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Designing an optimized fueling infrastructure for a hydrogen railway system

Journal of Rail Transport Planning & Management 2025年 35卷

作者： Alessio Trivella Amina Balha Daniela Guericke Industrial Engineering and Business Information Systems University of Twente Hallenweg 17 7522 NH Enschede Netherlands

Hydrogen use is increasing in transportation, including within the railway sector. In collaboration with a governmental institution in the Netherlands, we study how to design an efficient hydrogen fueling infrastructure for a railway system. The problem involves selecting yards in a network for hydrogen fueling, assigning trains to these yards, locating hydrogen storage and fueling stations, and connecting them via pipelines. This key planning phase must avoid oversizing costly fueling infrastructure while accounting for track availability at yards and costs due to fueling operations. We formulate this novel problem, which has the structure of a nested facility location problem, as a mixed-integer linear program to minimize total annualized investment and operational costs. Due to the complexity of real-sized instances, we propose a matheuristic that estimates the infrastructural costs for each yard and train assignment by combining a constructive algorithm with a set covering model. It then solves a single-stage facility location problem to select yards and assign trains, followed by a yard-level improvement phase. Numerical experiments on a real Dutch case show that our approach delivers high-quality solutions quickly and offer insights into the optimal infrastructure design depending on the discretization of yard areas, number of trains, and other parameters.

关键词： Railway systems Hydrogen trains Fueling infrastructure Facility location problem mixed-integer linear programming Matheuristic

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A new inventory routing problem with route and schedule unpredictability

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Applied Mathematical Modelling 2025年 147卷

作者： Marlize H. Visser Jan H. van Vuuren Stellenbosch Unit for Operations Research in Engineering Department of Industrial Engineering Stellenbosch University Private Bag XI Matieland 7602 South Africa

The inventory routing problem (IRP) in a retail supply chain setting allows for the simultaneous optimisation of delivery schedules, vehicle routes, and delivery quantities. The IRP relies on the adoption of a vendor-managed inventory strategy which has the potential to reduce transportation, inventory, and stock-out costs in a supply chain. In this paper, we introduce a mathematical model for a new IRP variant, the heterogeneous fixed fleet IRP with time-windows (HeFIRPTW) with route and schedule unpredictability, in the form of a bi-objective mixed-integer linear programming problem. This model simultaneously incorporates route and schedule unpredictability aimed at mitigating inherent safety and security threats experienced during the transportation of valuable goods. Delivery routes and schedules are generated that minimise the operational costs incurred whilst also ensuring that route segments are not traversed too regularly and that customers are not visited during overlapping daily time intervals. The feasibility of adopting an exact ϵ -constrained model solution method is investigated empirically by solving small, adapted benchmark instances of the problem. An investigation into the model solution complexity for varying problem sizes reveals that unpredictability, particularly with tightened constraints, increases the computational time. The complexity implications of multiple vehicles and the imposition of time-windows are also examined. The results highlight the computational demands of the proposed model, demonstrating a clear need for a faster, perhaps approximate, solution approach capable of generating high-quality solutions for realistic problem instances within reasonable time-frames.

关键词： Inventory routing problem mixed-integer linear programming Multi-objective optimisation Route unpredictability Schedule unpredictability

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A Model Predictive Control for Microgrids Considering Battery Aging

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Journal of Modern Power Systems and Clean Energy 2020年第2期8卷 296-304页

作者： Ugur Can Yilmaz Mustafa Erdem Sezgin Murat Gol Department of Electrical and Electronics Engineering Middle East Technical UniversityAnkaraTurkey

The increasing number of distributed energy resources(DERs),advancing communication and computation technologies,and reliability concerns of the customers have caused an intense interest in the concept of *** DERs are the biggest motivation of the microgrids due to their intermittent generation characteristics,they constitute a risk for system *** storage systems(BSSs)stand as one of the most effective solutions for this reliability ***,the inappropriate use of BSS creates other operational problems in power *** order to deal with these concerns explicitly in microgrids,an optimized microgrid central controller(MGCC)is the key factor,which controls the realtime operation of a *** work proposes a model predictive control(MPC)based MGCC that will provide optimal control of the microgrid,considering economic and operational *** proposed system will minimize the energy cost of the microgrid by utilizing mixed-integer linear programming(MILP)assuming the presence of DERs and BSS as well as the bi-directional grid ***,the aging effect of BSS will be considered in the proposed optimization problem which will provide an up-to-date system *** proposed method is evaluated using real load and photovoltaic(PV)generation data.

