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

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Bi-objective Resource Allocation for Multi-product and Multi-stage Steel Production Systems

Bi-objective Resource Allocation for Multi-product and Multi...

引用

Chinese Control and Decision Conference, CCDC

作者： Zhuohan Zhang Yang Zhang Shixin Liu College of Information Science and Engineering Northeastern University Shenyang China Huiju Business Group Shell Housing Technology Co.ltd Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Reasonable resource allocation is the key to coordinated production among the processes in steel enterprises. This paper deals with a novel bi-objective resource allocation problem arising from steel production systems. One objective function is to minimize the sum of various costs related to transportation, fixed, shortage, and storage. The other objective function is to balance the machine’s workload in the same stage. A mixed integer linear programming model is developed for the concerned problem. Non-dominated sorting genetic algorithm II is designed to solve it. Experimental results indicate that our algorithm can obtain multiple Pareto solutions quickly. Its excellent performance is verified, thus demonstrating that it is ready to be applied in practice.

关键词： Production systems Costs Transportation linear programming mixed integer linear programming Steel Resource management

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Investigating the Bidding Strategy of Loaded Virtual Power Plant While Considering Multiple Demand Response Resources

Investigating the Bidding Strategy of Loaded Virtual Power P...

引用

IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Juan Zuo Chongxin Xu Yu Ji Wenbo Wang Shengkui Ma Ying Zhang State Grid Shanghai Energy Internet Research Institute Co. LTD Shanghai Jiao Tong University Shanghai China State Grid Shanghai Energy Internet Research Institute Co. LTD Shanghai China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

In recent years, in response to national policies, the traditional power system has gradually evolved to the new power system in order to achieve low-carbon power generation. System operators, loaded virtual power plant and end users are the three main players in the current power market. However, most current studies take demand response as a constraint, and rarely take loaded virtual power plant as the main body. This will lead to the failure to integrate the user's demand response resources to participate in the electricity market bidding, so as to provide a feasible demand response scheme for each individual user. This paper takes the loaded virtual power plant as the main body, adopts the layered bidding strategy, establishes the demand response model of the loaded virtual power plant and the response contract to participate in the day-ahead market bidding, and uses the simulation to solve the mixed integer linear programming model, so as to obtain the optimal allocation scheme.

关键词： Virtual power plants Electricity supply industry Demand response Power markets Power systems mixed integer linear programming Resource management Power generation Contracts Load modeling

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A Multi-Objective Optimization Problem for Load Restoration of Power Distribution Networks by Network Reconfiguration and Repair Crew Deployment

A Multi-Objective Optimization Problem for Load Restoration ...

引用

National Power Systems Conference (NPSC)

作者： Vandana Kumari Sanjib Ganguly Department of Electronics and Electrical Engineering Indian Institute of Technology Guwahati Guwahati India

ISBN: (数字)9798331519568

ISBN: (纸本)9798331519575

Extreme events like earthquakes, wildfires, and windstorms are rare but significantly impact power distribution networks (PDNs). Therefore, it is important to improve the resilience of PDNs. Repair crew deployment and network reconfiguration are the two most effective operational measures for the resilience enhancement of PDNs. These two operational measures are utilized in this study for load restoration of PDNs. This study proposes a multi-objective mixed integer linear programming (MO-MILP) model aimed at optimizing the operation of switches and scheduling repair sequences for damaged lines. The optimization problem has two main objectives: the first is to minimize load shedding, and the second is to minimize the cost associated with load restoration. The cost of load restoration includes the operating expenses of switches, as well as the travel and repair expenses of the repair crews. The weighted sum method is used to solve the proposed MO-MILP model. Furthermore, the proposed model is validated using a 33-bus test system.

关键词： Seismic measurements Costs Load shedding Maintenance engineering Minimization Power systems mixed integer linear programming Optimization Load modeling Resilience

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Optimal Sizing of a Multi - Energy Port with Vehicles Charging Capabilities

Optimal Sizing of a Multi - Energy Port with Vehicles Chargi...

