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Reliability Assessment of Distribution Systems Considering the Effects of Cyber Failures

Reliability Assessment of Distribution Systems Considering t...

引用

Intelligent Power and Systems (ICIPS), International Conference on

作者： Xuan Fang Wenrui Zhou Jiahao Liang Juntao Li Siguang Zheng Bohuai Yan Guangzhou Bureau of China Southern Power Grid EHV Transmission Company Guangzhou China College of Electrical Engineering & New Energy China Three Gorges University Yichang China The School of Electrical and Information Engineering Tianjin University China College of Science Hongkong Baptist University Hongkong China

ISBN: (数字)9798331532765

ISBN: (纸本)9798331532772

The traditional reliability assessment methods for cyber-physical distribution systems suffer from low computational efficiency and accuracy, as well as insufficient consideration of cyber systems. This article deeply analyzes the impact of cyber systems failures on the reliability of distribution networks, and uses optimization methods to solve the reliability of distribution systems. The reliability assessment method proposed in this article has the advantage of precise evaluation.

关键词： Accuracy Optimization models Distribution networks Planning mixed integer linear programming Computational efficiency Reliability Information systems

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The Vehicle Routing Problem with Drones and Flexibility Demands

The Vehicle Routing Problem with Drones and Flexibility Dema...

引用

Congress on Evolutionary Computation

作者： Tran Thi Hue Bao Nguyen Quoc Nguyen Pham Phu Manh Nguyen Khanh Phuong Huynh Thi Thanh Binh Dang Quang Thang Hanoi University of Science and Technology Hanoi Vietnam Banking Academy of Vietnam

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

In recent years, the Vehicle Routing Problem, with its variants handling complex realistic constraints, continues to be a key area of research, reflecting its enduring importance in modernized societies. Nevertheless, less attention has been paid to the variant with the flexibility of customer demands. This paper introduces the problem of addressing the integration of drones into the existing transportation system to maximize the profit of distributing freight during a limited working time by allowing flexibility in the delivered quantity. We propose a mixed integer linear programming (MILP) formulation and a genetic algorithm (GA) to solve the problem. To assess the proposed algorithm, we create the benchmark instances of the problem from published data sources. Experimental results on the instances show a significantly better performance of our proposal than MILP. Moreover, we evaluate our approach by comparing its performance with existing solutions in published closely related works.

关键词： Power demand Soft sensors Vehicle routing Transportation Benchmark testing mixed integer linear programming Proposals

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A Multi-Objective Train Timetable Rescheduling Model During the Transitional Period

A Multi-Objective Train Timetable Rescheduling Model During ...

引用

International Conference on Intelligent Transportation

作者： Hao Peng Shiqi Zhang Shuai Su Du Shang Zhikai Wang State Key Laboratory of Advanced Rail Autonomous Operation Frontiers Science Center for Smart High-speed Railway System Beijing Jiaotong University Beijing P. R. China Beijing Mass Transit Railway Operation Co. Ltd.

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

In a metro system, train delays cause inconvenience to passengers and render the scheduled timetable infeasible. This paper addresses the problem of train timetable rescheduling and rolling stock circulation planning, with a particular focus on train delays occurring during the transitional period from peak to off-peak hours. Considering both operating costs and passenger service quality, this paper proposes a multi-objective optimization model to minimize the number of stranded passengers at platforms, train delays, and train service cancellations. Additionally, a strategy of adding temporary train services is considered to accommodate the change in passenger flow. Further, some linearization methods are used to transform this model into a mixed integer linear programming (MILP) problem, which can be effectively solved using the CPLEX optimizer. Finally, computational experiments are conducted using realistic case studies based on the Beijing Yizhuang line, incorporating scenarios with randomly induced delays. The experimental results show that the proposed rescheduling method in this study can reduce the number of stranded passengers due to train delays during the transitional period, and a feasible solution can be found in a short time.

关键词： Costs Computational modeling Optimization models Transforms Delays Planning mixed integer linear programming Computational efficiency Artificial intelligence Intelligent transportation systems

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Advancing Multi-Energy Hub Design: an Integrated Approach for Optimizing Residential Clusters in High RES Penetration Scenarios

Advancing Multi-Energy Hub Design: an Integrated Approach fo...

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International Conference on Smart Energy Systems and Technologies (SEST)

作者： Marialaura Di Somma Lingkang Jin Nicola Bianco Christina Papadimitriou Department of Industrial Engineering University of Naples Federico II Naples Italy Electrical Engineering Department Eindhoven University of Technology Eindhoven Netherlands

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

With the energy transition underway, the wider penetration of multi-energy hubs (MEHs) is inevitable as they allow for the integration of multiple energy carriers at the local level and especially at the users' side by enhancing flexibility of energy supply and renewabIes penetration. Thus, addressing their design properly is imperative. While numerous energy modeling software and tools are extensively discussed in the literature, they primarily focus on a single energy carrier, mainly dedicated to the electrical network. In this study, an optimization planning tool capable of analyzing the synergies of various energy carriers is presented. The tool aims to determine the optimal configuration of MEHs with sizes of the chosen technologies based on the modeler's preferences. The tool offers flexibility in modelling a wide range of technologies as potential options for the optimal configuration, and in considering different types of objectives as economic and environmental ones that can be assessed through a multi-objective approach. It is formulated through mixed-integer linear programming in a modular manner, facilitating the easy implementation of new emerging technologies, by enhancing scalability and applicability in real context. To prove the effectiveness of the optimization tool, it is applied for the design of a MEH for a residential building cluster located in Torino (Italy). Different scenarios are analyzed to determine the impact of high levels of renewabIes penetration on the design of the MEH while guaranteeing the economic sustainability of the solution.