关键词： Microgrid optimization battery storage model predictive control mixed-integer linear programming

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A linear AC-OPF Formulation for Unbalanced Distribution Networks

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2021年第5期57卷 4462-4472页

作者： Giraldo, Juan S. Vergara, Pedro P. Lopez, Juan Camilo Nguyen, Phuong Hong Pateralds, Nikolaos G. Univ Twente EEMCS Fac Math Operat Res Grp NL-7522 NB Enschede Netherlands Delft Univ Technol Intelligent Elect Power Grids Grp NL-2628 CD Delft Netherlands Univ Estadual Campinas Sch Elect & Comp Engn BR-13083970 Campinas Brazil Eindhoven Univ Technol Energy Syst Grp NL-5612 AP Eindhoven Netherlands

linear optimal power flow (OPF) formulations are powerful tools applied to a large number of problems in power systems, e.g., economic dispatch, expansion planning, state estimation, congestion management, electricity markets, among others. This article proposes a novel mixed-integer linear programming formulation for the ac-OPF of three-phase unbalanced distribution networks. The model aims to minimize the total energy production cost while guaranteeing the network's voltage and current magnitude operational limits. New approximations of the Euclidean norm, which is present in the calculation of nodal voltage and branch current magnitudes, are introduced by applying a linear transformation of weighted norms and a set of intersecting planes. The accuracy, optimality, feasibility, and scalability of the proposed linearizations are compared with common linear approximations in the literature using two unbalanced distribution test systems. The obtained results show that the proposed formulation is computationally more efficient (almost twice) while being as accurate and more conservative than the benchmarked approaches with maximum errors lower than 0.1%. Thus, its potential application in a variety of distribution systems operation and planning optimization problems is endorsed.

关键词： Substations programming Computational modeling Scalability Reactive power Distribution networks Admittance Ac optimal power flow Euclidean norm approximation mixed-integer linear programming unbalanced distribution networks

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Petroleum allocation at PETROBRAS: Mathematical model and a solution algorithm

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COMPUTERS & CHEMICAL ENGINEERING 2009年第12期33卷 2123-2133页

作者： Rocha, Roger Grossmann, Ignacio E. Poggi de Aragao, Marcus V. S. Pontif Catholic Univ Dept Informat Rio De Janeiro Brazil Ctr Res & Dev PETROBRAS Logist Div BR-21949900 Rio De Janeiro Brazil Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

Petroleum allocation is an important link for the integration of petroleum supply chain at PETROBRAS as it is responsible for refining the strategic supply planning information to be used at the operation levels. In this work we describe how mathematical programming is being used to solve the petroleum allocation problem and we show the effectiveness of a local search method by optimization to solve real industrial problems. We propose a mixed-integer linear programming formulation of the problem that relies on a time/space discretization network. As the model cannot be solved for the industrial size instances of the problem, and not even a feasible solution can be found after 15 days of computation, we implement an algorithm based on a heuristic to find a feasible solution and on a local search procedure based on optimization to improve it. Using this algorithm. Solutions are found for all the case studies within 10% of optimality in less than 5 h. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Petroleum supply chain mixed-integer linear programming Local branching procedure

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Three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants

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Chinese Journal of Chemical Engineering 2022年第4期35卷 29-40页

作者： Kexin Bi Mingyu Yan Shuyuan Zhang Tong Qiu Department of Chemical Engineering Tsinghua UniversityBeijing 100084China Beijing Key Laboratory of Industrial Big Data System and Application Beijing 100084China Fushun Petrochemical Company PetroChinaFushun 113008China

In order to explore the potential of profit margin improvement,a novel three-scale integrated optimization model of furnace simulation,cyclic scheduling,and supply chain of ethylene plants is proposed and evaluated.A decoupling strategy is proposed for the solution of the three-scale model,which uses our previously proposed reactor scale model for operation optimization and then transfers the obtained results as a parameter table in the joint MILP optimization of plant-supply chain scale for cyclic *** optimization framework simplifies the fundamental mixed-integer nonlinear programming(MINLP)into several sub-models,and improves the interpretability and *** the evaluation of an industrial case,a profit increase at a percentage of 3.25%is attained in optimization compared to the practical *** sensitivity analysis is carried out for strategy evolving study when price policy,supply chain,and production requirement parameters are *** results could provide useful suggestions for petrochemical enterprises on thermal cracking production.

