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Review of Transient Earth Voltage sensor Implementation to Detect Partial Discharge in High Voltage Equipment 4

Review of Transient Earth Voltage Sensor Implementation to D...

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4th international conference on High Voltage Engineering and Power systems, ICHVEPS 2023

作者： Khayam, Umar Zaeni, Arpan Institut Teknologi Bandung School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350318678

this paper reviews the implementation of a Transient Earth Voltage (TEV) sensor to detect partial discharge in high-voltage equipment. the use of TEV as a partial discharge sensor is one of the main choices recently because of its ease of use. Research regarding the implementation of TEV has been carried out by many researchers. the research conducted is mainly for metal-enclosed high-voltage equipment such as GIS, Transformers, etc. the main purpose of this paper is to provide a reference related to the development of TEV implementation research for high-voltage equipment. From the review conducted, it can be known that there are some common methods for comparing TEV sensor performance with other sensors based on the comparison of PD measurement which is implemented in 6 types of high-voltage equipment. By comparing parameters such as frequency value, occurrence time, duration, PD pattern, waveform shape, etc., a more in-depth analysis of the characteristics of partial discharge detected by TEV or its comparative sensor for each equipment or type of defect can be determined. © 2023 ieee.

关键词： Transients

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Microgrid Capacity Configuration Optimization Based on Multi-population Cooperative Grey Wolf Algorithm 4

Microgrid Capacity Configuration Optimization Based on Multi...

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4th international conference on Intelligent Power and systems, ICIPS 2024

作者： Wen, Xiaoyao Yang, Jiahao Zhang, Jingrui Tsai, Wen-Chang Xiamen University Department of Instrumental and Electrical Engineering Xiamen China Xiamen University Tan Kah Kee College School of Mechanical and Electrical Engineering & Automation Zhangzhou China

ISBN: (纸本)9798331532765

With the rapid development of renewable energy, independent microgrids integrating distributed energy sources such as wind and solar power have become a research focus due to their excellent cost-effectiveness and energy efficiency. In microgrid design, optimal capacity allocation is crucial for improving resource utilization and reducing operational costs. Grey Wolf Optimization (GWO) algorithms which show great potential in solving optimal allocation problems are prone to early convergence and local optima. To address these issues, this study proposes four strategies to enhance global search capability and population diversity: (1) multi-population strategy to increase diversity;(2) t-distribution mutation to disturb optimal individuals, improving early global search and late-stage local optimization, thereby accelerating convergence;(3) hybrid operation to introduce diversity and prevent local convergence;and (4) replacement strategy to maintain population diversity and exploration ability. Taking the optimal configuration of a wind-solar-diesel-storage microgrid as an example, experimental results show that the multi-population collaborative GWO algorithm reduces annual costs by 3,720 RMB, 10,470 RMB, and 57,350 RMB compared to traditional GWO, PSO, and DE algorithms, respectively. these results demonstrate the superiority of the proposed algorithm in microgrid optimization, highlighting its advantages in enhancing global optimization capabilities and reducing operational costs. © 2024 ieee.

关键词： distributed energy

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SMVAR: A Novel RNN Accelerator Based on Non-blocking Data Distribution Structure 25

SMVAR: A Novel RNN Accelerator Based on Non-blocking Data Di...

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25th ieee international conferences on High Performance computing and Communications, 9th international conference on Data Science and systems, 21st ieee international conference on Smart City and 9th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Xu, Jinwei Jiang, Jingfei Xu, Shiyao Gao, Lei National University of Defense Technology Science and Technology on Parallel and Distributed Laboratory Hunan Changsha China

ISBN: (纸本)9798350330014

Recurrent neural networks (RNNs) have become common models in the field of artificial intelligence to process temporal sequence task, such as speech recognition, text analysis, natural language processing, etc. To speedup RNNs inference, previous research proposed model sparse pruning techniques. However, the pruning rate of existing sparse pruning algorithms will be affected by pruning granularity and hardware friendliness. In order to approximate nonstructured pruning algorithm, this paper proposes Large Region Balanced Sparse (LRBS) pruning method, which does not limit sub-matrix shape and effectively improves pruning rate. Furthermore, we propose Sparse Matrix Vector Multiplication Accelerator for RNNs (SMVAR), which adopt non-blocking data distribution structure to solve the problem of efficient execution of large region irreg-ular matrix multiplication. To further improve the accelerator performance, SMVAR fine-grained adjusts the pipeline between macro-operations to reduce the idle of compute components. In addition, according to the coarse-grained block characteristics of LRBS algorithm, we develop the coarse-grained parallelism of accelerator with multiply compute units(CUs) structure. Experiments show that the pruning rate of our proposed LRBS is 1.25x-2.5x higher than that of the existing pruning algorithms. Compared with the existing work, the execution efficiency is improved by more than 2.02x-35.9x in the same application scenario. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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Sustainable Wireless sensor Networks: Energy-Efficient Clustering Protocols for Extended Operation 4

Sustainable Wireless Sensor Networks: Energy-Efficient Clust...

