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IEEE Asia Meeting on Environment and Electrical Engineering (IEEE-AM)

作者： Nhung Nguyen Hong Quan Dang Minh Phuc Vu Minh Hanoi Univ Sci & Technol Sch Elect & Elect Engn Hanoi Vietnam

ISBN: (纸本)9798350381061

Over the past decade, Renewable Energy Sources (RES) have been rapidly developed to meet the surging demand for electricity consumption. Besides the benefits, the penetration of RES into the power grid raises multiple issues, including the intermittent nature of power output and technical requirements for grid integration. Therefore, the Virtual Power Plant (VPP) model has been implemented to address the drawbacks of RES through aggregating Distributed Energy Resources (DER). This paper applies a mixed-integer linear programming (MILP) model to optimize the VPP's operation and maximize VPP's expected profit in the day-ahead market (DAM). The optimization model is solved by GAMS and CPLEX software. This study applies the proposed model to a VPP trial system, including a Wind Power Plant (WP), a Photovoltaic Power Plant (PV), an Energy Storage System (ESS), an Electric Vehicle (EV) charging station, and residential load. WP, PV, and load uncertainties are viewed as stochastic processes and modeled by a set of scenarios. The shifting of the EV charging schedule is considered. The results show that the proposed model has practical significance.

关键词： virtual power plant day-ahead market renewable energy sources mixed-integer linear programming electric vehicles.

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Approximation Algorithm for the Maximum Interval Multi-cover Problem 1

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18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024

作者： Xu, Yuxuan Ran, Yingli Zhang, Zhao School of Mathematical Sciences Zhejiang Normal University Zhejiang Jinhua321004 China

ISBN: (数字)9789819777983

ISBN: (纸本)9789819777976

Given a set of points P on a line, a collection of intervals I along the line, and a positive integer K≤|I|, each point p∈P is associated with a covering requirement qp, the goal of the maximum interval multi-cover (MaxIMC) problem is to find a sub-collection of intervals I′⊆I with |I′|≤K to maximize the number of fully-covered points, where a point p is fully-covered by I′ if it belongs to at least qp intervals of I′. In this paper, we present a 12-approximation algorithm for the MaxIMC problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： mixed-integer linear programming

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Research on Accessibility Optimization of the Last Train of Metro Based on Minimum Cost 24

Research on Accessibility Optimization of the Last Train of ...

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24th COTA International Conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Peng, Ruicai Li, Wei Luo, Qin College of Applied Technology Shenzhen Univ. Guangdong China College of Urban Transportation and Logistics Shenzhen Technology Univ. Guangdong China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

The dynamic nightlife scene has resulted in a significant increase in late-night passengers utilizing the metro system. However, efficiently serving these passengers during their last train connections in metro while minimizing costs poses a challenging task for operators. To address this challenge, this study employs CPLEX to develop a linear mixed-integer programming model. The model aims to optimize metro network by maximizing the number of connected transfer directions while minimizing adjustments to departure time of the last trains. The results reveal that optimizing the transfer stations on weekdays has led to a remarkable 13.0% increase in the number of connectable paths within the metro network. Notably, only minor adjustments to the departure time of three lines were necessary, resulting in an ideal cost outcome. Furthermore, during special events, strategically delaying the departure time of specific routes resulted in a significant improvement of 18.0%. This outcome demonstrates the model’s excellent effectiveness in optimizing the system. © ASCE.

关键词： mixed-integer linear programming

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Optimizing Pharmaceutical Supply Chain Configuration in Primary Healthcare: A Mathematical Modeling and Decision Support Approach 13

Optimizing Pharmaceutical Supply Chain Configuration in Prim...

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13th International Workshop on Innovative Simulation for Health Care, IWISH 2024, Held at the 21st International Multidisciplinary Modeling and Simulation Multiconference, I3M 2024

作者： AlZaidan, Manal Hadid, Majed Padmanabhan, Regina Kerbache, Laoucine Division of Engineering Management and Decision Sciences College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar Primary Health Care Cooperation Doha Qatar

ISBN: (纸本)9791281988132

This research project aims to determine the optimal warehouse location allocation for medication distribution to ensure efficient and cost-effective pharmaceutical supply chain *** also aims to make significant contributions to pharmaceutical inventory management and supply chain resilience while providing a tangible and practical solution for improving patient care in public health centers in *** paper presents a mixed-integer linear programming (MILP) model for strategically allocating warehouse locations in a pharmaceutical supply chain, designed to minimize the total operational costs while satisfying regional medication *** demonstrated that a centralized warehouse in the West region, which has the highest number of health centers, offers the most cost-effective solution, indicating reduced transportation costs and improved distribution efficiency over decentralized *** optimal configuration results in significant cost savings and heightened operational efficiency, affirming the strategic advantage of aligning warehouse location with healthcare demand *** expected impacts of the project extend to both practical and scientific *** a practical perspective, the project outcomes will enhance the quality of patient care by improving accessibility to medications, reducing the burden on pharmacies, and reducing cost and efficiency. © 2024 The Authors.

