检索结果-内蒙古大学图书馆

Optimal planning of hybrid energy storage systems in traction power supply system with railway power conditioner

INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS 2023年第4期36卷

作者： Wang, Meng Liang, Zongyou Fu, Haochun Deng, Hao Chongqing Univ Sch Civil Engn Chongqing Peoples R China Jiang Tiao Construction Co Chongqing Railway Grp Co Ltd Chongqing Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu Peoples R China Southwest Jiaotong Univ Sch Elect Engn 999 Xian Rd Chengdu 611756 Sichuan Peoples R China

The railway power conditioner (RPC) is a promising technology to improve the regenerative braking energy (RBE) utilization and power quality of the traction power supply system (TPSS). The hybrid energy storage systems (HESS) play a key role in the economic operation of TPSS due to the high cost of the system. The capacity and power of HESS are the critical issues affecting the system performance and cost. Therefore, a hierarchical energy management model is proposed to optimize the HESS sizing and the scheduling of TPSS with RPC. At the master level, a nonlinear mathematical model is built to minimize the HESS cost, which includes capital cost, replacement cost, and recovery cost. At the slave level, considering voltage unbalance as a constraint, a mixed-integer linear programming model is established to minimize the electricity cost of railway operation. In order to solve the hierarchical nonlinear programming problem, an improved particle Swarm optimization (PSO) algorithm with a GUROBI solver embedded is proposed. Finally, the results show that the 14.08% cost reduction is achieved, and the standard limit value of voltage unbalance is satisfied.

关键词： hybrid energy storage systems mixed-integer linear programming railway power conditioner traction power supply system

来源：评论

学校读者我要写书评

暂无评论

Assessing flexibility options in electricity market clearing

引用

RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2023年 173卷

作者： Koltsaklis, Nikolaos E. Knapek, Jaroslav Czech Tech Univ Fac Elect Engn Tech 2 Prague 16627 Czech Republic

This work presents a model to co-optimize the energy and reserves markets, taking into account the penetration and participation of various flexibility providers in both markets. In particular, a detailed unit commitment model has been developed based on mixed-integer programming techniques incorporating energy storage systems with both charging and discharging options, electric vehicles with both grid-to-vehicle and vehicle-to-grid modes, and demand response programs for cost-optimal energy and ancillary services scheduling. The balancing services considered include Frequency Containment Reserves (FCR), automatic Frequency Restoration Reserves (aFRR), and manual Frequency Restoration Reserves (mFRR), in both upward and downward directions. The impact of all these flexibility providers on operational and economic aspects has been assessed through an illustrative case study of a power system with high penetration of renewable energy sources, including thermal and hydroelectric power units. The results highlight the superiority of results when considering the participation of all flexibility providers, especially in the ancillary services market, in terms of economic competitiveness, renewable energy curtailment, associated CO2 emissions, and utilization of costly energy resources. The growing share of flexibility providers in both energy management and reserve provision mix highlights the importance of these sources for power mixes with low carbon content. The methodological framework developed can be employed by system operators, market participants, and policymakers to provide price signals and optimize their resources and portfolios.

关键词： Optimization mixed-integer linear programming Unit commitment Power markets Ancillary services Flexibility Electric vehicles Energy storage Demand response

来源：评论

学校读者我要写书评

暂无评论

The pickup and delivery problem with transshipments: Critical review of two existing models and a new formulation

引用

EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2023年第1期305卷 260-270页

作者： Lyu, Zefeng Yu, Andrew Junfang Univ Tennessee Dept Ind & Syst Engn Knoxville TN 37996 USA

