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检索条件"主题词=Mixed integer linear programming"

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Analysis of Hydrogen Storage for Seasonal Leveling of Renewable Energy Generation in Scenarios of Japan’s Generation Mix

Analysis of Hydrogen Storage for Seasonal Leveling of Renewa...

引用

IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Yuna Oishi Shoki Okawara Takuto Komuro Yusuke Manabe Nobuyuki Yamaguchi Department of Electrical Engineering Graduate School of Engineering Tokyo University of Science Tokyo Japan

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The power sector is being decarbonized to achieve carbon neutrality in 2050, and the Group of Seven (G7) has decided to phase out coal-fired power generation by 2035. In this study, we set up coal phase-out scenarios for 2030, 2040, and 2050 and conducted a simulation analysis by unit commitment with an expanded introduction of renewable energy. In this study, we estimate the optimal capacity of hydrogen storage system (HSS) for various future supply scenarios in Japan through an inter-seasonal energy supply-demand leveling simulation. The proposed method is a time series simulation of unit commitment (UC) and inter-seasonal hydropower storage systems using mixed integer linear programming (MILP). As a result, the HSS significantly contributed to reducing the amount of Variable Renewable Energy (VRE) output suppression and effectively utilizing VRE in all future scenarios.

关键词： Costs Hydrogen storage Sensitivity analysis Hydrogen Time series analysis Europe Carbon neutral Wind power generation Smart grids mixed integer linear programming

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zonoLAB: A MATLAB Toolbox for Set-Based Control Systems Analysis Using Hybrid Zonotopes

zonoLAB: A MATLAB Toolbox for Set-Based Control Systems Anal...

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American Control Conference (ACC)

作者： Justin Koeln Trevor J. Bird Jacob Siefert Justin Ruths Herschel C. Pangborn Neera Jain Department of Mechanical Engineering University of Texas at Dallas Richardson TX USA School of Mechanical Engineering Purdue University West Lafayette IN USA Department of Mechanical Engineering The Pennsylvania State University University Park PA USA

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper introduces zonoLAB, a MATLAB-based toolbox for set-based control system analysis using the hybrid zonotope set representation. Hybrid zonotopes have proven to be an expressive set representation that can exactly represent the reachable sets of mixed-logical dynamical systems and tightly approximate the reachable sets of nonlinear dynamic systems. Moreover, hybrid zonotopes can exactly represent the continuous piecewise linear control laws associated with model predictive control and the input-output mappings of neural networks with piecewise linear activation functions. The hybrid zonotope set representation is also highly exploitable, where efficient methods developed for mixed-integer linear programming can be directly used for set operation and analysis. The zonoLAB toolbox is designed to make these capabilities accessible to the dynamic systems and controls community, with functionality spanning fundamental operations with hybrid zonotope, constrained zonotope, and zonotope set representations, powerful set analysis tools, and general-purpose algorithms for reachability analysis of open- and closed-loop systems.

关键词： Control system analysis Heuristic algorithms Neural networks Nonlinear dynamical systems mixed integer linear programming Complexity theory Closed loop systems

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Accounting for Travel Time and Arrival Time Coordination During Task Allocations in Legged-Robot Teams

Accounting for Travel Time and Arrival Time Coordination Dur...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Shengqiang Chen Yiyu Chen Ronak Jain Xiaopan Zhang Quan Nguyen Satyandra K. Gupta Department of Aerospace and Mechanical Engineering University of Southern California Los Angeles CA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Many applications require the deployment of legged-robot teams to effectively and efficiently carry out missions. The use of multiple robots allows tasks to be executed concurrently, expediting mission completion. It also enhances resilience by enabling task transfer in case of a robot failure. This paper presents a formulation based on mixed integer linear programming (MILP) for allocating tasks to robots by taking into account travel time and ensuring efficient execution of collaborative tasks. We extended the MILP formulation to account for complexities with legged robot teams. Our results demonstrate that this approach leads to improved performance in terms of the makespan of the mission. We demonstrate the usefulness of this approach using a case study involving the disinfection of a building consisting of multiple rooms.

关键词： Legged locomotion Uncertainty Robot kinematics Collaboration mixed integer linear programming Complexity theory Time factors

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Optimal Residential Community Demand Response Scheduling Based on User Preferences and MILP

Optimal Residential Community Demand Response Scheduling Bas...

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Chinese Control and Decision Conference, CCDC

作者： Qiya Peng Xiaohui Li Shanli Mao Bin Cai Jie He Wei Nie School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China Research Center Wuhan Netizen Technology Co. Ltd Wuhan China Research Center Shenglong Electric Group Co. Ltd Wuhan China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Demand response manages energy demand to match available energy in the smart grid. Residential community loads in the smart grid are diverse and flexible. To integrate user preferences with demand response scheduling for residential communities, a centralized demand response scheduling algorithm is proposed. In this paper, user willingness price is first introduced through fuzzy c-means to quantify user preferences. Secondly, a complete residential community DR scheduling algorithm is established based on use preference and mixed integer linear programming to minimize the total energy cost of the residential community. Simulation results show that the proposed algorithm can reduce the total energy cost of the residential community and communication traffic.

