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

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Distributed Robust Optimization-Based Coordinated Day-Ahead Scheduling Method for Distribution-Microgrid Coordination

Distributed Robust Optimization-Based Coordinated Day-Ahead ...

引用

China International Electrical and Energy Conference (CIEEC)

作者： Han Zhentao Wang Qixiang Zhang Mingli Han Liu Wang Jing Yu Zongmin State Grid Liaoning Electric Power Company Limited Economic Research Institute Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China State Grid Economic and Technological Research Institute Co. Ltd. Beijing China Sichuan Energy Internet Research Institute Tsinghua University Chengdu China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Microgrids are essential for integrating new energy sources and enhancing distribution network reliability. Coordination among multiple microgrids is crucial for safe and economic operation. Coordinated dispatching requires a distributed approach considering uncertainties in new energy sources and discrete control devices. The method employs distributed robust optimization for uncertainty representation and the SDM-GS-ALM algorithm for discrete control. It approximates integer variables through convex hulls, ensuring convexity. The C&CG algorithm serves as the outer layer, embedding SDM-GS-ALM in various stages. This establishes a framework for distributed computation in coordinating distribution and microgrids. The proposed method's effectiveness is validated using the North American 5-node system with Aggregate equivalent method for line operation state consideration.

关键词： System testing Uncertainty Processor scheduling Microgrids Approximation algorithms Scheduling mixed integer linear programming

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Optimization of group AC/DC hybrid offshore electrical system for offshore wind farms

Optimization of group AC/DC hybrid offshore electrical syste...

引用

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

作者： Lingling Huang Feixiang Ying Yang Liu Shurong Wei Zhangjie Fu Shanghai University of Electric Power Shanghai China

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The exploration of offshore wind power has shown a definite trend of clustering and rapid development from the shore to the far ocean. This has created new challenges for offshore electrical system (OES) planning for offshore wind farm clusters (OWFCs) because high-voltage alternating current (HVAC) transmission is no longer the only optimal choice. The limitations of transmission capacity and distance restrict the applications of HVAC transmission systems and have led to research on AC&DC hybrid OES. Distributed offshore wind farms (OWFs) in the OWFC and nonpredetermined alternating current/direct current (AC/DC) transmission systems for OWFs demonstrate some new features. This paper presents a mixed-integer linear programming (MILP) model for the OES optimization of the OWFC. Based on a definition of a set of 0–1 decision variable matrices and the linilization of nonlinear variables with auxiliary binary decision variables, CPLEX is introduced to solve the problem. The case results show the effectiveness of the proposed methodology. Some suggestions for the AC/DC hybrid OES planning of the OWFC have also been proposed.

关键词： HVAC Optimization models Oceans Europe Wind farms Wind power generation Planning Smart grids mixed integer linear programming Optimization

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Assignment of patients within a hospital department: case of pediatric department of Hedi Chaker Sfax hospital

Assignment of patients within a hospital department: case of...

引用

International Conference on Logistics (LOGISTIQUA)

作者： Oumaima Fersi Mohamed Ali Elleuch Jihen Jlassi Elmabrouk Olid Laboratory Higher Institute of Indusrial Management of Sfax (ISGIS) University of Sfax Sfax Tunisia Olid Laboratory Faculty of Economics and Management of Sfax (FSEGS) University of Sfax Sfax Tunisia

ISBN: (数字)9798350383911

ISBN: (纸本)9798350383928

Public hospitals in Tunisia are facing significant challenges, such as patient overload and assignment issues, stemming from overcrowding and prolonged wait times. These challenges are closely linked to increased mortality, decreased satisfaction among patients and staff, and inefficient utilization of hospital resources. Patient assignment is a complex task influenced by triage procedures and the dynamic availability of personnel and material resources. This research focused on a real-life case study to address issues related to patient assignment in the emergency, pediatric, and pediatric resuscitation departments of Hedi Chaker Hospital in Sfax, Tunisia. To address these challenges, a comprehensive programming formulation was developed with the aim of maximizing patient allocation while optimizing the allocation of doctors and nurses, all while respecting procedural constraints and staff availability. This integrated approach includes methods such as the Analytic Hierarchy Process (AHP), an algorithm using the Python programming language, to optimize patient assignment, workload balancing, and overall improvement in hospital resource management.

关键词： Supply chain management Hospitals Refining Analytic hierarchy process programming mixed integer linear programming Resource management

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Research on Dispatching of Delivery System Considering Channel Curve Optimization

Research on Dispatching of Delivery System Considering Chann...

