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Revisit power system dispatch:Concepts,models,and solutions

iEnergy 2023年第1期2卷 43-62页

作者： Zhifang Yang Pei Yong Mingxu Xiang State Key Laboratory of Power Transmission Equipment&System Security and New Technology College of Electrical EngineeringChongqing UniversityChongqing 400044China State Key Laboratory of Power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China

Power system dispatch is a general concept with a wide range of *** is a special category of optimization problems that determine the operation pattern of the power system,resulting in a huge influence on the power system security,efficiency,and *** this paper,the power system dispatch problem is revisited from the *** paper provides a categorization of the dispatch problem,especially with an emphasis on industrial ***,this paper presents a detailed review of the dispatch *** common formulations of the dispatch problem are ***,this paper discusses the solutions of the dispatch problem and lists the major challenges.

关键词： Power system dispatch optimal power flow unit commitment energy storage

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Quantum Computing Approaches to Optimize Employee Scheduling in Multi-task Call Centers 3rd

Quantum Computing Approaches to Optimize Employee Scheduling...

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3rd International Conference on Smart Manufacturing, Industrial and Logistics engineering, SMILE 2023 and the 7th Asian Conference of Management Science and Applications, ACMSA 2023

作者： Li, Cheng Liu, Zhaoyang Song, Yu Liu, Haojie Liu, Hanlin Liu, Xiaodong Comprehensive Research Organization Fukuoka Institute of Technology Fukuoka Japan Graduate School of Engineering Fukuoka Institute of Technology Fukuoka Japan Department of System Management Fukuoka Institute of Technology Fukuoka Japan

ISBN: (纸本)9789819701933

The call center industry urgently needs efficient staff scheduling due to unpredictable customer service demands and challenges in human resource coordination. Appropriate scheduling is vital to enhance operational efficiency, reduce labor costs and improve customer satisfaction. This research is aim to solve the daily multi-task staff scheduling problem by integrating the innovative capabilities of QUBO (Quadratic Unconstrained Binary Optimization) model and Quantum Computing. We formulate the intricate parameters related to the number of employees, task type, and skill proficiency using a traditional mixed-integer programming model. Specifically, the study formulates scheduling constraints and objectives and then we convert this model into a QUBO model this transformation makes the problem to be suitable for Quantum Annealing (QA) and enabling subsequent integration with QA technology. This technology enables rapid and advanced exploration of extensive solution spaces and identify the optimal or near-optimal solutions. This research offers valuable insights and substantial groundwork for future explorations and developments in optimizing call center staff scheduling problem. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Customer satisfaction

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Optimal Sizing and Placement of BESS in Distribution Grid with High PV Penetration Considering BESS Optimal Operation 11

Optimal Sizing and Placement of BESS in Distribution Grid wi...

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11th International Conference on Power and Energy systems engineering, CPESE 2024

作者： Ta-Duy, Bach Nguyen-Tuan, Anh Nguyen-Duc, Tuyen Fujita, Goro Hanoi Uni. of Science and Technology School of EEE Dept. Electrical Engineering Hanoi Viet Nam Department of Power System Department of EE Tokyo Japan

ISBN: (纸本)9798350377439

Battery Energy Storage systems (BESSs) are an effective solution in preventing overvoltage caused by the high penetration rate of renewable energy sources (RES). This paper proposes a new strategy to achieve voltage regulation in distributed power systems in the presence of solar sources and BESSs. The goal is to find the minimum size of the BESSs and their corresponding position in the network based on the size and location of the integrated solar generation. The proposed method formulates the problem by combining grid sensitivity coefficient analysis and modeling second-order cone programming (SOCP) in power flow analysis. Using reactive power to adjust voltage regulation is not always the optimal solution in distribution systems in which R/X is large. Therefore, the study only considers the minimum size and best BESS location achieved by optimizing the amount of solar-curtailed active power through BESS based on the grid topology and R/X ratios in the distribution system. Simulation results on the modified IEEE-33 bus verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Sensitivity analysis

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LBA: Matching Theory Based Latency-Sensitive Binary Offloading in IoT-Fog Networks 16

LBA: Matching Theory Based Latency-Sensitive Binary Offloadi...

