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

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Short-term hydro generation and interchange contract scheduling for Swiss Rail

Short-term hydro generation and interchange contract schedul...

引用

Power Industry Computer Application Conference (PICA)

作者： M. Christoforidis B. Awobamise Sai Tong R.J. Frowd F.A. Rahimi Muhamed Aganagic Siemens Empros Power Systems Control Brooklyn MN USA Macro Corporation Mountain View CA USA

This paper describes the short-term resource scheduling (STRS) function that has been developed by Siemens-Empros as part of the new SBB/Direktion Kraftwerk (Swiss Rail) energy management system. Optimal scheduling of the single-phase hydroelectric power plants, single-phase and three-phase energy accounts, and purchase and sale of three phase energy subject to a multitude of physical and contractual constraints (including spinning and regulating reserve requirements), is the main objective of the STRS function. The operations planning horizon of STRS is one day to one week using an hourly time increment.

关键词： Contracts Rails Optimal scheduling Reservoirs Marketing and sales Frequency conversion Senior members Spinning mixed integer linear programming Rivers

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Evaluating and Comparing the Potentials in Primary Response for GPU and CPU Data Centers

Evaluating and Comparing the Potentials in Primary Response ...

引用

IEEE General Meeting Power& Energy Society

作者： Yihong Zhou Ángel Paredes Chaimaa Essayeh Thomas Morstyn University of Edinburgh U.K. University of Málaga Spain University of Oxford U.K.

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

The rapid growth of Large Language Models (LLMs) and Artificial Intelligence (AI) has transformed traditional CPU-centric Data Centers (DaCe) into more power-demanding GPU DaCes. Previous work has explored methods to reduce energy costs and carbon emissions in GPU DaCes. However, there remains a gap in understanding the potential of GPU DaCes for providing primary response, a crucial ancillary service for stabilizing the power system. Drawing on real-world job traces from a GPU-intensive DaCe operated by SenseTime and a CPU-intensive DaCe at Oak Ridge National Laboratory, we developed a mixed-integer linear programming model to assess the DaCe flexibility potentials considering individual jobs’ characteristics. We show that the GPU DaCe possesses a larger flexibility for delivering primary responses compared to the CPU DaCe. Furthermore, the GPU DaCe exhibits lower variability in flexibility across different times of the day and over a 7-month evaluation horizon, making them more dependable and stable sources for offering primary response.

关键词： Data centers Costs Large language models Graphics processing units Carbon dioxide Power system stability mixed integer linear programming

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An efficient parallel single surrogate objective optimization method for multi-objective black-box problem and its application in processor design

An efficient parallel single surrogate objective optimizatio...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： Xiaoliang Lv Qiaozhu Zhai Yuhang Zhu Jianchen Hu Yuzhou Zhou Xiaohong Guan Systems Engineering Institute MOE KLINNS Lab Xi’an Jiaotong University Xi’an China Center for Intelligent and Networked Systems and TNLIST Tsinghua University Beijing China

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

As micro-architectures evolve with increasing complexity, the design process needs to account for a broad range of parameters, which leads to expansive design spaces. Design space exploration (DSE) for multiple metrics with limited simulation resources is a challenging task. In this paper, we focus on multi-objective (performance and area of processor) optimization, where one of the objectives (performance) is infeasible to model analytically and the other (area) is easy to model analytically. Most of the current black-box optimization methods are data-driven, which means that they require a large amount of simulation data to model the optimization metrics for high-dimensional and discrete problems. Based on the mixed integer linear programming (MILP), the Surrogate Objective-based Parallel Multi-objective Optimization Algorithm (SOP-MOOA) is proposed to reduce the data requirements by integrating mechanism constraints and human experience. The proposed method adopts the separability assumption to establish a surrogate objective function that is ordinal consistent with the real black-box objective for paralleling a single objective model. The white box objective is modeled as a series of arithmetic constraints, thus transforming the multi-objective optimization problem into a series of parallel single-objective optimization problems. The Pareto-optimal set is explored by iteratively constructing a series of parallel single-objective black-box optimization problems. The experimental results show that the proposed algorithm outperforms HEBO, a state-of-the-art Bayesian optimization (BO) method, combined with NSGA-II in terms of the quality of the Pareto-optimal set and the recommended points.

关键词： Measurement Analytical models Computer aided software engineering Closed box Optimization methods linear programming Data models Space exploration mixed integer linear programming Glass box

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Optimizing the Transportation of CO2 Via Vessels in a Milk Run Network of Three Ports

Optimizing the Transportation of CO2 Via Vessels in a Milk R...