The pickup and delivery problem with transshipments (PDP-T) is generalized from the classical pickup and delivery problem (PDP) by allowing the transfer of requests between vehicles. After considering the time window constraints, the PDP-T is further generalized to the pickup and delivery problem with time windows and transshipments (PDPTW-T). In this paper, we review two state-of-the-art models for the PDP-T and PDPTW-T. We point out the possible issues existing in the models and provide our revisions. In addition, we develop a new mixed-integer linear programming formulation to solve the PDP-T and PDPTW-T. The performance of the proposed model is evaluated by solving 340 generated PDP-T instances and 360 open-access PDPTW-T instances. Computational results show that the proposed model outper-forms the existing models in terms of solution quality and computing time. PTP-T instances with up to 25 requests and 2 transfer stations are solved to optimality by using the proposed model. As a compar-ison, the best-known benchmarks in the literature are instances with 5 requests and 1 transfer station. In addition, the computing time is significantly reduced. In our experiments, the average computational time for solving PDP-T is reduced by 96%. For PDPTW-T instances, the solvable scale is increased from 3 requests and 4 transfer stations to 5 requests and 4 transfer stations. The average computing time is reduced by 40%.(c) 2022 Elsevier B.V. All rights reserved.

关键词： Logistics Pickup and delivery Transshipments Time windows mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Design of double pipe heat exchanger structures using linear models and smart enumeration

引用

BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING 2023年第1期40卷 231-245页

作者： Peccini, Alice Bagajewicz, Miguel J. Costa, Andre L. H. Fed Univ Rio de Janeiro UFRJ Escola Quim CT Bloco E BR-21949900 Rio De Janeiro RJ Brazil Rio de Janeiro State Univ UERJ Rua Sao Francisco Xavier 524 BR-20550900 Rio De Janeiro RJ Brazil Univ Oklahoma Sch Chem Biol & Mat Engn Norman OK 73019 USA

The design of double pipe heat exchanger hairpin-based structures has been presented in the form of a mixed-integer nonlinear model (MINLM). While some metaheuristics/stochastic methods can provide good answers, the only way to guarantee global solutions of this model is by using mixed-integer nonlinear programming (MINLP). Our novel contribution focuses on globally optimal solutions obtained robustly, that is, without convergence and initialization issues. For that purpose, as an alternative to the direct solution of the original nonlinear mathematical model, we propose the use of a rigorous linear reformulation of a MINLM to a linear model (MILM). Because the reformulation is rigorous, the global optimum of the original nonlinear model is obtained using a MILP approach. Smart enumeration procedures, applicable after parametrization of the search space are applied to overcome computational obstacles associated with solving the reformulation resultant MILP. Our approach presents various novelties: parametrization, calculation of lower bounds, and Smart Enumeration, a recently introduced technique, extendable to the solution of other problems. Numerical examples illustrate the corresponding performances.

关键词： Optimization Double pipe heat exchanger Design mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Optimization of an integrated harvest, and process planning model in the agri-food industry

JOURNAL OF ENGINEERING RESEARCH

引用

JOURNAL OF ENGINEERING RESEARCH 2025年第1期13卷 331-350页

作者： Bilgen, Bilge Taskiner, Tugce Dokuz Eylul Univ Dept Ind Engn TR-35397 Izmir Turkiye Dokuz Eylul Univ Grad Sch Nat & Appl Sci Dept Ind Engn TR-35397 Izmir Turkiye

In this paper, an integrated harvest and production planning problem in the olive oil industry is addressed. The aim of the paper is to develop and optimize a mathematical model that integrates both olive harvest and olive oil production process. The objective is to maximize the total profit while determining quantity of olives harvested from several olive groves, quantity of olives purchased from external farmers, quantity of olive oil produced, and by-product management to handle hazardous effects of olive oil production. The problem is formulated as a mixed integer linear programming model (MILP). Maximization of profit consists of two components;total sales revenue and total cost including harvesting, purchasing, fixed and variable processing costs. Constraints on the system include harvest planning, harvest capacity, production planning, and processing constraints. The proposed MILP model incorporates several distinguishing characteristics of the problem such as ripeness of olives, olive oil quality, organic and conventional farming, and by-product management. A numerical experiment based on a real-world case study was presented to verify the effectiveness of the developed model. The results show that simultaneously considering harvesting and production processes can significantly assist the profitability of the olive oil supply chain. A scenario analysis is conducted by extending the base model to explore olive loss in the olive groves which can occur due to the severe climatic conditions.