引用

Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Xiong Wu Mingkang He Yonglong Fan Lanxi Tang Minjian Cao Penglei Wang School of Electrical Engineering Xi'an Jiaotong University Xi'an China Electric Power Planning Institute Co. Ltd Beijing China China Three Gorges Corporation Wuhan China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

We consider the channel curve optimization problem and propose a delivery system scheduling model considering curve optimization. Firstly, considering factors such as channel power, stratification, and adjustment frequency, an optimization model for the delivery channel curve is proposed. Secondly, in the delivery system, taking into account the unpredictability of renewable energy generation, optimization is performed on various power sources and delivery curves. Finally, using opportunity constraints to manage the influence of renewable energy output, the distribution-robust optimization method, relying on Kullback-Leibler divergence, converts probabilistic constraints into deterministic constraints, thereby converting the problem into a mixed-integer linear programming problem that is easy to solve. Case analysis is conducted using a certain delivery system as an example, and the results indicate that the proposed delivery curve optimization model, combined with the output of the power source at the sending end and the demand for load at the receiving end, can optimize the delivery curve, validating the effectiveness of the model.

关键词： Electrical engineering Renewable energy sources Analytical models Asia Probabilistic logic Dispatching mixed integer linear programming

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Strategic Offering of a Wind Power Producer in Energy and Green Certificate Markets: a Stochastic Bilevel Approach

Strategic Offering of a Wind Power Producer in Energy and Gr...

引用

IEEE International Conference on Power and Energy Applications (ICPEA)

作者： Jie Li Xiuli Wang Xiaoxin Zhou School of Electrical Engineering Xi'an Jiaotong University Xi'an China National Key Laboratory of Power Grid Safety China Electric Power Research Institute Beijing China

ISBN: (数字)9798350356113

ISBN: (纸本)9798350356120

With the high penetration of renewable energy and the execution of renewable portfolio standards, it becomes urgent to analyze the behavior of a wind power producer (WPP) in energy and green certificate markets. To this end, we propose a strategic offering model for a WPP, aiming to analyze the impact of exercising market power on market clearing results and social welfare. Afterwards, the model is transformed into stochastic mathematical programming with equilibrium constraints (MPEC) and eventually mixed integer linear programming (MILP), which can be solved by off-the-shelf solvers. Finally, case studies are carried out on a small test system, illustrating that the market clearing price might increase compared with the perfect competition situation, and the expected profit of WPP increases at the expense of market efficiency. Besides, we analyse the impact of line congestion on the revenue of WPP.

关键词： Renewable energy sources Green products Stochastic processes Wind power generation programming Mathematical models mixed integer linear programming Standards Portfolios Mathematical programming

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Optimization Configuration of Electric Hydrogen Integrated Charging Station for New Energy Transportation with Adjustable Characteristics

Optimization Configuration of Electric Hydrogen Integrated C...

引用

Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Jiajun Yuan Wendi Zheng Zhiyuan Liu Bingtao Zhang Bochao Lv Jin Sun College of Electrical Engineering and Automation Fuzhou University Fu’zhou China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

With the development of clean energy technologies such as hydrogen energy, public transportation systems are facing a critical moment to switch to new energy transportation. Therefore, this paper takes the electric-hydrogen integrated charging station (EHICS) constructed by electrolyzer, hydrogen storage tank, cold ironing (CI), and swapping electricity compartment (SEC) as the object of research, and formulates the optimized configuration scheme. Analyze the adjustable characteristics of the SEC and CI in depth, and establish the adjustable mathematical model of battery and electric ship charging. The nonlinear function in the optimization model is linearized to establish a mixed integer linear programming model. With the goal of minimizing the comprehensive cost of the system, the proposed configuration method can effectively improve the flexibility and economy of the electric-hydrogen integrated charging station through the comparative analysis of different cases.

关键词： Costs Hydrogen storage Hydrogen Switches Charging stations Batteries mixed integer linear programming

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An Adaptive Two Stage Demand Response Control Method of Base Stations Considering the Services Reliability

An Adaptive Two Stage Demand Response Control Method of Base...

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IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS)

作者： Wangzhang Cao Hongxuan Luo Xin Jin Tingzhe Pan CSG Electric Power Research Institute Co. Ltd. Guangdong Provincial Key Laboratory of Intelligent Measurement and Advanced Metering of Power Grid Guangzhou China

ISBN: (数字)9798350374315

ISBN: (纸本)9798350374322

To address the issue of service reliability for base stations participating in demand response programs, an adaptive two stage demand response control method is proposed. In the first stage, considering the extremely harsh communication environment, the number of Active Antenna Units (AAUs) enabled by the base station and their power consumption are analyzed, and the bandwidth allocated by each mobile terminal is calculated. The energy consumption of each base station is then determined. In the second stage, to address the outage risk during demand response, a mixed integer linear programming model is established to quantify the discharging cost of energy storage, and analyze the energy storage charging and discharging strategy. Simulations are conducted to compare this method with typical traditional scenarios that do not consider service reliability, and it is verified that this method can ensure the normal operation of the base station, and greatly improve the service reliability even in the extremely harsh communication environment and the risk of power failure.