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International Conference on Intelligent Transportation

作者： Mauro Gaggero Institute of Marine Engineering National Research Council of Italy Genoa Italy GNAMPA-INdAM Gruppo Nazionale per l'Analisi Matematica la Probabilità e le loro Applicazioni - Istituto Nazionale di Alta Matematica

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

The optimization of the transportation of CO 2 through ships in a carbon capture and storage context is investigated by means of mixed-integer linear programming and a greedy heuristic approach. The goal is to schedule the berthing and departure times along with the optimal load of vessels carrying CO 2 among three different maritime ports, by pursuing the minimization of the usage of temporary storage buffers available at the ports. Since solving the MILP problem can be computationally intensive, a greedy heuristic algorithm based on a threshold mechanism is introduced. This heuristic, with its lower computational requirements, can provide an initial solution to the MILP-based approach, thereby enhancing its performance. Simulation results are presented in two case studies to evaluate the effectiveness of the methods.

关键词： Schedules Dairy products Simulation Heuristic algorithms Seaports Parallel machines Minimization mixed integer linear programming Marine vehicles Optimization

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Optimization of Car Flow Management within the Collection System of Heavy-Haul Railway System

Optimization of Car Flow Management within the Collection Sy...

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International Conference on Intelligent Transportation

作者： Zhian Qiu Hongwei Wang Xin Yang Pengfei Ning Yang Li Xi Wang School of Traffic and Transportation Beijing Jiaotong University Beijing China School of Automation and Intelligence Beijing Jiaotong University Beijing China State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Heavy-haul railways play a crucial role in transporting large volumes of bulk cargo, particularly coal. The optimization of car flow management within the collection system is pivotal, given that substantial time is spent by both loaded and empty trains in marshaling stations. This optimization can significantly enhance the transport efficiency of heavy-haul railways. In this paper, we propose a mixed-integer linear programming model to minimize the total time spent by loaded trains at marshaling stations and the time taken by empty trains to load and return to the marshaling station. To enhance the model's computational efficiency, we designed two valid inequalities (VI). To evaluate the effectiveness of our proposed model, we construct test cases using real-world data from the Daqin railway and the Hudong marshaling station and various numerical experiments are constructed. The computational analysis reveals that our model can reduce the objective function value by up to 4.7% of X4a2 test case and an average of 2.7% in all test case compared to traditional empirical methods. Furthermore, the VI results in a maximum reduction of 1400 seconds in computation time, showcasing the practical benefits of our approach. These findings highlight the potential of our methodology to significantly reduce the dwell time of heavy-haul trains at collection system, and than improve the operational efficiency of heavy-haul railways.

关键词： Computational modeling Transportation Rail transportation Numerical models Computational efficiency mixed integer linear programming Automobiles Optimization Load modeling Testing

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A Coverage Path Planning Method Based on Multiple Solar Powered Unmanned Aerial Vehicles

A Coverage Path Planning Method Based on Multiple Solar Powe...

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International Conference on Unmanned Systems and Artificial Intelligence

作者： Nannan Du Zichao Zhang Jian Chen Xuzan Liu Kai Zhang Ben Ma College of Engineering China Agricultural University Beijing Key Laboratory of Optimized Design for Modern Agricultural Equipment Beijing China

ISBN: (数字)9781728158594

ISBN: (纸本)9781728158600

This paper proposes a solution to solve the coverage path planning (CPP) problem of multi-solar unmanned aerial vehicles (UAVs), and the research content of this paper is as follows. First, the energy production model and consumption model of the solar UAV are established, and according to this model, the flying speed of the solar UAV are determined. Besides, the energy flow efficiency is defined to evaluate the energy utilization efficiency of this operation. After that, transform the CPP problem into vehicle routing problem (VRP), and a mixed integer linear programming (MILP) model is established to determine the flight path of each UAV with the objective of minimizing operation time. In this method, the solar UAV is used for CPP, which solves the problem of short flight time of traditional UAV. Operation time is used as the objective function to solve the CPP, so that the task can be completed as soon as possible. And the calculation of energy flow efficiency can be used to evaluate the operation efficiency of solar UAV.

关键词： solar powered UAV coverage path planning energy production model energy consumption model mixed integer linear programming Unmanned Aerial Vehicle mixed integer linear programming drone honey bees Path planning Energy flow energy exchange CPP gene energy utilization efficiency TIME OF FLIGHT operating efficiency FLIGHT PATHS operation time energy consumption solar powered

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Bullwhip effect metrics for multi-echelon systems under order batching policies with cyclic demand

Bullwhip effect metrics for multi-echelon systems under orde...