关键词： Costs Scheduling algorithms Simulation Demand response Scheduling Smart grids mixed integer linear programming

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Electric Vehicle Flexibility Harnessing Through Local Energy Community Operation Optimization: Maximizing Local Energy Utilization

Electric Vehicle Flexibility Harnessing Through Local Energy...

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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Enielma Cunha da Silva Carlos Sabillon Bala Venkatesh John Fredy Franco Department of Electrical Engineering Sao Paulo State University (UNESP) Ilha Solteira Brazil Universidad Loyola Andalucía Sevilla Spain Centre for Urban Energy Toronto Metropolitan University(TMU) Toronto Canada

ISBN: (数字)9798350355185

ISBN: (纸本)9798350355192

With an uprising penetration, local energy communities (LECs) face the local challenge of reaching energy self-sufficiency (catering for high generation-demand time mismatch) and the system-wide challenge of securely operating within the distribution network. In this sense, a novel strategy for LEC operation is proposed to overcome these challenges, aiming to maximize local consumption by controlling the charging/discharging of EVs and exploiting distributed generation resources at full, guaranteeing a distribution system secure operation. For this, the local operation of LECs (encompassing conventional and flexible demand members and prosumer members) is represented by a mixed-integer linear programming model, also considering the LEC interaction with the distribution network, and distribution system technical limits. To validate the proposed strategy, the impact of the economic interaction among LECs as well as EV charging/discharging control on LECs’ self-consumption, was analyzed in a case study under different operation conditions. The numerical results demonstrate that, when compared to the baseline scenario, EV charging/discharging coordination enabled the local supply of 80.5% of the LECs' daily energy, increasing to 88.31% when the interaction between LECs is enabled.

关键词： Economics Optimal control Europe Distribution networks Electric vehicles Mathematical models mixed integer linear programming Numerical models Optimization Faces

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Loop-Based Maritime Transport Optimization in Swedish National Freight Transport Models

Loop-Based Maritime Transport Optimization in Swedish Nation...

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： Jonas Westin Leif Olsson Per Åhag Department of Mathematics and Mathematical Statistics Umeå University Umeå Sweden Department of Communication Quality Management and Information Systems Mid Sweden University Sundsvall

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

This study addresses enhancements to the Swedish national freight transport model, Samgods, focusing on improving its maritime transport modeling capabilities. The current model faces challenges in accurately representing maritime transport due to its limitations in consolidation of diverse cargo types, and modeling indirect sea routes. We propose an advanced model using a mixed integer linear programming (MILP) technique to integrate transport loops, thereby increasing the model’s efficiency and realism in depicting maritime transport scenarios. A case study on the shipping of forest products from Northern Sweden to Western Europe illustrates the method’s effectiveness. Introducing transport loops into the model results in a $10-21\%$ reduction in logistics costs and a $2-4 \%$ increase in the utilization of maritime transport. The fleet composition also changes to more resemble real world data. These findings highlight the importance of loop structures in accurately capturing the full benefits of maritime transport in freight transport modeling.

关键词： Analytical models Adaptation models Costs Computational modeling Seaports Complexity theory mixed integer linear programming Optimization Standards Backhaul networks

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Optimizing Parking Lot Management with Mobile Energy Suppliers for Electric Vehicles

Optimizing Parking Lot Management with Mobile Energy Supplie...

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Global Energy Conference (GEC)

作者： Ali Furkan Tetik Hayri Yigit Ayse Kubra Erenoglu Ozan Erdinc Ali Rifat Boynuegri Dept. of Electrical Engineering Yildz Technical University Istanbul Türkiye Dept. of Electrical Engineering & Clean Energy Technologies Institute Yildiz Technical University Istanbul Türkiye

ISBN: (数字)9798331532611

ISBN: (纸本)9798331532628

As the increment of electric vehicles (EVs) continues, efficient parking lot management emerges as a critical concern. The constraints of traditional fixed charging stations can be mitigated by leveraging the flexibility provided by mobile energy suppliers (MES). This study explores the application of MES in public parking lots to optimize energy consumption. By integrating photovoltaic (PV) resources with grid connectivity, the dependence on grid-supplied energy is significantly reduced. A mixed-integer linear programming (MILP) optimization model has been developed to minimize energy costs. The results confirm that MES offers a dynamic and cost-effective solution, improving both parking management and energy efficiency. The economic and operational effectiveness of the proposed framework is supported by practical implementation.