关键词： Three-scale integrated optimization Cyclic scheduling Supply chain mixed-integer linear programming Thermal cracking

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A risk-based methodology for the optimal placement of hazardous gas detectors

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Chinese Journal of Chemical Engineering 2018年第5期26卷 1078-1086页

作者： Kang Cen Ting Yao Qingsheng Wang Shengyong Xiong School of Civil Engineering and Architecture Southwest Petroleum University Chengdu 610500 China Department of Fire Protection & Safety and Department of Chemical Engineering Oklahoma State University Stillwater OK 74078 USA Wanzhou Branch Plant of Chongqing General Natural Gas Purification Plant Southwest Oil & Gasfield Company PetroChina Wanzhou Chongqing 404001 China

Hazardous gas detection systems play an important role in preventing catastrophic gas-related accidents in process industries. Even though effective detection technology currently exists for hazardous gas releases and a majority of process installations have a large number of sensitive detectors in place, the actual operating performance of gas detection systems still does not meet the expected requirements. In this paper, a riskbased methodology is proposed to optimize the placement of hazardous gas detectors. The methodology includes three main steps, namely, the establishment of representative leak scenarios, computational fluid dynamics(CFD)-based gas dispersion modeling, and the establishment of an optimized solution. Based on the combination of gas leak probability and joint distribution probability of wind velocity and wind direction, a quantitative filtering approach is presented to select representative leak scenarios from all potential scenarios. The commercial code ANSYS-FLUENT is used to estimate the consequence of hazardous gas dispersions under various leak and environmental conditions. A stochastic mixed-integer linear programming formulation with the objective of minimizing the total leak risk across all representative leak scenarios is proposed, and the greedy dropping heuristic algorithm(GDHA) is used to solve the optimization model. Finally, a practical application of the methodology is performed to validate its effectiveness for the optimal design of a gas detector system in a high-sulfur natural gas purification plant in Chongqing, China. The results show that an appropriate number of gas detectors with optimal cost-effectiveness can be obtained, and the total leak risk across all potential scenarios can be substantially reduced. This methodology provides an effective approach to guide the optimal placement of pointtype gas detection systems involved with either single or mixed gas releases.

关键词： Leak scenario Leak risk Gas detection Detector placement mixed-integer linear programming

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A hybrid metaheuristic to solve the multi-trip team orienteering problem with integrated tours and increasing profits for blood transportation

Operations Research, Data Analytics and Logistics

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Operations Research, Data Analytics and Logistics 2025年 45卷

作者： Andrea Pirabán-Ramírez William Javier Guerrero-Rueda Nacima Labadie Doctorado en Logística y Gestión de Cadenas de Suministros Universidad de La Sabana Campus Puente del Común Km. 7 Autopista Norte de Bogotá. Chía Cundinamarca Colombia Computer Science and Digital Society Laboratory (LIST3N) University of Technology of Troyes 12 Rue Marie Curie CS 42060 10004 Troyes CEDEX France School of Engineering Universidad de La Sabana Campus Puente del Común Km. 7 Autopista Norte de Bogotá. Chía Cundinamarca Colombia

The efficient management of the blood supply chain is paramount, given its critical impact on human lives if improperly handled. This research focuses on the location of mobile collection sites over a multiperiod horizon and transferring blood units from these sites to blood centers using a multi-trip shuttle fleet. The goal is to minimize the total cost comprising the transportation, delay, wastage, and shortage costs. The model considers constraints such as the tight time limit between the collection and processing of platelets and cryoprecipitates. Additionally, collection levels at donation sites are modeled assuming linear increasing rates. First, the problem is modeled as a mixed-integer linear program; then, a hybrid iterative local search is designed as a solution approach. The effectiveness and applicability of the proposed method are evaluated through a set of 39 new instances based on the blood collection system of Bogota, Colombia, which demonstrates promising solutions by systematically computing the best-known solutions.

