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检索条件"任意字段=21st Conference on System Modeling and Optimization"

共 3611 条记录，以下是11-20 订阅

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IRNet: INVANETs Performance Prediction Via Spatio-Temporal Graph Attention Networks 21

IRNet: INVANETs Performance Prediction Via Spatio-Temporal G...

引用

21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Zhang, Tengwen Luo, Tao Huang, Shaoyuan Li, Yuting Wang, Xiaofei Tianjin Univ Coll Intelligence & Comp Tianjin Peoples R China

ISBN: (纸本)9798350363999;9798350364002

Intelligent Vehicular Ad-hoc Networks (INVANETs) optimize road travel in Intelligent Transportation systems (ITS), exploiting smart technologies to enhance safety, efficiency, and reduce congestion. Network modeling, as a fundamental tool in network analysis and optimization, is critical to the ongoing enhancement of INVANETs. However, affordable models that can accurately capture topological dependence among network performances in INVANETs and adapt to their dynamics are currently lacking. This paper proposes the INVANETs Routing modeling Network (IRNet). The IRNet is based on an elaborate Spatio-Temporal Graph Attention Networks (stGAT) to capture the intricate relationships between topology, network states, and Key Performance Indicators (KPIs), e.g., delay, jitter, and drops. IRNet first constructs models for per-packet delay and drops mathematical distributions, then calculates these KPIs for source-destination pairs, and derives global network indicators. It adapts to INVANETs' dynamic topologies using snapshots. Furthermore, IRNet generalizes well across different topologies, routing schemes, and traffic conditions. Evaluations reveal IRNet's superior prediction accuracy, outperforming baseline models with a 17.64% improvement in average-case MRE, highlighting its effectiveness. Use cases are also involved to illustrate IRNet's optimization impact on INVANETs.

关键词： Intelligent Vehicular Ad-hoc Networks Spatio-Temporal Graph Attention Network network modeling network optimization

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Robust Optimal Power Flow for Distuibution Network Based on Holomorphic Embedding Method 21

Robust Optimal Power Flow for Distuibution Network Based on ...

引用

21st International conference on Harmonics and Quality of Power

作者： Chen, Jingteng Huang, Jiaming State Grid Putian Elect Power Co Ltd Putian Peoples R China

ISBN: (纸本)9798350382570;9798350382563

This paper proposes a more robust optimal power flow algorithm (ROPF) to address the issue of optimal power flow solutions being more likely to be attracted to inoperable solutions in new power systems. Firstly, the holomorphic embedding power flow algorithm (HEM) and particle swarm optimization algorithm (PSO) are decoupled and reconstructed within the algorithm to achieve cross solving of the distribution network OPF problem. Secondly, based on the consideration of voltage quality and economic operation in the distribution network, a multi-objective optimization model was established with the system loss and voltage deviation rate as objective functions, and the flexible resource operation status of the distribution network as decision variables;Finally, using the ROPF to conduct simulation experiments on IEEE-33 system and compare the results with the OPF algorithm based on the NR method. The results indicate the ROPF has better robustness and practicality.

关键词： Optimal Power Flow Holomorphic embedding method particle swarm optimization robustness Independent of initial value

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A MBSE Framework for the Design and Analysis of Complex Automotive systems Using SysML and PCE 21

A MBSE Framework for the Design and Analysis of Complex Auto...

引用

21st International conference on Software Architecture (ICSA)

作者： Kaloor, Tirtha Barosan, Ion Eindhoven Univ Technol Eindhoven Netherlands

ISBN: (纸本)9798350366266;9798350366259

The development of automotive systems has become more complex due to the growing demand for sophisticated features, the necessity for smooth integration of technology, and faster production schedules, leading to numerous challenges in their development. To tackle some of these challenges, this paper introduces a practical method designed to simplify the early design and assessment stages of complex automotive systems through the use of sophisticated systems engineering methodologies. It details the combination of systems modeling Language (SysML) and IBM Rational Rhapsody's Parametric Constraint Evaluator (PCE) within an improved Model-Based systems Engineering (MBSE) framework aimed at the development of complex systems. This fusion enables the virtual evaluation of parametric constraints and the analysis of engineering performance for different system configurations, thus enhancing the process of engineering analysis. We demonstrate the practicality and effectiveness of this approach using a generic automotive powertrain case study. This involves modeling a system based on specific requirements and evaluating its performance across predetermined configurations. Furthermore, the versatility of the MBSE framework is highlighted, showing its applicability beyond the automotive industry to encompass a wide range of engineering domains. This study aims to pave the way for more efficient and manageable development processes in the face of growing system complexity.