关键词： Harvest planning Production planning mixed-integer linear programming Olive oil industry Optimization

来源：评论

学校读者我要写书评

暂无评论

Identifying potential routes and airports in Brazil: An integration of the route selection and fleet assignment problems

引用

CASE STUDIES ON TRANSPORT POLICY 2025年 20卷

作者： Nagano, Marcelo Seido de Jesus, Thiago Dias Rossi, Fernando Luis Univ Sao Paulo Sao Carlos Sch Engn Ave Trabalhador Saocarlense400 BR-13566590 Sao Carlos SP Brazil Fed Inst Educ Sci & Technol Sao Paulo Barretos SP Brazil Univ Sao Paulo Inst Ciencias Matemat & Computacao Trabalhador Sao Carlense Ave400 Centre BR-13566 590 Sao Carlos SP Brazil

The strategic planning of airline networks is critical for maximizing profitability and operational efficiency. Among the key challenges faced by airlines is the Route Selection Problem (RSP)-determining which routes to operate based on demand, economic conditions, and infrastructure-and the Fleet Assignment Problem (FAP)- optimally assigning aircraft to routes to minimize costs. While these problems are typically addressed separately, their integration can yield more robust and profitable solutions. This study presents a novel mathematical model that integrates RSP and FAP using mixed integer linear programming (MILP) to optimize network profitability and fleet utilization. The model was validated through a case study of a fictional regional airline in Southeast Brazil, analyzing 41 potential locations. The results identified 28 profitable routes, including 11 destinations currently without regular flights and one without an airport. By optimizing fleet allocation and route selection, the model provides a data-driven framework for airlines, policymakers, and investors to enhance network efficiency and identify underserved markets. This study demonstrates that an integrated approach to route selection and fleet assignment can significantly improve decision-making in the airline industry, offering a scalable methodology for network expansion and strategic investment.

关键词： Route Selection Problem Fleet Assignment Problem mixed-integer linear programming Airline

来源：评论

学校读者我要写书评

暂无评论

Optimization of the speed curve for heavy-haul trains considering cyclic air braking: an MILP approach

引用

ENGINEERING OPTIMIZATION 2023年第5期55卷 876-890页

作者： Su, Shuai Huang, Yucheng Liu, Wentao Tang, Tao Cao, Yuan Liu, Hongjie Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China

The most difficult problem for the control of heavy-haul trains is the cyclic air braking on long steep downward slopes. Unsuitable positions of the application of air braking will cause large longitudinal impulses, overspeeding and even accidents. This article proposes a mixed-integer linear programming (MILP) approach to the optimization of the speed curve of heavyhaul trains. First, with the objectives of maximizing the operation distance and minimizing the air braking time within a given period, an optimization model of a heavy-haul train is formulated considering multiple practical constraints, such as the speed limit, release time and releasing speed. Second, the optimization problem is transformed into an MILP problem by linearizing the nonlinear conditions, and is solved with existing CPLEX (R) solvers. Finally, some case studies are conducted with actual data from the Shuohuang railway in China to illustrate the effectiveness of the proposed method.

关键词： Heavy-haul trains cyclic air braking long steep downward slopes mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Investigation of Electric Vehicles Contributions in an Optimized Peer-to-Peer Energy Trading System

引用

IEEE ACCESS 2023年 11卷 12489-12503页

作者： Al-Sorour, Ameena Fazeli, Meghdad Monfared, Mohammad Fahmy, Ashraf A. A. Swansea Univ Fac Sci & Engn Dept Elect & Elect Engn Swansea SA1 8EN Wales Swansea Univ ASTUTE Swansea SA1 8EN Wales Helwan Univ Dept Elect Power & Machines Helwan 11795 Egypt

The rapid increase in integration of Electric Vehicles (EVs) and Renewable Energy Sources (RESs) at the consumption level poses many challenges for network operators. Recently, Peer-to-Peer (P2P) energy trading has been considered as an effective approach for managing RESs, EVs, and providing market solutions. This paper investigates the effect of EVs and shiftable loads on P2P energy trading with enhanced Vehicle to Home (V2H) mode, and proposes an optimized Energy Management Systems aimed to reduce the net energy exchange with the grid. mixed-integer linear programming (MILP) is used to find optimal energy scheduling for smart houses in a community. Results show that the V2H mode reduces the overall energy costs of each prosumer by up to 23% compared to operating without V2H mode (i.e., EVs act as a load only). It also reduces the overall energy costs of the community by 15% compared to the houses operating without the V2H mode. Moreover, it reduces the absolute net energy exchanged between the community and the grid by 3%, which enhances the energy independence of the community.