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16th International Conference on COMmunication systems and NETworkS, COMSNETS 2024

作者： Soni, Priyanka Deshlahre, Omkar Chand Satpathy, Anurag Addya, Sourav Kanti National Institute of Technology Karnataka Cloud and Smart System Services Lab Department of Computer Science and Engineering India Missouri University of Science and Technology RollaMO United States

ISBN: (纸本)9798350383119

The Internet of Things (IoT) is growing more popular with applications like healthcare services, traffic monitoring, video streaming, smart homes, etc. These applications produce an enormous amount of data, so a realistic option in this instance is to offload computational tasks to their proximity fog nodes (FNs) instead of the remote cloud. However, a negligent offloading strategy may cause anomalous computational traffic load at the FNs, causing congestion that may adversely affect the latency. However, the latency of task flows from IoT devices comprises communications latency at BS and computational latency at FNs. Therefore, designing offloading algorithms to distribute the computational load at FN evenly and efficiently utilize the FN resources is crucial. To solve this problem, we proposed LBA in a fog network with a binary offloading strategy using the matching theory-based approach. We utilize the Analytic Hierarchy Process (AHP) to generate the preference list. Furthermore, the binary offloading technique follows the deferred acceptance algorithm (DAA) to produce a stable assignment, and the complete offloading problem is modeled as a one-to-many matching game. Comprehensive simulations ensure that LBA can accomplish a better-balanced assignment for homogeneous and heterogeneous input concerning all the baseline algorithms. © 2024 IEEE.

关键词： Analytic Hierarchy Process (AHP) Binary offloading Fog computing IoT Load balancing Matching Theory

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FDDSGCN: Fractional Decoupling Dynamic Spatiotemporal Graph Convolutional Network for Traffic Forecasting

FDDSGCN: Fractional Decoupling Dynamic Spatiotemporal Graph ...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Xu, Jinpeng Zhao, Chunna Yang, Jing Huang, Yaqun Yang, Yaoyuan Yee, Por Lip School of Information Science & Engineering Yunnan University Kunming China Department of Computer System and Technology Universiti Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9798350368741

Urban traffic flow management faces increasing challenges due to accelerating urbanization. Traffic data collected from roadside sensors contain complex temporal and spatial dependencies that interact simultaneously. Although Graph Neural Networks and Recurrent Neural Networks have been successful in capturing these dependencies, two critical issues remain: 1) Treating all traffic signals equally fails to capture the nuanced spatiotemporal dependencies hidden in time series data;2) Dynamic traffic conditions hinder the accurate capture of local spatial dependencies, thereby limiting prediction accuracy and reliability. To address these challenges, we propose an innovative model, FDDSGCN. To resolve the first issue, we introduce Fractional Residual Decomposition, which effectively separates traffic data into spatial and temporal signals. For the second issue, we employ Dynamic Spatial-Temporal Graph Convolution with fractional-order weight adjustments to dynamically capture local dependencies. Additionally, the Long Short-Term Dependency module analyzes both long-term and short-term dependencies. Extensive experiments on three public datasets demonstrate the superior performance and practical value of our model. © 2025 IEEE.