关键词： BBS Bogota blood system BC blood center BCP blood collection problem BKS best-known solution BSC blood supply chain cryo cryoprecipitate CS collection site ILS iterative local search MILP mixed-integer linear programming MT-TOPIT-IP multi-trip team orienteering problem with integrated tours and increasing profits MT-VRPIP multi-trip vehicle routing problem with increasing profits NP-hard non-deterministic polynomial-time hard PLT platelet VND variable neighborhood descent WB whole blood Healthcare logistics Optimization OR in health services Perishable products Variable profits

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Power capacity enhancement of hydropower plant through the penetration of solar and wind energy

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International Journal of Electrical Power & Energy Systems 2025年 169卷

作者： Ahmad Shah Irshad Ahmad Shah Amin Amir Mohammad Ilham M.H. Elkholy Said Elias Tomonobu Senjyu Department of Electrical and Electronics Engineering Faculty of Engineering University of the Ryukyus Okinawa 903-0213 Japan Department of Energy Engineering Engineering Faculty Kandahar University Kandahar 3801 Afghanistan Da Afghanistan Brashna Sharkat Kandahar 3801 Afghanistan Electrical Power and Machines Faculty of Engineering Zagazig University P.O. 44519 Zagazig Egypt Institute for Risk and Reliability Leibniz University Hannover Germany

Integrating renewable energy sources is crucial for enhancing the power capacity and reliability of existing hydropower plants. This study explores the potential of augmenting hydropower capacity by incorporating solar and wind energy. By leveraging the complementary nature of these renewable sources, the study aims to optimize energy production and reduce dependence on hydro resources during low water availability. A comprehensive analysis, including simulation models and field data, demonstrates the effective harnessing and synchronization of solar and wind energy with hydropower generation. A multi-objective genetic algorithm was employed to optimize this integration, addressing objectives such as maximizing power output, improving energy efficiency, and minimizing environmental impact. This algorithm facilitated the identification of effective strategies for enhancing the performance and capacity of the hybrid renewable energy system. Three key objectives were achieved: reducing the Loss of Power Supply Probability (LPSP) to 0.75 %, calculating the net present cost (NPC) at $4.37 million, and determining the cost of energy (COE) at $0.086 per kilowatt-hour (kWh). These results demonstrate the economic viability and reliability of the integrated system. The power generation capacity of the plant was enhanced by 25 % with integration of PV, and wind energy system. The findings reveal significant improvements in power capacity and grid stability, highlighting the feasibility and benefits of a hybrid renewable energy system. This approach enhances energy security, reduces greenhouse gas emissions by 248,922.4 tons per year, and promotes clean energy use. The study offers valuable insights and guidelines for policymakers and energy planners seeking to implement similar strategies.

关键词： Hybrid Renewable Energy System Solar-Wind-Hydro Integration Energy Cost Optimization Net Present Cost Analysis Power Supply Reliability Environmental Sustainability CO 2 Carbon dioxide COE Cost of energy CRF Capital recovery factor DG Diesel generator GA Genetic algorithm GHG Greenhouse gas GHI Global horizontal irradiance GOA Grasshopper optimization algorithm HRES Hybrid renewable energy systems IRENA International Renewable Energy Agency LCOE Levelized cost of energy LPSP Loss of power supply probability MILP mixed-integer linear programming MOGA Multi-objective genetic algorithm MPSO Modified particle swarm optimization NASA National Aeronautics and Space Administration NOCT Nominal operating cell temperature NPC Net present cost O&M Operation and maintenance PHS Pumped hydro storage PV Photovoltaic RE Renewable energy RES Renewable energy sources STC Standard test condition UNFCCC United Nations Framework Convention on Climate Change WT Wind turbine

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Resource-constrained maximum network throughput on space networks

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Journal of Systems Engineering and Electronics 2015年第2期26卷 215-223页

作者： Yanling Xing Ning Ge Youzheng Wang Department of Electronic Engineering Tsinghua University Research Institute of Tsinghua University in Shenzhen Department of Aeronautics and Astronautics Engineering Tsinghua University

This paper investigates the maximum network through- put for resource-constrained space networks based on the delay and disruption-tolerant networking （DTN） architecture. Specifically, this paper proposes a methodology for calculating the maximum network throughput of multiple transmission tasks under storage and delay constraints over a space network. A mixed-integer linear programming （MILP） is formulated to solve this problem. Simula- tions results show that the proposed methodology can successfully calculate the optimal throughput of a space network under storage and delay constraints, as well as a clear, monotonic relationship between end-to-end delay and the maximum network throughput under storage constraints. At the same time, the optimization re- sults shine light on the routing and transport protocol design in space communication, which can be used to obtain the optimal network throughput.

关键词： throughput disruption-tolerant networking(DTN) maximum flow mixed-integer linear programming evolving graph space network

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