关键词： mixed-integer linear programming

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A Mathematical Model for Optimization of Hospital Capacity in Response to Multiple Hazards: Case of Coquimbo and La Serena Territories in Chile 15

A Mathematical Model for Optimization of Hospital Capacity i...

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15th International Conference on Emerging Ubiquitous Systems and Pervasive Networks / 14th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, EUSPN/ICTH 2024

作者： Gatica, Gustavo Fuentes, Erick Alexander Montenengro Rojas, Felipe Aliaga, Erwin Rivera, Laura Coronado-Hernandez, Jairo R. Universdiad Andrés Bello Chile Universidad de la Costa Colombia

Socio-natural disasters pose a significant risk to healthcare systems, particularly in areas with high volcanic and seismic activity, combined with high poverty rates, reflecting vulnerable communities facing severe impacts on societal well-being and the economy. This is the case in the territories of Coquimbo and La Serena in Chile, which are constantly affected by natural phenomena, such as wildfires. Between 2020 and 2021, a total of 58 wildfires were recorded. This study presents a quantitative risk analysis of the healthcare network in response to the recurrence of wildfires in Coquimbo and La Serena cities, employing mixed-integer programming models for optimal location, relating fixed costs to the increased demand for care from the affected population. The methodology applied was quantitative, where the first phase involved identifying the areas affected by wildfires in La Serena and Coquimbo. Subsequently, we have formulated the mathematical model, including the objective function, definition of variables and parameters, definition of constraints, and finally, the implementation of the mathematical model's code. © 2024 The Authors. Published by Elsevier B.V.

关键词： mixed-integer linear programming

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Scenario-Oriented Multi-Cut Generalized Benders Decomposition-Based Distributed OPF for AC/DC Hybrid Grids

Scenario-Oriented Multi-Cut Generalized Benders Decompositio...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Li, Hai-Xiao Ergun, Hakan Van Hertem, Dirk Lekic, Aleksandra Delft University of Technology Faculty of Electrical Engineering Mathematics & Computer Science Delft Netherlands Chongqing University of Technology School of Electrical and Electronic Engineering Chongqing China Ku Leuven Department of Electrical Engineering Leuven Belgium Etch-EnergyVille Genk Belgium

ISBN: (纸本)9789531842976

In this paper, a distributed optimal power flow (OPF) for the AC/DC hybrid grid, composed of the AC grid, renewable energy system (RES), and voltage source converter (VSC)-based multi-terminal DC (MTDC) grid, is presented. Firstly, we apply a series of linear approximations/convex relaxations to construct a mixed-integer convex AC/DC OPF model. To address the uncertainties from RESs, we then illustrate scenario-oriented decision making for the constructed AC/DC OPF model. Additionally, we verify that considering all possible scenarios can be replaced by a small set of extreme scenarios if the OPF model is (mixed-integer) convex. Furthermore, we develop a scenario-oriented multi-cut generalized Benders decomposition to achieve more efficient distributed problem solving for the constructed AC/DC OPF model. Finally, numerical results are provided to validate the effectiveness of our constructed AC/DC OPF model and our developed distributed problem-solving approach. © 2024 IEEE.

关键词： mixed-integer linear programming

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Performance Comparison of Ant Colony Optimization and Symbiotic Organism Search In Smart Home Energy Management Systems 8

Performance Comparison of Ant Colony Optimization and Symbio...

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8th International Conference on Electrical, Telecommunication and Computer Engineering, ELTICOM 2024

作者： Siregar, Yulianta Pinem, Maksum Saputra, Sandy Armando Universitas Sumatera Utara Department of Electrical Engineering Medan Indonesia

ISBN: (纸本)9798331531249

Home Energy Management Systems (HEMS) technology is increasingly being adopted due to its numerous benefits. This technology aims to facilitate the automatic operation and management of household appliances. Demand-side energy management seeks to manage and optimize energy usage and reduce electricity costs. Numerous approaches to optimizing demand-side energy management in HEMS have been proposed, utilizing linear programming, mixed integer linear programming, mixed integer nonlinear programming, dynamic programming, and convex programming. However, these approaches often struggle to handle numerous variables, such as a large number of appliances or loads. The application of metaheuristic algorithms in HEMS is proposed as a solution to this issue. The algorithms proposed in this study are Ant Colony Optimization and Symbiotic Organism Search. The resulting optimal scheduling recommendations are then analyzed and compared, focusing on load shifting schedules and cost savings. The Ant Colony Optimization algorithm can reduce costs by up to 5.27%, whereas the Symbiotic Organism Search algorithm can achieve reductions of up to 24.75%. After analysis and comparison, conclusions are drawn from this research. © 2024 IEEE.

