检索结果-内蒙古大学图书馆

A mixed-integer linear programming for Nodal Clearing Price in Day Ahead Market Considering Security Constraints

IOP Conference Series: Earth and Environmental Science 2021年第4期632卷

作者： Guanghui Sun Xiaowei Wang Libo Yang Peng Lu Bin Ma Hao Lv Long Yuan State Grid Hebei Electric Power CO. LTD Shijiazhuang 050021 Hebei China

A nodal clearing price model in day ahead market considering security constraints is established. First, the intra-region and inter-region transaction modes are explained, and the order types are shown. The clearing model takes the total social welfare as the goal, considers the security constraints of the network, and specifies the market clearing price expressed by the Lagrangian multiplier. Then the mixed linear programming algorithm is used to solve the model in this paper, and a verification method based on the N-1 criterion is performed. Finally, a numerical case is performed to calculate the clearing price of the network, which illustrates the effectiveness of the proposed method and model.

关键词： Clearing price electricity transaction order mixed-integer linear programming security constraints

来源：评论

学校读者我要写书评

暂无评论

A mixed-integer linear programming Model for a Selective Vehicle Routing Problem 5th

A Mixed-Integer Linear Programming Model for a Selective Veh...

引用

5th Workshop on Engineering Applications (WEA)

作者： Posada, Andrea Carlos Rivera, Juan Palacio, Juan D. Univ EAFIT Dept Ciencias Matemat Escuela Ciencias Medellin Colombia

ISBN: (纸本)9783030003531;9783030003524

In this paper, we propose a new vehicle routing problem variant. The new problem is a type of selective vehicle routing model in which it is not necessary to visit all nodes, but to visit enough nodes in such a way that all clusters are visited and from which it is possible to cover all nodes. Here, a mixed-integer linear programming formulation (MILP) is proposed in order to model the problem. The MILP is tested by using adapted instances from the generalized vehicle routing problem (GVRP). The model is also tested on small size GVRP instances as a special case of our proposed model. The results allow to evaluate the impact of clusters configuration in solver efficacy.

关键词： Combinatorial optimization mixed-integer linear programming Selective vehicle routing problem

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of mixed-integer linear programming and Genetic Algorithms for Solving Binary Problems 5

A Comparative Study of Mixed-Integer Linear Programming and ...

引用

5th International Conference on Industrial Engineering and Applications (ICIEA)

作者： Kuendee, Punyisa Janjarassuk, Udom King Mongkuts Inst Technol Ladkrabang Fac Engn Bangkok Thailand

ISBN: (纸本)9781538657485

This paper aims to investigate the capability of mixed-integer linear programming (MILP) method and genetic algorithm (GA) to solve binary problem (BP). A comparative study on the MILP method and GA with default and tuned setting to find out an optimal solution is presented. The mixed-integer programming library (MIPLIB 2010) is used to test and evaluate algorithms. The evaluation is shown in quality of the solution and the execution time of computation. The results show that GA is superior to MILP in execution time with inconsistent results. However, MILP is superior to GA in quality of the solution with more stable results.

关键词： mixed-integer linear programming genetic algorithm binary problem mixed integer programming library

来源：评论

学校读者我要写书评

暂无评论

Stochastic Optimization Model for Energy Management of a Hybrid Microgrid using mixed integer linear programming

引用

IFAC-PapersOnLine 2020年第2期53卷 12948-12955页

作者： G. Franke M. Schneider T. Weitzel S. Rinderknecht Technische Universität Darmstadt Institute for Mechatronic Systems in Mechanical Engineering Germany Technische Universität Darmstadt Institute of Production and Supply Chain Management Germany

In the context of increasing decentralization of the energy supply system, the concepts of microgrids are well suited to realise a reduction of CO 2 -emissions and create opportunities for new business models. For this the operation of the microgrid has a significant impact. In real systems, however, the consideration of uncertainties in generation and consumption data is essential for the operating strategy. Therefore, in this paper we propose an optimization model based on mixed-integer linear programming for the hybrid microgrid of a residential building district and include stochastic optimization in a computationally efficient way. For this, a two-stage approach is used. In a first step, we do a day-ahead optimization to determine a schedule for the combined heat and power plant and the power exchanged with the grid. In a second step, based on the results of the day-ahead optimization and the observed values for the uncertain parameters the intraday optimization is carried out. Using a numerical example, we demonstrate the advantages of this stochastic optimization over conventional optimization based on point forecasts. The data used originates from a real project district in Darmstadt, Germany.

