set theory stochastic linear programming

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Benders decomposition with special purpose method for the sub problem in lot sizing problem under uncertain demand

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OPERATIONS RESEARCH PERSPECTIVES 2019年 6卷

作者： Witthayapraphakorn, Aphisak Charnsethikul, Peerayuth Kasetsart Univ Ind Engn Dept 50 Ngam Wong Wan Rd Bangkok 10900 Thailand

We propose herein the application of Benders decomposition with stochastic linear programming instead of the mix integer linear programming (MILP) approach to solve a lot sizing problem under uncertain demand, particularly in the case of a large-scale problem involving a large number of simulated scenarios. In addition, a special purpose method is introduced to solve the sub problem of Benders decomposition and reduce the processing time. Our experiments show that Benders decomposition combined with the special purpose method (BCS) requires shorter processing times compared to the simple MILP approach in the case of large-scale problems. Furthermore, our BCS approach shows a linear relationship between the processing time and the number of scenarios, whereas the MILP approach shows a quadratic relationship between those variables, indicating that our approach is suitable in solving such problems.

关键词： Benders decomposition stochastic linear programming Large-scale problem Lot sizing problem Uncertain demand

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Analytical Solution of stochastic Load Flows in Network Planning

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IFAC Proceedings Volumes 1985年第7期18卷 381-384页

作者： E. López P. C. Fernández M. E. Salazar H. Department of Electrical Engineering Universidad de Concepción Casilla 53-C Concepción Chile Department of Mathematics Universidad de Concepción Casilla 2017 Concepción Chile

This paper presents a linear model for stochastic load flows (S. L. F.) studies in electric power systems when the effect of unit commitment is taken into account. It propose a method which permit to obtain the exact analytical solution of the random vector of powers generated by the production units (and thus, the load flow solution and the probability of lines overload) and some statistical indices of interest. In order to consider explicitly the production units a connection matrix is used. It allows us to consider the non-identica1 production units to be linked to the same node. The proposed model is especially well adapted for network planning studies. For this special application an algorithm is suggested.

关键词： Electric power systems models in network planning power transmission probability stochastic linear programming stochastic load flows

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OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)

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WATER RESOURCES BULLETIN 1992年第2期28卷 337-342页

作者： TRILLA, J ESTALRICH, J Univ Autonoma de Barcelona Barcelona Spain

Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a stochastic Dynamic programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons.

关键词： stochastic DYNAMIC programming stochastic linear programming AQUIFER MANAGEMENT RELIABILITY

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About One Approach to the Planning in Retail with the stochastic Parameters

About One Approach to the Planning in Retail with the Stocha...

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International Asian School-Seminar Optimization Problems of Complex Systems

作者： Artem Novikov Sobolev Inst. of Math.

ISBN: (纸本)9781728129877

Retail is one of the largest industries for financial investments in Russia. There are various mathematical descriptions for the development of retail projects. Earlier in [1] the researchers considered the resource region development model and a corresponding linear stochastic programming problem, where the budget constraints are assumed to vary in a random manner at specified interval;and the methods of its solving. In this paper, we propose new models for planning retail investment projects related to carrying out promo efficiency in the retail chain. As well as in [1], these models are based on linear stochastic programming problems, where the dimension of the problems increases essentially, and the stochastic parameters appear in market behaviour. To solve this problem, we put forward the method based on its reduction to the deterministic one. For the numerical check of the algorithms we use the data on transactions of the LLC NSK Holdi.

关键词： Modelling of the investment projects Retail stochastic linear programming Forecasting Retail stores stochastic programming stochastic models stochastic Investments development model

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OPTIMIZING THE PROBABILITIES OF WATER YIELD FOR THE RIDAURA AQUIFER (SPAIN)

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JAWRA Journal of the American Water Resources Association 1992年第2期28卷 337-342页

作者： Trilla, J. Estalrich, J. Respectively Professor and Associate Professor Unidad de Geodinamica Externa e Hidrogeologia Dpto. Geologia Universidad Autonoma de Barcelona 08193 Bellaterrra Barcelona Spain.

ABSTRACT: Aquifer pumping represents, in many geographical locations, an alternative and/or a complementary source of water to surface water supplies. Several Catalonian coastal towns in the northeastern corner of Spain are in this situation. Also, since pumped water is used to supply drinking water, the main purpose in managing these water resources is to supply, no matter the cost, the amount needed at every moment. In other words, the managers of these aquifers attempt to optimize firm water yield. If we think of these aquifers as underground reservoirs with fixed storage capacity, most of the techniques which are applied to surface reservoirs can be implemented. In this paper we use a stochastic Dynamic programming model to optimize the yield from the aquifer of the Ridaura River. The objective function in this model was chosen with the aim of maximizing the reliability of the target yields in each of four seasons. Copyright © 1992, Wiley Blackwell. All rights reserved

关键词： aquifer management reliability stochastic dynamic programming stochastic linear programming

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Modeling data integrity under stochastic linear constraints

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International Journal of Electronic Commerce Studies 2015年第2期6卷 233-242页

作者： Shing, Lee-Pin Shing, Lee-Hur Shing, Marn-Ling Shing, Chen-Chi Virginia Tech 926 Kabrich St Blacksburg 24060 VA United States Virginia Tech 1204 Highland Circle Blacksburg 24060 VA United States University of Taipei 1 Ai-Kuo West Road Taipei Taiwan Taiwan Radford University Radford University Box 6933 Radford 24142 VA United States

The most commonly used data integrity models today are Bibba, Wilson-Clark and Chinese models. These models are designed for both data integrity protection and confidentiality. Many optimization problems are related to linear programming. In practice, these variables involved are probabilistic. This paper proposes a data integrity model based on data anomalies assuming data are under stochastic linear constraints. An algorithm is constructed using the simplex method to find confidence intervals for the problem solutions. In the end the results from Monte Carlo simulation are compared with those from simplex method.

关键词： Data Integrity Model Risk Management Model stochastic linear programming

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