关键词： dynamic graph learning Fractional Residual decomposition spatial-temporal graph Traffic prediction

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Recent Advances in Space-Deployable Structures in China

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engineering 2022年第10期17卷 207-219页

作者： Xiaofei Ma Tuanjie Li Jingya Ma Zhiyi Wang Chuang Shi Shikun Zheng Qifeng Cui Xiao Li Fan Liu Hongwei Guo Liwu Liu Zuowei Wang Yang Li Xi’an Institute of Space Radio Technology Xi’an 710100China School of Electromechanical Engineering Xidian UniversityXi’an 710071China Beijing Institute of Spacecraft System Engineering Beijing 100094China Aerospace System Engineering Shanghai Shanghai 201109China State Key Laboratory of Robotics Harbin Institute of TechnologyHarbin 150001China Department of Astronautical Science and Mechanics Harbin Institute of TechnologyHarbin 150001China

Deployable space structure technology is an approach used in building spacecraft,especially when realizing deployment and folding *** in orbit,the structures are released from the fairing,deployed,and *** the development of communication,remote-sensing,and navigation satellites,space-deployable structures have become cutting-edge research topics in space science and *** paper summarizes the current research status and development trend of spacedeployable structures in China,including large space mesh antennas,space solar arrays,and deployable structures and mechanisms for deep-space *** technologies of space-deployable structures are addressed from the perspectives of deployable mechanisms,cable-membrane form-finding,dynamic analysis,reliable environmental adaptability analysis,and ***,future technology developments and trends are elucidated in the fields of mesh antennas,solar arrays,deployable mechanisms,and on-orbit adjustment,assembly,and construction.

关键词： Deployable space structures Mesh antennas Solar arrays Deep-space exploration

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An Elite Archive-Assisted Multi-Objective Evolutionary Algorithm for mRNA Design 13

An Elite Archive-Assisted Multi-Objective Evolutionary Algor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Hong, Wenjing Chen, Cheng Zhu, Zexuan Tang, Ke Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Shenzhen China Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen China

ISBN: (纸本)9798350308365

Messenger RNA (mRNA) vaccines have emerged as highly effective strategies in the prophylaxis and treatment of diseases. mRNA design, a key to the success of mRNA vaccines, in-volves finding optimal codons and increasing secondary structure stability to lengthen mRNA half-life, ultimately enhancing protein expression. Despite receiving widespread attention, most methods primarily rely on manual design, which is time-consuming and labor-intensive. While optimization approaches can alleviate this issue, existing methods still exhibit critical limitations caused by conflicts between codon usage and mRNA structural stability, compounded by the vast design space of mRNA resulting from the presence of synonymous codons. In this paper, a novel multi-objective evolutionary optimization-based mRNA design method is proposed. We first formulate the mRNA design problem as a multi-objective optimization problem and then develop an Elite Archive-Assisted Multi-Objective Evolutionary algorithm for mRNA Design, namely EAA-MOED, by incorporating a novel elite archive-assisted method into a weighted optimization framework to improve search efficiency. Experimental studies, involving two state-of-the-art mRNA design methods and five well-known MOEAs, show the competitiveness of the proposed EAA-MOED in mRNA design. © 2024 IEEE.

关键词： Vaccines

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Deep Learning Techniques for Advanced Large-Scale Data Processing 15

Deep Learning Techniques for Advanced Large-Scale Data Proce...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sunil, M.P. Shekhawat, Jyoti Vanaja, T. Mohammed, Vazeer Ali Thaware, Shailesh J. Singh, Vaishali Karnataka Bangalore India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer & Information System Lewis University Illinois United States Department of Computer Engineering Vishwakarma Institute of Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350370249

Deep getting to know techniques have become increasingly more popular due to their potential to improve huge-scale records processing performance. Leveraging specialized hardware which includes GPUs, deep getting to know algorithms can attain mind-blowing pace will increase compared to traditional algorithms. further, deep gaining knowledge of fashions can discover complicated non-linear relationships in big datasets, permitting greater accurate overall performance and less fake predictions. Latest advances in deep mastering have enabled it to be implemented to remedy a plethora of information processing duties, from photo recognition to natural language processing. CNNs, RNNs, and GANs are a number of the maximum famous deep gaining knowledge of fashions used in tackling complex data processing obligations. agencies consisting of Google, fb, and Amazon use these sophisticated frameworks to build predictive models that help improve numerous programs. Deep getting to know strategies offer exquisite ability to take massive-scale information processing to the following stage. corporations are increasingly more becoming privy to the emerging opportunities, and actively investing in deep mastering to liberate the untapped strength of their information. ©2024 IEEE.