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International Conference on Industrial Engineering and Systems Management

作者： Joaquim Jorge Vicente Susana Relvas Ana Paula Barbosa-Póvoa Centre for Manage. Studies Univ. de Lisboa Lisbon Portugal

ISBN: (纸本)9781467383400

This paper analyzes how order batching policies impact on the bullwhip effect over a multi-echelon distribution supply chain facing cyclic demand. As a demand cycle is repeated over the time planning horizon, a wrapping around operator is considered and based on this a single cycle is required to represent the real problem. The problem consists on determining the optimal reordering plan, which minimizes the overall system operational costs while investigating which bullwhip measures are more adequate to control such type of systems. A mixed integer linear programming model is developed, which considers a multi-echelon inventory/distribution system formed by N-warehouses and M-retailers with lateral transshipments among warehouses and among retailers. A case study based on a real retailer distribution chain are presented and solved.

关键词： bullwhip effect inventory planning mixed integer linear programming order batching supply chain management wrap-around Policies WAREHOUSE mixed integer linear programming Supply chain management

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Energy Storage Sizing Taking into Account Forecast Uncertainties in Distributed Energy Management System

Energy Storage Sizing Taking into Account Forecast Uncertain...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Yue Li Xiaoyu Tang Shuzheng Wang Qinmin Yang the Collaborative Innovation Center for Intelligent Technology and Equipment in Distribution Network the State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang University

The rapid development of eco-friendly technologies such as energy storage system（ESS） and smart grid will shape the power consumption pattern in the *** paper proposes an analytical method to determine the battery capacity of ESS based on economic analysis,optimal scheduling strategy and forecast uncertainties in distributed energy management system（DEMS）.Firstly,an improved support vector regression（SVR） model is developed to raise the accuracy of load ***,an effective algorithm combining ergodic theory and two-stage optimization is presented to divide the battery of ESS into schedule-based capacity and emergency capacity for different *** historical load and forecast uncertainties are taken into consideration in determining the *** mixed integer linear programming（MILP） models considering the reliability constraints and peak-shaving requirement are utilized to describe the process in each *** simulations show the effectiveness of the scheme.

关键词： Energy storage system optimal sizing support vector regression two-stage optimization mixed integer linear programming

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Optimal Branch Exchange for Feeder Reconfiguration in Distribution Networks

Optimal Branch Exchange for Feeder Reconfiguration in Distri...

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IEEE Annual Conference on Decision and Control

作者： Qiuyu Peng Steven H. Low Electrical Engineering Department California Institute of Technology Pasadena CA 91125 USA Computing and Mathematical Sciences and the Electrical Engineering Departments California Institute of Technology Pasadena CA 91125 USA

ISBN: (纸本)9781467357159

The feeder reconfiguration problem chooses the on/off status of the switches in a distribution network in order to minimize a certain cost such as power loss. It is a mixed integer nonlinear program and hence hard to solve. A popular heuristic search consists of repeated application of branch exchange, where some loads are transferred from one feeder to another feeder while maintaining the radial structure of the network, until no load transfer can further reduce the cost. Optimizing each branch exchange step is itself a mixed integer nonlinear program. In this paper we propose an efficient algorithm for optimizing a branch exchange step. It uses an AC power flow model and is based on the recently developed convex relaxation of optimal power flow. We provide a bound on the gap between the optimal cost and that of our solution. We prove that our algorithm is optimal when the voltage magnitudes are the same at all buses. We illustrate the effectiveness of our algorithm through the simulation of real-world distribution feeders.

关键词： branch exchange Power grids voltage magnitude Reconfiguration mixed integer linear programming Nonlinear programming optimal load flow Load transfer power loss efficient algorithm

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Under-relaxed iterative procedure for feasible short-term scheduling of a hydro chain

Under-relaxed iterative procedure for feasible short-term sc...

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Power Tech Conference

作者： J. Garcia-Gonzalez E. Parrilla J. Barquin J. Alonso A. Saiz-Chicharro A. Gonzalez Instituto de Investigación Tcmoiógica (IIT) Universidad. Pontifica·Comillas de. Madrid Madrid CP SPAIN Instituto de Investigacidn Teololdgica Universidad Politecnica de Madrid Madrid Spain ENDESA Madrid CP SPAIN

This paper presents a method for short-term hydro scheduling. The objective is to determine a feasible operation of a set of coupled hydro units, fulfilling the aggregate requirements obtained from a higher-level hydrothermal coordination tool. In order to take into account the nonlinear relationship among the electrical power, the net head and the turbine water discharge, an under-relaxed iterative procedure is proposed. The performance of this algorithm enhances previous research works as possible diverging oscillations are damped in order to reach the convergence. Therefore, the net heads used to build the power/discharge curves of the head dependent units are determined using previous iterations results. This way, each stage can be solved by means of a MILP optimization problem where binary variables allow modeling the discrete hydro unit-commitment decisions. The process finishes when the maximum gap between the reservoir levels of two consecutive iterations satisfies the convergence tolerance. A case study is also presented to show its application to a real size hydro chain.

关键词： Reservoirs Power generation Ink Convergence mixed integer linear programming Hydraulic turbines Iterative algorithms Partial discharges Costs Power demand

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