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4th ieee international conference on ICT in Business Industry and Government, ICTBIG 2024

作者： John, V.Y. Nawadkar, Ashwini Ranjit thangamani, A. Nanda, Simranjeet Kala Priydarshini, G. Grover, Madhur School of Mangement - Pg Management Karnataka Bangalore India Vishwakarma Institute of Technology Pune India Karpagam Academy of Higher Education Department of Chemistry Coimbatore641021 India Chitkara University Centre of Research Impact and Outcome Punjab Rajpura140417 India Prince Shri Venkateshwara Padmavathy Engineering College Department of Eee Chennai127 India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India

ISBN: (纸本)9798331518981

Because of their widespread use in contexts with constrained resources, wireless sensor networks' (WSNs) ability to conserve energy is of the utmost importance. Assigning cluster heads to each group of sensor nodes and classifying them as a cluster is the standard method for clustering. But it's not easy to get the network performance and energy usage just right. Several hierarchical methods, several levels of clustering, and dynamic clustering models are covered in this study as energy-efficient clustering protocols. We evaluate these protocols' impact on network lifetime, energy consumption, and data transfer reliability using simulation results and performance metrics. Among the most recent developments in the field of energy-efficient clustering include the use of machine learning for the purpose of predicting network behavior and adjusting cluster formation, and the development of intricate protocols that combine several energy-saving techniques. the research highlights the importance of enhancing and incorporating clustering techniques into WSN systems to meet their future demands and adapt to their dynamic nature. Improving the operational life of WSNs and building sustainable and optimal solutions are both made possible by energy-efficient clustering methods. © 2024 ieee.

关键词： Energy utilization

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Application of Integrated Optical E-field sensor for Non-Contact Transient Voltage Measurements 4

Application of Integrated Optical E-field Sensor for Non-Con...

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4th international conference on Smart Grid and Energy Internet, SGEI 2024

作者： Qian, Bo Xu, Yang Sun, Yongsen Xie, Tianxi Zhu, Yuchen Yang, Huaiyuan State Grid Jiangsu Electric Power Co. Ltd. Nanjing210000 China State Grid Jiangsu Electric Power Co. Ltd. Research Institute Nanjing211103 China Department of Electrical Engineering Tsinghua University Beijing China

ISBN: (纸本)9798350368314

As power grids evolve towards smarter, more transparent systems, there is an increasing demand for high-precision, high-reliability, and cost-effective voltage measurement techniques. Unlike traditional contact methods, integrated optical E-field sensor offers safe, accurate voltage measurement without altering system topology. this paper established a non-contact voltage measurement system using integrated optical electric field sensors based on the Pockels effect. the system employed Common Path Interferometer (CPI) electric filed sensors, known for high stability and bandwidth, to measure transformer overvoltage caused by delayed closing and switching off in substations. Experiments show that the maximum delayed closing overvoltage occurs during the second closing action, while switching off overvoltage are lower and decay faster. this system provides a precise, reliable, and cost-effective solution for transient voltage measurement in modern power grids. ©2024 ieee.

关键词： Strain measurement

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Research on Two-stage Identification of distributed Photovoltaic Output Based on WGAN Data Reconstruction Technology 4

Research on Two-stage Identification of Distributed Photovol...

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4th international conference on Advanced Electrical and Energy systems, AEES 2023

作者： Su, Yun Gu, Jun Zhang, Jianxin Yang, Xiu Jin, Yu Li, Wenhao Shanghai Electric Power Company Shanghai China Shanghai University of Electric Power College of Electrical Engineering Shanghai China

ISBN: (纸本)9798350342659

In recent years, the development of household distributed photovoltaics has been rapid, and its unobservable characteristics have brought huge challenges to the planning and control of the power grid and user energy management by the power sector. In view of this, this article proposes a two-stage identification method for distributed photovoltaic output based on data reconstruction technology. this method transforms the problem of distributed photovoltaic output identification into the problem of reconstruction of actual load missing data. Based on this, it fully considers the hidden photovoltaic feature information in the net load, corrects the photovoltaic output identification results, and achieves precise identification of the target user's photovoltaic output. Compared with existing methods, the proposed method does not need to consider the impact of environmental factors on photovoltaic output during identification, and the accuracy of the results identified by existing technologies is also significantly improved. © 2023 ieee.

关键词： Electric power system control

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Dynamic Performance Improvement for Permanent Magnet Synchronous Motor Drive Combining Hall sensor and sensorless Algorithem 4

Dynamic Performance Improvement for Permanent Magnet Synchro...

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4th international conference on Electrical Engineering and Control Science, IC2ECS 2024

作者： An, Quntao Cong, Weihui Zhao, Mengji Wu, Youtong Harbin Institute of Technology School of Electrical Engineering and Automation Harbin China

ISBN: (纸本)9798331510107

the underwater unmanned vehicle (UUV) has strict requirements for the volume, noise, and dynamic response of the motor propulsion system. therefore, a control algorithm of permanent magnet synchronous motor (PMSM) combining hall sensors and position sensorless technology is adopted to meet the above requirements. And during the speed transition phase, the hysteresis is employed to facilitate a seamless transition between low speed and medium-high speed control methods. Since the observer-based position sensorless control method is a closed-loop system that utilizes state deviation for regulation, its state tracking performance is affected by the regulator type and delay, which can lead to issues of response delay and overshoot in digital discrete control systems. To solve this problem, a position sensorless control system for PMSM is proposed, which is a back electromotive force (EMF) estimation algorithm based on model predictive control (MPC). It has been verified that the proposed drive system can offer good operation performance by the simulation and experiments. © 2024 ieee.