关键词： Model-Based systems Engineering Complex system modeling SysML PCE Parametric Evaluation Automotive

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Hybrid Energy storage Energy Management Collaborative optimization Method for Improving Power Quality in Ship Power Grids 21

Hybrid Energy Storage Energy Management Collaborative Optimi...

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21st International conference on Harmonics and Quality of Power

作者： Duan, Quanzheng Yang, Xiangguo Wang, Yufan Zhou, Chaobin Tang, Telu Ke, Shuiqing Wuhan Univ Technol Sch Naval Architecture Ocean & Energy Power Engn Wuhan Peoples R China

ISBN: (纸本)9798350382570;9798350382563

Aiming at the challenge that the traditional single energy storage scheme can hardly meet the power quality demand under complex working conditions, this paper proposes a multi-objective co-optimization technique grounded in the non- dominated sorting genetic algorithm (NSGA-II) for hybrid energy storage in ship DC integrated power systems. In this paper, second-order filtering is adopted as the approach for handling energy administration. Next, developing a collaborative optimization framework that takes into account the interrelated aspects of capacity distribution and energy management tactics. Besides, the optimal filter coefficients and optimal energy storage capacity are solved by NSGA-II. Ultimately, the proposed method was evaluated through a simulation model, and the findings indicated that it not only curbs power fluctuations more effectively, but also enhances the quality of the ship's electrical grid, diminishes the DC bus voltage variations, and ensures that the system's investment costs are kept to a minimum.

关键词： co-optimization method hybrid energy storage system (HESS) power quality Second-order filtering

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Harmonic Suppression Model Based on Economic optimization 21

Harmonic Suppression Model Based on Economic Optimization

引用

21st International conference on Harmonics and Quality of Power

作者： Wei, Yongxin Ma, Xing Chen, Yongtao Zhang, Shuyuan State Grid Chongqing Elect Power Res Inst Chongqing Peoples R China Sichuan Univ Coll Elect Engn Chengdu Peoples R China

ISBN: (纸本)9798350382570;9798350382563

There are significant harmonics in distribution network, which can affect the operation of power equipment, increase losses, interfere with communications, reduce product quality, and even cause safety accidents, and effective suppression of which is of great significance to ensure system stability. In this paper, a model for harmonic suppression based on economic optimization is proposed to optimize the harmonic suppression cost to the minimum while satisfying constraints such as all nodes in distribution network have lower than standard total harmonic voltage distortion. Simulation results demonstrate that the proposed model can realize all nodes harmonics not exceeding the standard in different cases and can greatly reduce the cost of harmonic suppression compared to APF. This proves that the model can well solve the technical and economic problems of harmonic suppression, and lays the foundation for practical application.

关键词： Distribution network optimization model constraint APF harmonic suppression costs

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Fusion of strategic Queueing Theory and AI for Smart City Telecommunication system 21

Fusion of Strategic Queueing Theory and AI for Smart City Te...

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21st IEEE International conference on Mobile Ad-Hoc and Smart systems (MASS)

作者： Zin, Thi Thi Moe, Aung Si Thu Phyo, Cho Nilar Tin, Pyke Univ Miyazaki Grad Sch Engn Miyazaki Japan

ISBN: (纸本)9798350363999;9798350364002

This paper explores the innovative intersection of queueing theory and artificial intelligence (AI), addressing emerging challenges for Smart City Telecommunication system. We propose a novel approach that integrates queueing theory with AI methodologies, particularly artificial neural networks (ANNs), to optimize strategic parameters in Markov Decision Process (MDP) problems in communication systems. These parameters include server numbers, customer waiting times, queue lengths, and other critical metrics. Our fusion approach demonstrates high efficacy and indicates significant advancements in applying machine learning to complex queueing theory issues. The study underscores the practical applications of this integration across various domains. We provide real-world examples illustrating the strategic use of AI-enhanced queueing models in improving user experiences and optimizing system efficiencies. Our discussions cover the benefits of intelligent resource allocation, dynamic load balancing, and adaptive service time optimization. We extend our exploration through specific case studies demonstrating the efficacy of this integration in industries such as telecommunications, healthcare, and transportation. For instance, in telecommunications, AI-driven queue management systems can dynamically allocate bandwidth to ensure optimal service quality. In healthcare, queueing models enhanced by AI can improve patient flow and reduce wait times, potentially leading to better healthcare outcomes. In this paper, we investigate the application of deep learning models to queueing theory, specifically focusing on [mention specific problem or application, e.g., "forecasting queue lengths in real-time systems"]. We implement and evaluate several deep learning architectures to determine their effectiveness in modeling and predicting queue dynamics. The paper concludes by emphasizing the necessity for continued interdisciplinary research, encouraging collaboration between AI expert

关键词： smart city queueing management artificial intelligence artificial neural networks service time optimization complex queueing problems in smart telecommunication Markov decision process dynamic optimization

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Hydrogen powered microgrid for EV charging stations load flow analysis and optimization 21

Hydrogen powered microgrid for EV charging stations load flo...