关键词： Economics Scalability Biological system modeling Buildings linear programming Software Planning mixed integer linear programming Sustainable development Optimization

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Optimization of Port Integrated Energy Systems Considering the Dissatisfaction of Port Operators with Hydrogen Safety

Optimization of Port Integrated Energy Systems Considering t...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Kai Ma Yingye Zhang Kun Yang Shiliang Guo Yong Yang Jie Yang School of Electrical Engineering Yanshan University Qinhuangdao China School of Civil Engineering and Mechanics Yanshan University Qinhuangdao China State Grid Handan Electric Power Supply Company Handan China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

Hydrogen energy, as a clean energy source, is increasingly being applied to port operations. However, previous studies on hydrogen energy applications have largely overlooked the impact of hydrogen energy safety on system design. This paper introduces prospect theory in the context of hydrogen-containing ports and proposes a safety dissatisfaction model for port operators based on this theory, which innovatively incorporates their considerations of hydrogen energy safety into the analytical framework. An optimization model of port integrated energy system based on hydrogen safety is developed and formulated as a mixed-integer linear programming problem. The optimization model effectively reduces the operation cost and operator dissatisfaction level of the port through the simulation of a large port example, which validates the effectiveness of the proposed model.

关键词： Green energy Costs Optimization models Hydrogen System integration Safety mixed integer linear programming Optimization System analysis and design Energy storage

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Aggregated Energy Management of Multiple Factories that Purchased Green Energy Collectively

Aggregated Energy Management of Multiple Factories that Purc...

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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Leehter Yao Cheng-Yu Ku J. C. Teo Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan

ISBN: (数字)9798350355185

ISBN: (纸本)9798350355192

This paper proposes an aggregated energy management of multiple factories that purchased green energy collectively. These factories purchase green energy collectively to get a better price. The green energy is procured for each time step throughout the consumption day in a day ahead manner. On the consumption day, the green energy provider feeds green energy into the power grid at each time step, following the quantities that were purchased for those specific time intervals. The aggregated energy management system optimally dispatches the electrical power of the factories in an aggregated manner based on the purchased green energy profiles to maximize the consumption of the purchased green energy. A mixed integer linear programming (MILP) formulation is developed to carry out the aggregated energy management. To overcome the high computation time associated with conventional MILP, a linear programming relaxation technique is employed. This technique relaxes the binary variables, allowing them to take any value between 0 and 1, which enables the optimization problem to be solved in a very short time. After solving the optimization problem, the values of the variables are corrected back to binary values using a delicate method to ensure the feasibility of the solution.

关键词： Green energy Processor scheduling Electricity Simulation linear programming Production facilities Real-time systems Power grids mixed integer linear programming Optimization

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A novel optimization model for apparel closed-loop supply chain planning

A novel optimization model for apparel closed-loop supply ch...

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Logistics and Industrial Engineering (ICLIE), International Conference on

作者： Quang Nhat Pham Tran Hong Phuong Pham Thi Yen Vi Ngo Duc Duy Nguyen Department of Industrial Systems Engineering Ho Chi Minh City University of Technology (HCMUT) Ho Chi Minh City Vietnam Vietnam National University Ho Chi Minh City Thu Duc City Ho Chi Minh City Vietnam

ISBN: (数字)9798331510695

ISBN: (纸本)9798331510701

Closed-loop supply chains play an essential role in the apparel industry, recognized as one of the most environmentally polluting sectors globally due to its intricate supply chain and the use of chemicals in production. Optimizing these supply chain networks is crucial for companies to enhance competitiveness and sustainability. Therefore, this study introduces a mixed-integer linear programming approach to formulate a Closed-Loop Supply Chain (CLSC) in the apparel industry, aiming to optimize total costs while addressing environmental concerns and promoting efficient resource utilization. The model’s effectiveness and feasibility are validated through the 6 datasets from small to large scales. The datasets generated by normal distribution with different sample sizes are based on a practical dataset of a case study in the apparel industry in Vietnam, one of the world’s largest exporters of textiles. The proposed CLSC model emerges as a practical tool for policymakers and businesses seeking to embrace sustainable practices within the apparel industry.

关键词： Industries Optimization models Supply chains Production mixed integer linear programming Planning Resource management Sustainable development Textile industry Textiles

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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...

引用

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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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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