关键词： Base stations Energy consumption Simulation Bandwidth Mobile antennas Demand response mixed integer linear programming Reliability Optimization Energy storage

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Optimal Planning for Timed Partial Order Specifications

Optimal Planning for Timed Partial Order Specifications

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Kandai Watanabe Georgios Fainekos Bardh Hoxha Morteza Lahijanian Hideki Okamoto Sriram Sankaranarayanan Departments of Computer Science and Aerospace Engineering Sciences University of Colorado Boulder Boulder Colorado Toyota Motor North America Research and Development

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper addresses the challenge of planning a sequence of tasks to be performed by multiple robots while minimizing the overall completion time subject to timing and precedence constraints. Our approach uses the Timed Partial Orders (TPO) model to specify these constraints. We translate this problem into a Traveling Salesman Problem (TSP) variant with timing and precedent constraints, and we solve it as a mixed integer linear programming (MILP) problem. Our contributions include a general planning framework for TPO specifications, a MILP formulation accommodating time windows and precedent constraints, its extension to multi-robot scenarios, and a method to quantify plan robustness. We demonstrate our framework on several case studies, including an aircraft turnaround task involving three Jackal robots, highlighting the approach’s potential applicability to important real-world problems. Our benchmark results show that our MILP method outperforms state-of-the-art open-source TSP solvers OR-Tools.

关键词： Heuristic algorithms Contingency management Traveling salesman problems Robustness Planning Timing mixed integer linear programming

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Towards Sustainable Edge Computing: Efficient Task Offloading for Energy Efficiency and Latency Reduction

Towards Sustainable Edge Computing: Efficient Task Offloadin...

引用

IEEE Conference on Global Communications (GLOBECOM)

作者： Parisa Fard Moshiri Murat Simsek Burak Kantarci School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

In networks with limited resources, the concept of offloading computation to Mobile Edge Computing (MEC) has emerged as a promising research direction with the advent of new services in fifth-generation (5G) networks. However, poorly designed offloading strategies can lead to excessive energy consumption and unpredictable latency, while the number of dropped tasks significantly impacts system efficiency. This paper presents a 5G-MEC task offloading scenario aimed at minimizing computation and communication latency, energy consumption, and the rate of dropped tasks. To achieve this, we employ mixed integer non-linear programming (MINLP) and mixed integer linear programming (MILP), comparing their performance with Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). Our analysis considers the impact of the quantity of tasks and User Equipment (UE) on network parameters, distinguishing between urgent and non-urgent tasks. We ensure a zero-dropped task rate for urgent tasks. The proposed approach outperforms baseline techniques such as First Come First Serve (FCFS), Shortest Deadline First (SDF), and Urgent Tasks First (UTF) in the context of 5G-MEC task offloading. Specifically, compared to MILP, PSO, and GA, the MINLP-based approach reduces total latency by 12%, 34%, and 44%, respectively. Moreover, it decreases energy consumption by 8%, 30%, and 47% compared to MILP, PSO, and GA, respectively. The dropped task ratio is also reduced by 17%, 42%, and 65% under the MINLP-based approach compared to MILP, PSO, and GA, respectively.

关键词： Green energy Energy consumption Multi-access edge computing Quality of service programming mixed integer linear programming Resource management Particle swarm optimization Optimization Genetic algorithms

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Achieving Predictable and Scalable Load Balancing Performance in LEO Mega-Constellations

Achieving Predictable and Scalable Load Balancing Performanc...

引用

IEEE International Conference on Communications (ICC)

作者： Songshi Dou Shengyu Zhang Kwan L. Yeung The University of Hong Kong Singapore University of Technology and Design

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

With the increasing deployment scale of Low Earth Orbit (LEO) mega-constellations, more satellites are expected to become visible to users simultaneously, bringing a new opportunity to optimize the network performance by properly assigning users to satellites. In this paper, we consider LEO mega-constellations without Inter-Satellite Links (ISLs) while assuming there are enough ground relays for inter-satellite communications. To establish a path from a user terminal to the nearest ground station (which serves as a gateway to the Internet), shortest path routing is usually adopted. To focus on the problem of user-satellite assignment, as well as to make routing more scalable, we divide the routing process into two parts: assigning the user terminal to a visible satellite, and finding a path from the satellite to the nearest ground station. For simplicity, shortest path routing is assumed in the second part. Aiming at minimizing the Maximum Satellite Utilization (MSU), a mixed integer linear programming (MILP), called Optimal User-Satellite Assignment (OUSA), is formulated. Performance evaluations are conducted based on Starlink Phase I mega-constellation and AWS ground station locations. As compared with the existing solutions, we show that the average load balancing performance can be improved by up to 33.29%.

关键词： Performance evaluation Satellites Low earth orbit satellites Logic gates Routing Load management mixed integer linear programming

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