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21st International Learning and Technology conference, L and T 2024

作者： Alammari, Eithar Alamro, Joud Alashwali, Sara Hassan, Rana Muthanna, Lina Barkat, Enfel Effat University Dept. of Electrical & Computer Engineering Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

This paper presents an exhaustive analysis of power flow optimization within an IEEE 33-bus microgrid system using Particle Swarm optimization (PSO) and compares it with traditional Optimal Power Flow (OPF) methods. The PSO approach is evaluated based on its effectiveness in reducing real and reactive power losses and enhancing overall system efficiency, particularly when integrated with renewable energy sources. Our study delves into the intricacies of power system optimization, examining the system's adaptability to load variations and the integration of distributed generation. The performance metrics focus on energy conservation, operational cost, system reliability, and power quality. The results from the PSO are critically assessed against those obtained from the OPF, providing insights into the suitability and effectiveness of each optimization method for modern smart grid applications. © 2024 IEEE.

关键词： Reactive power

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Sensitivity Analysis of Distribution system Harmonic Impedance and Impact on Transmission system 21

Sensitivity Analysis of Distribution System Harmonic Impedan...

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21st International conference on Harmonics and Quality of Power

作者： Todeschini, Grazia Scholtz, stephan Blanco, Ana-Maria Domagk, Max Meyer, Jan Olasunkanmi, Omowumi Grace Kings Coll London London England TUD Dresden Univ Technol Dresden Germany Swansea Univ Swansea W Glam Wales

ISBN: (纸本)9798350382570;9798350382563

A recent collaboration between the TUD Dresden University of Technology and King's College London explored the challenges associated with modeling the harmonic impedance of distribution systems and assessing its effects at higher voltage levels. Two network models, incorporating both transmission and distribution system representations, were utilized. For each model, different parameters were considered for sensitivity studies, and the harmonic impedance at the transmission level was computed for each scenario. The findings indicate that some of the parameters result in notable effects only locally, while others impact impedance at the transmission system buses. Common parameters that affect both networks are identified, and future work is outlined.

关键词： Power Quality Frequency Dependent Impedance Sensitivity Analysis Modelling

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Multi-level optimization Based on Approximate Models for Double-Sided Linear Flux Switching Permanent Magnet Motors 21

Multi-level Optimization Based on Approximate Models for Dou...

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IEEE 21st Biennial conference on Electromagnetic Field Computation (IEEE CEFC)

作者： Zhao, Qiankai Wen, Cheng Huang, Lei Li, Yuan Southeast Univ Sch Elect Engn Nanjing Peoples R China Shijiazhuang Tiedao Univ Sch Elect & Elect Engn Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9798350348958;9798350348965

In this paper, a novel multi-level optimization method for DLFSPM is proposed, to improve the efficiency of multi-objective optimization. To split the high dimension parameters space, a combination of comprehensive sensitivity analysis, correlation analysis, and cross-factor variance analysis is employed to evaluate the effect of the machine's structure parameters towards the optimization objective. Moreover, an approximate model for this machine based on BOHB-RF and a least squares method of approximation is applied to reduce the computational complexity for motor modeling. Then, Nondominated sorting genetic algorithm-II (NSGA-.) is applied to optimize the DLFSPM with a level-by-level multi-objective optimization design, that to obtain the global optimal performance of this motor with high thrust density, low thrust ripple and low mover loss. Finally, the results of FEA prove the effectiveness for the multi-level optimization method.

关键词： linear motor multi-level optimization multi-objective optimization approximation model NSGA-II

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A Graphical modeling Language for Artificial Intelligence Applications in Automation systems 21

A Graphical Modeling Language for Artificial Intelligence Ap...

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IEEE 21st International conference on Industrial Informatics (INDIN)

作者： Schieseck, Marvin Topalis, Philip Fay, Alexander Helmut Schmidt Univ Inst Automat Technol Hamburg Germany

ISBN: (纸本)9781665493130

Artificial Intelligence (AI) applications in automation systems are usually distributed systems whose development and integration involve several experts. Each expert uses its own domain-specific modeling language and tools to model the system elements. An interdisciplinary graphical modeling language that enables the modeling of an AI application as an overall system comprehensible to all disciplines does not yet exist. As a result, there is often a lack of interdisciplinary system understanding, leading to increased development, integration, and maintenance efforts. This paper therefore presents a graphical modeling language that enables consistent and understandable modeling of AI applications in automation systems at system level. This makes it possible to subdivide individual subareas into domain specific subsystems and thus reduce the existing efforts.

关键词： AI system modeling Graphical modeling Language Domain Specific modeling Language Cyber Physical systems

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