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International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles & International Transportation Electrification Conference (ESARS-ITEC)

作者： F. D’Agostino M. Gallo D. Kaza M. Saviozzi F. Silvestro F. Conte University of Genova DITEN Genova Italy Università Campus Bio-Medico di Roma Faculty of Engineering Roma Italy

ISBN: (数字)9798350373905

ISBN: (纸本)9798350373912

This work proposes a three-stage optimal sizing procedure for a green smart port, considering boats and cars connected to the grid. A mixed integer linear programming formulation is exploited, integrating the operational profile of all the vehicles connected to the charging points. The aggregated power profile of all the vehicles is obtained through several iterations of the sizing algorithm. Electric vehicles can operate in vehicle-to-grid mode, performing energy regulation in order to maximize the port earnings. The algorithm, developed in the Matlab environment, is tested on a notional marina. The results demonstrate that the integration of the vehicles into the port can reduce the size of the storage system, especially when operating in vehicle-to-grid mode.

关键词： Vehicle-to-grid Sensitivity analysis Green products Transportation Electrification Regulation Discharges (electric) mixed integer linear programming MATLAB Energy management

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Production Simulation Method of High Proportion New Energy Power System Based on Interval Probability

Production Simulation Method of High Proportion New Energy P...

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Electrical Engineering and Automation (IFEEA), International Forum on

作者： Shenglei Du Ding Li Yu Xin Qi Cao State Grid Gansu Economic and Technological Research Institute Lanzhou China Xi'an Jiaotong University Xi'an China

ISBN: (数字)9798331516611

ISBN: (纸本)9798331516628

With the large-scale new energy connected to the grid, its volatility and randomness bring challenges to the power system increasingly prominent. It is urgent to study how to reduce or avoid the wind and light cutting load and evaluate the reliability of power system reasonably. This study introduces a stochastic production simulation algorithm utilizing interval probability. Initially, a maintenance strategy for the units is developed using the equal reserve capacity approach, and unit commitment is established through mixed integer linear programming. Next, scenario reduction is performed based on interval probability assessments, and the critical scenarios are selected for scheduling simulations. Lastly, through example analysis, the proposed approach demonstrates its accuracy and effectiveness, enabling it to handle a significant share of new energy integration and optimize power system operations.

关键词： Electrical engineering Schedules Thermal engineering Production Probability Power systems Maintenance Power system reliability mixed integer linear programming Capacity planning

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Algorithms for Fair Repetitive Scheduling

Algorithms for Fair Repetitive Scheduling

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IEEE International Conference on Industrial Engineering and Engineering Management

作者： D. Shabtay A Plotkin Y. Fink Department of Industrial Engineering Ben Gurion University of the Negev Beer Sheva Israel Department of Computer Science Ben Gurion University of the Negev Beer Sheva Israel

ISBN: (数字)9798350386097

ISBN: (纸本)9798350386103

We consider a single machine scheduling problem consisting of $\boldsymbol{n}$ clients and q consecutive operational periods (e.g., days). Each client submits a single job to processing on each of the days and wants his jobs to be completed as early as possible. A solution is defined by a set of q schedules (one per day), and it is classified as a K-fair solution if the total completion time of any of the clients on the entire set of q days is not greater than K. The scheduler’s objective is to obtain a K-fair solution with the minimum possible K value. The problem is known to be strongly NPhard, but no practical techniques were developed for solving it. Our main goal is to close this gap in the literature by providing a set of tools to maximize the system’s fairness. To do so, we design a mixed integer linear programming formulation, two greedy algorithms and a metaheuristic. We intend to compute the entire set of algorithms and to test the quality of the different algorithms by applying an extensive experimental study.

关键词： Greedy algorithms Schedules Job shop scheduling Processor scheduling Engineering management Metaheuristics Industrial engineering mixed integer linear programming Single machine scheduling

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Profit Maximization Under Unit Commitment Solutions Through Self-Scheduling

Profit Maximization Under Unit Commitment Solutions Through ...

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Electrical Power Engineering, Communication and Computing Technology(ODICON), Odisha International Conference on

作者： Dipu Mistry Bishaljit Paul Reshmi Chandra Suman Moitra Chandan Kumar Chanda Department of Electrical Engineering Narula Institute of Technology Kolkata India Department of Electrical Engineering Abacus Institute of Engineering and Management Hooghly India Department of Electrical Engineering Elitte College of Engineering Sodepur India Department of Electrical Engineering IIEST Shibpur Howrah India

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

The variable renewable energy sources with null operating cost like solar, photovoltaic and wind which are of significant rise of interest as it proclaims to reduce the greenhouse gases, aims the reduction of the carbon footprints. These renewables are intermittent due to meteorological phenomena and affects the production. A possible solution to alleviate this is to combine with conventional generators, known as mixed generation. These conventional generators which participate, though costly but deterministic to cope up with the load. A basic model using dc power flow model, which is a linearized ac model, representing ON and OFF status, shut down, start up, ramp up and ramp down costs and imposing bounds, while declaring binary variables and logical expression which are formulated. Here in this paper, it is revealed through a 6-hour planning horizon that an owner who owns power plant, want to make profit with the conventional plant. The profit to be maximized is calculated using mixed integer linear programming at each hour.