关键词： Residential micro grid battery energy storage system optimal operating strategy mixed-integer linear programming stochastic optimization

来源：评论

学校读者我要写书评

暂无评论

Conjugate active and reactive power management in a smart distribution network through electric vehicles: A mixed integer -linear programming model

引用

SUSTAINABLE ENERGY GRIDS & NETWORKS 2020年 22卷

作者： Pirouzi, Sasan Latify, Mohammad Amin Yousefi, G. Reza Isfahan Univ Technol Dept Elect & Comp Engn Esfahan *** Iran

Electrical Vehicles (EVs) have a growing penetration rate in many countries aimed at the reduction of fossil fuel consumption and declining environmental issues. The high penetration rate of EVs, as new electrical energy demands, can cause operational problems for distribution networks. Therefore, designing and implementation of monitoring and management mechanisms for EVs charging is a necessity. EVs are equipped with power electronic-based chargers, bringing them a high degree of flexibility in conjugate active and reactive power control. This capability can be employed not only to reduce the adverse impacts of the high penetration rate of EVs on distribution networks operation but also to support the active and reactive management in distribution networks. In this paper, to employ EVs conjugate active and reactive power control capability, a model for central active and reactive power management in a smart distribution network is proposed. The proposed model is an optimization problem in which the objective function consists of two terms, namely, "minimizing the cost of energy" and "improving the voltage profile", over the operation planning horizon. The constraints of the optimization problem include distribution network operation constraints and charging and discharging constraints related to the EVs batteries and chargers. This problem is modelled as a mixed integer linear programming (MILP) problem and is implemented on the 33-bus, 69-bus, and 133-bus distribution networks. The results show that the proposed model can obtain the lowest energy cost and energy loss and the best operational voltage profile in a completely acceptable calculation time. Moreover, by using the proposed model, supplying the required energy for EVs during their plugin time interval is guaranteed and, increasing the penetration rate of EVs into the network is facilitated. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Conjugate active and reactive power management Electric vehicles mixed-integer linear programming Smart distribution network operation

来源：评论

学校读者我要写书评

暂无评论

A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks

引用

BMC BIOINFORMATICS 2017年第1期18卷 1-10页

作者： Roehl, Annika Bockmayr, Alexander Free Univ Berlin Dept Math & Comp Sci Arnimallee 6 Berlin Germany

Background: Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Results: Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Conclusions: Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

关键词： Constraint-based modeling Model reduction Stoichiometric models mixed-integer linear programming Metabolic networks

来源：评论

学校读者我要写书评

暂无评论

A new cross decomposition method for stochastic mixed-integer linear programming

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第2期256卷 487-499页

作者： Ogbe, Emmanuel Li, Xiang Queens Univ Dept Chem Engn 19 Div St Kingston ON K7L 3N6 Canada

Two-stage stochastic mixed-integer linear programming (MILP) problems can arise naturally from a variety of process design and operation problems. These problems, with a scenario based formulation, lead to large-scale MILPs that are well structured. When first-stage variables are mixed-integer and second-stage variables are continuous, these MILPs can be solved efficiently by classical decomposition methods, such as Dantzig/Wolfe decomposition (DWD), Lagrangian decomposition, and Benders decomposition (BD), or a cross decomposition strategy that combines some of the classical decomposition methods. This paper proposes a new cross decomposition method, where BD and DWD are combined in a unified framework to improve the solution of scenario based two-stage stochastic MILPs. This method alternates between DWD iterations and BD iterations, where DWD restricted master problems and BD primal problems yield a sequence of upper bounds, and BD relaxed master problems yield a sequence of lower bounds. The method terminates finitely to an optimal solution or an indication of the infeasibility of the original problem. Case study of two different supply chain systems, a bioproduct supply chain and an industrial chemical supply chain, show that the proposed cross decomposition method has significant computational advantage over BD and the monolith approach, when the number of scenarios is large. (C) 2016 Elsevier B.V. All rights reserved.