关键词： Large datasets

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Natural Sit-to-Stand Control of a Musculoskeletal Model with Deep Reinforcement Learning-Based Reward Shaping

Natural Sit-to-Stand Control of a Musculoskeletal Model with...

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2024 China Automation Congress, CAC 2024

作者： Dong, Borui Chen, Yaru Chen, Wenqian Wang, Yongxuan Wang, Xiaohong Liu, Rong Liaoning Key Lab of IC BME System School of Biomedical Engineering Dalian University of Technology Dalian China School of Information Engineering Dalian University Dalian China Department of Neuroelectrophysiology Central Hospital of Dalian University of Technology Dalian China

ISBN: (纸本)9798350368604

Understanding the neuromuscular control mechanisms underlying the human sit-to-stand (STS) movement, a fundamental daily activity, is crucial for enhancing the physical capabilities of older adults and advancing applications in robotics and exoskeletons. This paper introduces a deep reinforcement learning (DRL) approach with reward shaping to replicate natural human STS movements using a lower limb musculoskeletal model with three degrees of freedom and nine muscles. We used proximal policy optimization (PPO) with two behavior-guided reward shaping functions,: one focused on joint angle changes (Rjoint) and the other on head height changes (Rhead), each tailored to the model’s capabilities and the movement’s objectives. To assess the effectiveness of our control method, we collected kinematic and kinetic data of human STS movements, allowing for a comparison of joint angles between the musculoskeletal model and human subjects. Both reward conditions demonstrated a strong correlation with experimental data, with the Rhead reward achieving a correlation of 0.9 and faster convergence compared to Rjoint. Additionally, Rhead more accurately captured human joint dynamics, enhancing the realism of the simulated movements, while Rjoint proved more effective in reducing energy consumption. These findings highlight the potential of DRL with reward shaping to generate realistic and efficient movement patterns, paving the way for future applications in robotics and assistive technologies. © 2024 IEEE.

关键词： Deep reinforcement learning

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Investigation of Wheel Robot Grouser Width Parameter Effect on Robot Mobility in Soft Sand Terrain Using Sand Test Bed 1

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4th International conference on Innovative Manufacturing, Mechatronics and Materials Forum, iM3F2023

作者： Basri, Ikmanizardi Aziz, Intan Nur Aqiella Che Ibrahim, Ahmad Najmuddin Fukuoka, Yasuhiro Faculty of Manufacturing and Mechatronics Engineering Technology Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Campus Pahang Pekan26600 Malaysia Department of Mechanical System Engineering Ibaraki University College of Engineering Ibaraki University Hitachi316-8511 Japan

ISBN: (数字)9789819988198

ISBN: (纸本)9789819988181

Much research has been done to investigate the most ideal grouser parameters to improve a robot’s wheel mobility in sandy terrain. However, their area of research mainly focused on the normal wheel with fixed grousers. This paper showcases the study of performance of the assistive grouser wheel moving on a flat surface sandy terrain attached with different grouser width parameters. Two different grouser shapes were fabricated which consist of C-Shape and Wider C-Shape, with two configurations forward facing and inverse. For each grouser set, one of the grousers was attached with 2 load cell sensors used to measure force. The grousers were tested across a total of 3 runs to identify its total average traction force acting on the grouser during the wheel’s movement. The results show increased maximum positive and negative forces when the grouser width is increased, which resulted in less net traction force. The inverse configuration also showed better results than forward facing. This shows that for assistive mechanism, increasing the width of the grouser may not increase the effectiveness of the grouser in generating traction force. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Wheels

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