关键词： sensorless control

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Research on Multi-Level Collaborative Scheduling Model Based on distributed Power Connected to the New Power System 4

Research on Multi-Level Collaborative Scheduling Model Based...

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4th ieee international conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Zhou, Ji Yang, Zijun Li, Kai Xia, Lei Tan, Huilei Xu, Lina State Grid Corporation of China Beijing China State Grid Jiangsu Electric Power Co. Ltd Jiangsu Province Nanjing China Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Beijing China

ISBN: (纸本)9798350359589

After the distributed power supply connects to the new power system, the power grid scheduling is affected by voltage flash during the grid scheduling, resulting in an increase in operating costs of the power grid. It is proposed that the high -penetration distribution power supply connects the diversified electric energy dual -layer scheduling method of the new power system. After mastering the current adjustment of the load and credible contribution information of the power grid, this paper builds a multi -purpose power system diversified power dual-layer scheduling model based on multi -target optimization. the upper layer scheduling target of this model is to optimize the quality of diversified electricity. the lower layer scheduling goal is to maximize the economic benefits of the new power system. the minimum value method can be solved to achieve the upper and lower target functions. the system schedules the optimal solution to ensure that under the access to high penetration distributed power supply, to ensure the maximization goal of the economic benefits of the power grid, it reasonably dispatches the displacement of the distributed power supply, and realizes the optimization of the diversified power quality of the new power system. the experimental results show that under the scheduling of this method, the voltage offset of the photovoltaic grid system is reduced by 0.60 MV. the operating cost of the new power system is also effectively controlled. Compared with that before the scheduling, this method is available. © 2024 ieee.

关键词： distributed power multi-layer collaboration new power system optimal scheduling

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Intelligent System for distributed Deep Learning Training Traffic Optimization 24

Intelligent System for Distributed Deep Learning Training Tr...

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24th ieee international conference on High Performance computing and Communications, 8th ieee international conference on Data Science and systems, 20th ieee international conference on Smart City and 8th ieee international conference on Dependability in sensor, Cloud and Big Data systems and Application, HPCC/DSS/SmartCity/DependSys 2022

作者： Lu, Weipeng Wu, Shuang Ou, Junhui Niu, Bing He, Jin Song, Kevin Zheng, Xinwei Ustc Hefei China Vmware Beijing China

ISBN: (纸本)9798350319934

distributed training crossing multiple computing nodes and accelerators has been the mainstream solution for large model training. Precedent work on distributed deep learning (DDL) training acceleration has focused on improving the efficiency of communication and GPU resource scheduling, with little attention given to network bandwidth usage. However, due to cluster GPU fragmentation, more than one training job is frequently assigned to the same node to reduce waiting time. the competition for network bandwidth among various distributed training jobs becomes a problem that cannot be overlooked, and this competition results in a considerable reduction in training speed. We propose a system deployed in cluster nodes that includes traffic monitoring, classification, and prediction of DDL training status and implement a priority-based traffic scheduling policy that considers DDL training features. We demonstrate that this policy is beneficial compared to Linux's default policy, which can increase training speed by approximately 18%. Additionally, we increase the training speed by approximately 20% in the case of continuous background traffic by increasing the bandwidth priority during DDL training. © 2022 ieee.

关键词： Deep learning

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Towards a Federated Intrusion Detection System based on Neuromorphic computing 9

Towards a Federated Intrusion Detection System based on Neur...

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9th international conference on Smart and Sustainable Technologies (SpliTech)

作者： Lofu, Domenico Sorino, Paolo Di Noia, Tommaso Di Sciascio, Eugenio Politecn Bari Dept Elect & Informat Engn DEI Via E Orabona 4 I-70125 Bari Italy

ISBN: (纸本)9798350390797;9789532901351

Intrusion Detection systems (IDSs) have emerged as essential tools for detecting cyber attacks and safeguarding sensitive data. Over time, there has been a shift towards designing IDSs that leverage Federated Learning (FL) methods, enabling them to detect attacks across distributed environments while upholding privacy-preserving manner. Concurrently, selecting the appropriate algorithm for Host execution, ensuring data privacy, low power consumption, and swift execution, has become a promising challenge. Recently, there has been a growing interest in Spike Neural Networks (SNNs) due to their ability to directly generate spikes and closely emulate human brain functions. SNN-based models are optimized to achieve energy efficiency by representing computations through asynchronously generated spikes. To tackle these challenges, we propose a theoretical approach for implementing a Federated Intrusion Detection System (IDS) that gathers data from different geographical locations, based on Neuromorphic computing principles.

关键词： Neuromorphic computing Artificial Intelligence Federated Learning Intrusion Detection System

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