关键词： Photovoltaic systems Energy consumption Renewable energy sources Costs Sockets Optimization models Production Electric vehicles mixed integer linear programming Vehicle dynamics

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Train Operating Schedule Adjustment Model Based on Rain and Snow Conditions

Train Operating Schedule Adjustment Model Based on Rain and ...

引用

International Conference on Intelligent Transportation

作者： Jingyang Zhou Xueliang Wu Du Shang Shuai Su State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing P. R. China Beijing Mass Transit Railway Operation Corporation Limited Beijing P. R. China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Inclement weather, such as rain and snow, can significantly affect the operation of urban rail systems, particularly in open-air sections of the track. In order to ensure the safety of train operation, it is necessary to organize the train to run at a limited speed in the open-air section. Train timetable is the basis of urban rail transportation organization, and trains run according to the given planning train timetable under normal conditions. However, the imposition of speed restrictions during adverse weather can result in delays and subsequent disruptions to the schedule. To address this problem, combined with the objectives and characteristics of operation and scheduling under rainy and snowy weather conditions, the train is adjusted by comprehensively adopting adjustment means such as early train departure, shortening stopping time, additional reserve trains, intermediate turnarounds and compression of the turnaround time of the underground line, and a train constraint model under rainy and snowy conditions has been established to take into account the decision-making variable sand constraints related to the training. The main objective under rain and snow conditions is to maintain capacity as much as possible, so the model aims to minimize train timetable deviations and minimize the number of stations with service cancellations to model the adjustment of train operations under rain and snow conditions and derive valid inequalities based on the model characteristics. The model is then transformed into a mixed-integer linear programming (MILP) model, which is solved using effective inequalities combined with the branch-and-bound method of SCIP. Finally, the validity of the model is verified by an arithmetic example.

关键词： Training Schedules Rain Snow Computational modeling Scheduling mixed integer linear programming Delays Safety Meteorology

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Poster Abstract: Landing-Type Aware Multi-Drone Route Generation for Last-Mile Delivery Service

Poster Abstract: Landing-Type Aware Multi-Drone Route Genera...

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IEEE/ACM International Conference on Cyber-Physical Systems (ICCPS)

作者： JiHyun Kwon BaekGyu Kim Yi-Ying Chen Chung-Wei Lin Dept. of Electrical Engineering and Computer Science DGIST Daegu South Korea Dept. of Computer Science and Information Engineering National Taiwan University Taipei Taiwan

ISBN: (数字)9798350369274

ISBN: (纸本)9798350369281

We consider the problem of generating delivery routes for multiple drones in the last-mile delivery service. In particular, the landing type—how a parcel is to be dropped off from a drone—is explicitly modeled in terms of the landing area and the landing time, which was not considered in other drone delivery works. A mixed integer linear programming (MILP) problem is formulated to optimize the delivery route for each drone by minimizing the total delivery completion time. Our preliminary result shows that landing types affect the total delivery completion time significantly, even with a small number of drones. Therefore, it is necessary to explicitly consider the characteristics of landing types for more realistic delivery route generation of a large number of drones.

关键词： Cyber-physical systems mixed integer linear programming Drones

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Genetic Algorithm-Based Synthesis-, Design-, and Operation Optimization of Large Sector Coupled Ship Energy Systems

Genetic Algorithm-Based Synthesis-, Design-, and Operation O...

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Design Methodologies Conference (DMC), IEEE

作者： Mattis Molinski Timon S. Hartwich Thorsten A. Kern Institute for Mechatronics in Mechanics Hamburg University of Technology Hamburg Germany

ISBN: (数字)9798350355864

ISBN: (纸本)9798350355871

The decarbonization of the maritime industry is crucial for mitigating climate change. Achieving this goal involves increasing power generation efficiency, adopting non-fossil fuels, and enhancing overall ship efficiency. This study introduces the Maritime Energy System Optimizer (MESO), a modular Python platform designed to enhance ship concepts through holistic synthesis, design, and operation optimization of sector coupled ship energy systems (ES). MESO uses a genetic algorithm for synthesis and design optimization, and, nested within the fitness calculation, a mixed-integer linear programming approach for operation optimization based on power flows and energy balances using the open energy modelling framework (oemof). Validation studies, based on a 2018 cruise liner with 30 MW propulsion power and high demand granularity, demonstrated the effectiveness of MESO for various levels of detail. MESO reduces unnecessary iterations compared to the conventional heuristic design process and enables more informed decision-making. Optimized ESs are at least 4.4 % cheaper than conventional systems, mainly due to the integration of storages for peak shaving and load balancing. MESO is designed for easy expansion and will be extended to include partial load efficiency, demand-side management, and load profile generation.

关键词： Propulsion Low carbon economy Load management mixed integer linear programming Marine vehicles Optimization Power generation Genetic algorithms Python Load flow Climate change

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