关键词： Batteries Costs State of charge Peer-to-peer computing Vehicle-to-grid Tariffs Electric vehicles mixed integer linear programming Electric vehicle energy management system local consumption mixed-integer linear programming peer-to-peer energy trading

来源：评论

学校读者我要写书评

暂无评论

Fair Least Core: Efficient, Stable and Unique Game-Theoretic Reward Allocation in Energy Communities by Row-Generation

IEEE Transactions on Energy Markets, Policy and Regulation

引用

IEEE Transactions on Energy Markets, Policy and Regulation 2024年第2期3卷 170-181页

作者： Fioriti, Davide Bigi, Giancarlo Frangioni, Antonio Passacantando, Mauro Poli, Davide University of Pisa Department of Energy Systems Territory and Construction Engineering PI Pisa56122 Italy University of Pisa Dipartimento di Informatica PI Pisa56127 Italy University of Milano-Bicocca Department of Business and Law MI Milan20126 Italy

Energy Communities are increasingly proposed as a tool to boost renewable penetration and maximize citizen participation in energy matters. These policies enable the formation of legal entities that bring together power system members, enabling collective investment and operation of energy assets. However, designing appropriate reward schemes is crucial to fairly foster individuals to join, as well to ensure collaborative and stable aggregation, maximizing community benefits. Cooperative Game Theory, emphasizing coordination among members, has been extensively proposed for ECs and microgrids;however, it is still perceived as obscure and difficult to compute due to its exponential computational requirements. This study proposes a novel framework for stable fair benefit allocation, named Fair Least Core, that provides uniqueness, reproducibility, stability and fairness. A novel row-generation algorithm is also proposed that allows to efficiently compute the imputations for coalitions of practical size. A case study of ECs with up to 100 members shows the stability, reproducibility, fairness and efficiency properties of proposed model. The results also highlight how the market power of individual users changes as the community grows larger, which can steer the development of practical reliable, robust and fair reward allocations for energy system applications © 2023 IEEE.

关键词： mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

A proposed framework for supplier selection and order allocation using machine learning clustering and optimization techniques

引用

Journal of Data, Information and Management 2024年第3期6卷 235-254页

作者： Husna, Asma ul Ghasempoor, Ahmad Amin, Saman Hassanzadeh Department of Mechanical Industrial and Mechatronics Engineering Toronto Metropolitan University 350 Victoria Street Toronto M5B 2K3 ON Canada

The process of selecting the most suitable suppliers and allocating orders to them is critical in supply chain management. This research proposes a new framework to address the challenges of Supplier Selection and Order Allocation (SS&OA) by introducing a two-phase combined approach. In the first phase, three Machine Learning (ML) clustering techniques (i.e., K-means clustering, Gaussian Mixture Model, and Balance Iterative Reducing and Clustering using Hierarchies) are employed to identify a small group of suitable suppliers from a large pool of potential suppliers. The accuracy of the developed clustering models is assessed using Silhouette score technique. In the second phase, we focus on one of the clusters based on the results of Phase 1. In this phase, a new multi-objective model is developed for SS&OA that considers multi-source, multi-period, and multi-product scenarios. Compromise method is utilized to obtain efficient solutions. The framework is applied to extensive, real historical contract data from Canada's Public Works and Government Services Canada (PWGSC) on behalf of federal departments and agencies. The results indicate that K-means clustering model is the most accurate among the models examined for this dataset, and the choice of ML clustering techniques has a significant impact on SS&OA. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Machine learning clustering algorithms mixed-integer linear programming Multi-objective optimization Order allocation Supplier selection

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：