关键词： Renewable energy sources Costs Software algorithms Production Mathematical models Generators Software Planning mixed integer linear programming Load modeling

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Heuristic vs. Analytical Energy Hub Optimization: Design, Implementation, and Trade-Offs

Heuristic vs. Analytical Energy Hub Optimization: Design, Im...

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IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Simon Grafenhorst Jakob Ohm Rafael Poppenborg Kevin Förderer Veit Hagenmeyer Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Karlsruhe Germany

ISBN: (数字)9798350377378

ISBN: (纸本)9798350377385

Various algorithms can be used to optimize the operation of energy hubs, which differ in complexity and optimization quality. The heuristic Evolutionary Algorithm (EA) is able to approximate solutions to complex and non-convex problems. In comparison, the mixed-integer linear programming (MILP) and the mixed-integer Quadratic Program (MIQP) are able to compute the optimal solution of an approximated model. The present paper focuses on the comparison of energy hub schedule optimization using an EA, a MILP, and a MIQP. Furthermore, the source code for the MILP and MIQP models is publicly available. In our comparison, the analytical solver can optimize the schedule of an exemplary energy hub within seconds, and the EA takes multiple minutes to compute. The schedule generated with the analytical models follows the target closely with a similar root-mean-square error as the schedule generated by the EA.

关键词： Schedules Analytical models Computational modeling Source coding Evolutionary computation Approximation algorithms mixed integer linear programming Complexity theory Optimization

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Mathematical formulations for the offshore mobile charging vessel location and unmanned surface vehicle scheduling problem

Mathematical formulations for the offshore mobile charging v...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Bo Ren Haiying Liu Yantong Li School of Maritime Economics and Management Dalian Maritime University Dalian China

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

Unmanned surface vehicles (USVs) have been widely used in maritime logistics, environmental monitoring, and military fields due to their intelligence, flexibility, economy, and environmental protection advantages. However, USV applications are restricted by their limited operational capabilities. Most USVs are electrified, which require frequent charging operations, making them incapable of executing long-range tasks. Large mobile charging vessels have recently been produced to provide electric supply, enabling USVs to complete long-range tasks without returning to the port. This paper investigates an integrated mobile charging vessel location and USV scheduling problem, where multiple mobile charging vessels are deployed to offshore anchorages to provide charging services to USVs. The objective is to minimize the combined weighted sum of location costs, travel costs, and tardiness penalty costs. We propose two mixed integer linear programming models, which off-the-shelf commercial solvers can solve. Computational results on 40 random instances with up to 100 charging requests of USV, ten candidate locations, and five mobile charging vessels demonstrate the model’s effectiveness. In addition, sensitivity analysis is performed on key parameters, including time window duration and tardiness penalty coefficient, which provides useful managerial insights for practitioners.

关键词： Costs Sensitivity analysis Processor scheduling Computational modeling Surface charging Seaports Scheduling mixed integer linear programming Protection Autonomous vehicles

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An MILP Formulation for the Unit Commitment Problem Based on State Transitions

An MILP Formulation for the Unit Commitment Problem Based on...

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Power Science and Technology (ICPST), IEEE International Conference on

作者： Nianjie Tian Shijin Tian Jiang Dai Chong Tang Yang Xiao Tao Ding Power Dispatching Control Center Power Grid Co. Ltd. Guiyang China Electric Power Research Institute China Southern Power Grid Guangzhou China School of Electrical Engineering Xi’an Jiaotong University Xi’an China

ISBN: (数字)9798350349030

ISBN: (纸本)9798350349047

This paper proposes a method for establishing unit commitment (UC) problems based on state transitions. Specifically, this paper utilizes states to demonstrate the characteristics of generators, generates all relationships between these states, and establishes UC problems as a mixed-integer linear programming model. Due to this state transition formulation only requires describing the characteristics as states and their state transition relationships, this state transition formulation for UC problems permits more complex operation characteristics. Numerical experiments are conducted in this paper to verify the effectiveness of the state transition formulation for UC problems.

关键词： linear programming Generators Numerical models mixed integer linear programming

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