关键词： Stochastic programming mixed-integer linear programming Cross decomposition Benders decomposition Dantzig-Wolfe decomposition

来源：评论

学校读者我要写书评

暂无评论

Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate

引用

ENERGY 2017年 122卷 182-193页

作者： Esmaeily, Ali Ahmadi, Abdollah Raeisi, Fatima Ahmadi, Mohammad Reza Nezhad, Ali Esmaeel Janghorbani, Mohammadreza Islamic Azad Univ Dept Elect Engn Karaj Branch Karaj Iran Islamic Azad Univ Dept Elect Engn Marvdasht Branch Marvdasht Iran Hormozgan Univ Dept Management Bandarabbas Iran Islamic Azad Univ Young Researchers & Elite Club Shiraz Branch Shiraz Iran Islamic Azad Univ Dept Elect Engn Cent Tehran Branch Tehran Iran

A new optimization framework based on MILP model is introduced in the paper for the problem of stochastic self-scheduling of hydrothermal units known as HISS Problem implemented in a joint energy and reserve electricity market with day-ahead mechanism. The proposed MILP framework includes some practical constraints such as the cost due to valve-loading effect, the limit due to DRR and also multi-POZs, which have been less investigated in electricity market models. For the sake of more accuracy, for hydro generating units' model, multi performance curves are also used. The problem proposed in this paper is formulated using a model on the basis of a stochastic optimization technique while the objective function is maximizing the expected profit utilizing MILP technique. The suggested stochastic self scheduling model employs the price forecast error in order to take into account the uncertainty due to price. Besides, LMCS is combined with roulette wheel mechanism so that the scenarios corresponding to the non-spinning reserve price and spinning reserve price as well as the energy price at each hour of the scheduling are generated. Finally, the IEEE 118-bus power system is used to indicate the performance and the efficiency of the suggested technique. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： mixed-integer linear programming Uncertainty Modeling Electricity market Self-scheduling

来源：评论

学校读者我要写书评

暂无评论

Using a general-purpose mixed-integer linear programming solver for the practical solution of real-time train rescheduling

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第1期263卷 258-264页

作者： Fischetti, Matteo Monaci, Michele Univ Padua DEI Via Gradenigo 6-A I-35131 Padua Italy Univ Bologna DEI Viale Risorgimento 2 I-40136 Bologna Italy

At a planning level, train scheduling consists of optimizing the routing and scheduling for a set of trains on a railway network. In real-time operations, however, the planned schedule constantly needs to be verified and possibly updated due to disruptions/delays that may require train rerouting or cancelation. In practice, an almost immediate reaction is required when unexpected events occur, meaning that trains must be rescheduled in a matter of seconds. This makes the time-consuming optimization tools successfully used in the planning phase completely inadequate, and ad-hoc (heuristic,) algorithms have to be designed. In the present paper we develop a simple approach based on mixed-integer linear programming (MILP) techniques, which uses an ad-hoc heuristic preprocessing on the top of a general-purpose commercial solver applied to a standard event-based MILP formulation. A computational analysis on real cases shows that our approach can be successfully used for practical real-time train rescheduling, as it is able to deliver (almost) optimal solutions within the very tight time limits imposed by the real-time environment. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Combinatorial optimization Railways optimization Train rescheduling mixed-integer linear programming Real-time optimization

来源：评论

学校读者我要写书评

暂无评论

Analysis of mixed-integer linear programming Formulations for a Fuel-Constrained Multiple Vehicle Routing Problem

引用

UNMANNED SYSTEMS 2017年第4期5卷 197-207页

作者： Sundar, Kaarthik Venkatachalam, Saravanan Rathinam, Sivakumar Los Alamos Natl Lab Ctr Nonlinear Studies Los Alamos NM 87544 USA Wayne State Univ Dept Ind & Syst Engn Detroit MI 48202 USA Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA

This paper addresses a fuel-constrained, multiple vehicle routing problem (FCMVRP) in the presence of multiple refueling stations. We are given a set of targets, a set of refueling stations, and a depot where m vehicles are stationed. The vehicles are allowed to refuel at any refueling station, and the objective of the problem is to determine a route for each vehicle starting and terminating at the depot, such that each target is visited by at least one vehicle, the vehicles never run out of fuel while traversing their routes, and the total travel cost of all the routes is a minimum. We present four new mixed-integer linear programming (MILP) formulations for the problem. These formulations are compared both analytically and empirically, and a branch-and-cut algorithm is developed to compute an optimal solution. Extensive computational results on a large class of test instances that corroborate the effectiveness of the algorithm are also presented.

关键词： Fuel constraints green vehicle routing electric vehicles mixed-integer linear programming branch-and-cut

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：