关键词： mixed-integer linear programming

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An Optimization Model for Sizing a Hybrid Photovoltaic-Wind-Grid-Connected System in Saudi Arabia

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PROCESS INTEGRATION AND OPTIMIZATION FOR SUSTAINABILITY 2022年第4期6卷 1027-1042页

作者： Ghaithan, Ahmed M. Mohammed, Awsan King Fahd Univ Petr & Minerals Construct Engn & Management Dept Dhahran 31261 Saudi Arabia King Fahd Univ Petr & Minerals Smart Mobil & Logist Ctr Dhahran 31261 Saudi Arabia

This paper proposes a new optimization model based on mixed-integer linear programming approach for sizing a solar-windgrid-connected system. The proposed hybrid system aims to supply load demand for an industrial facility in Saudi Arabia. The developed model determines the optimal number of photovoltaic modules and wind turbines, as well as the optimal hourly energy obtained from the grid and hourly excess energy produced by the system and sold to the grid. The model findings show that 77 photovoltaic modules and 7 wind turbines in addition to the grid are needed to satisfy the load demand. The system produces 450,734 kWh annually which represents 82% of the annual load consumption. Also, the system produces surplus energy of 72,752 kWh which accounts to $6,184 as an income to the industrial facility. The case study is enriched by considering off-grid photovoltaic-wind system with battery storage. The results show that incorporating battery storage increases the cost of energy of the hybrid system. However, the off-grid photovoltaic-wind system shows promising results when considering environmental issues as it will displace around of 279,800 kg of carbon dioxide per year compared to the grid-connected system that will displace around 225,768 kg of carbon dioxide per year. A sensitivity analysis was carried out to identify the effect of the electricity cost on the optimal system design and the cost of energy obtained from the hybrid system.

关键词： mixed-integer linear programming Wind energy Solar energy Optimization Saudi Arabia

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Enhancing PV Self-Consumption Within an Energy Community Using MILP-Based P2P Trading

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IEEE ACCESS 2022年 10卷 93760-93772页

作者： Al-Sorour, Ameena Fazeli, Meghdad Monfared, Mohammad Fahmy, Ashraf Searle, Justin R. Lewis, Richard P. Swansea Univ Fac Sci & Engn Dept Elect & Elect Engn Swansea SA1 8EN W Glam Wales Swansea Univ ASTUTE Swansea SA1 8EN W Glam Wales Helwan Univ Dept Elect Power & Machines Helwan 11795 Egypt Swansea Univ SPECIF IKC Swansea SA1 8EN W Glam Wales

The high penetration of Distributed Energy Resources (DERs) into the demand side has led to an increase in the number of consumers becoming prosumers. Recently, Peer-to-Peer (P2P) energy trading has gained increased popularity as it is considered an effective approach for managing DERs and offering local market solutions. This paper presents a P2P Energy Management System (EMS) that aims to reduce the absolute net energy exchange with the utility by exploiting two days-ahead energy forecast and allowing the exchange of the surplus energy among prosumers. mixed-integer linear programming (MILP) is used to schedule the day-ahead household battery energy exchange with the utility and other prosumers. The proposed system is tested using the measured data for a community of six houses located in London, UK. The proposed P2P EMS enhanced the energy independency of the community by reducing the exchanged energy with the utility. The results show that the proposed P2P EMS reduced the household operating costs by up to 18.8% when it is operated as part of the community over four months compared to operating individually. In addition, it reduced the community's total absolute net energy exchange with the utility by nearly 25.4% compared to a previous state-of-the-art energy management method.

关键词： Batteries Costs Tariffs Energy management Peer-to-peer computing Medical services State of charge linear programming Energy management system energy independence local consumption mixed-integer linear programming peer-to-peer energy trading PV-battery systems

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A System Optimal Speed Advisory Framework for a Network of Connected and Autonomous Vehicles

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第6期23卷 5727-5739页

作者： Nguyen, Cuong H. P. Hoang, Nam H. Lee, Seunghyeon Vu, Hai L. Monash Univ Monash Inst Transport Studies Dept Civil Engn Fac Engn Melbourne Vic 3800 Australia Univ Technol Sydney Fac Engn & Informat Technol Ultimo NSW 2007 Australia

The technological advancements involving information and communication technologies (ICT), such as Connected and Automated Vehicles (CAVs) and the Intelligent Transport Systems (ITS), have enabled new efficient traffic control and management strategies to mitigate traffic congestion. Specifically, the combined traffic flow-speed advisory systems based on CAVs and ITS technologies could provide the individual vehicle with the optimal speed to reduce the fuel consumption, the number of stops, simultaneously reduce the network-wide traffic congestion and improve road safety. This article develops a novel bi-level control framework underpinned by the mutual interaction between a system optimal traffic flow control strategy at a network level and a speed control policy for an individual vehicle at a link level within a connected traffic environment. Our framework proposes the novel group-based method to guarantee the consistency and interaction between the macroscopic and microscopic models. To this end, it efficiently optimizes vehicular trajectories while meeting the network-wide objectives which have not been investigated previously in the literature. We propose an efficient algorithm for this problem that iteratively solves mixed-integer linear programming (MILP) models for each upper and lower level. Numerical results indicate the effectiveness of the proposed speed advisory method in vehicular emission reduction, favorable network queue formation, and its positive influence on traffic flow patterns over the network.

关键词： Biological system modeling Vehicle dynamics Trajectory Optimization Fuels Safety Heuristic algorithms mixed-integer linear programming dynamic traffic assignment optimal speed advisory bi-level control strategy car following model lane-changing model connected and autonomous vehicles

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