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Research on Power Security Control Technology Based on Multimode Data Fusion 4

Research on Power Security Control Technology Based on Multi...

引用

4th ieee international conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Shi, Ruida Zhao, Hua Luo, Huafeng Wang, Liuwang Fan, Weidong Nari Group Corporation/State Grid Electric Power Research Institute Nanjing211106 China Nanjing Nari Information & Communication Technology Co. Ltd. Nanjing211106 China State Grid Zhejiang Electric Power Co. Ltd. Hangzhou310011 China

ISBN: (纸本)9798350363586

Power grid operation, equipment maintenance, construction and other power grid field operations, the task is heavy, many points and wide. There are many dangerous factors in the process of power grid operation, including human factors, environmental factors, equipment factors, management factors and other influencing factors. Aiming at the problems of single mode and complex factor, a multi-mode fusion method is proposed. Based on the operation ticket mechanism in the "two votes and three systems"of the power system, under the supervision of the original traditional IP layout and control ball, various influencing factors on the site are collected as comprehensively as possible combined with sensors such as blood oxygen, gas concentration, tension, pressure and inclination Angle, and the information characteristics feedback from these factors are utilized across modes. Multi-level fusion method is adopted to fuse the text features extracted by BeRT and the image features extracted by Faster R-CNN at an early stage, which improves the normalization of the operation process. By making decision fusion of image features and sensor features extracted by LSTM, the alarm of potential hazards is advanced. Under the multi-mode integration, the average level of overall risk prevention and control on the job site has been improved. © 2024 ieee.

关键词： Power grids

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Optimal Dispatch Strategy of electric Vehicles under Coupled Transportation Network and Power grid 8

Optimal Dispatch Strategy of Electric Vehicles under Coupled...

引用

8th international conference on Power and Renewable energy, ICPRe 2023

作者： Luo, Keming Fang, Xiaohan Fan, Yuan Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Hefei230601 China

ISBN: (纸本)9798350328813

This paper addresses the complex nature of electric vehicles (eVs) as both transportation means and mobile loads, and proposes an optimal dispatching scheduling strategy for eVs in the coupled transportation network and power grid. Firstly, a dynamic traffic network model is established by utilizing a vast amount of real-world traffic data, including Origin-Destination (OD) information, battery states, and departure times. A graph theory-based analysis is then employed to determine the optimal paths for eVs in the traffic network. Secondly, the charging behavior of eVs is integrated with the power grid, and charge-discharge scheduling is conducted for charging stations to optimize the power grid load curve while meeting the charging demands of eVs. Additionally, adaptive electricity prices are formulated based on the power grid's load generation through a dynamic pricing mechanism, further optimizing the charging strategy for eVs. Lastly, the impact of eV charging on the power grid load is analyzed by contrasting ordered and unordered charging and discharging modes. The research results demonstrate that the proposed optimal charging scheduling strategy for eVs in traffic-aware power grids can significantly reduce peak-valley differences in power grid load, enhance the economic and operational stability of the power grid, and effectively meet the charging demands of eV users. These findings provide valuable insights and promising potential for practical applications and widespread adoption. © 2023 ieee.

关键词： Charging Dispatch Coupled Transportation Network and Power grid Dynamic Pricing Mechanism electric Vehicles (eVs)

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Using grid Search Methods and Parallel computing to Reduce AI Training Time for Reliability Lifetime Prediction of Wafer-Level Packaging 24

Using Grid Search Methods and Parallel Computing to Reduce A...

引用

24th international conference on Thermal, Mechanical and Multi-Physics Simulation and experiments in Microelectronics and Microsystems (euroSime)

作者： Chang, C. Y. Lee, C. H. Chiang, K. N. Natl Tsing Hua Univ Adv Microsyst Packaging & Nanomech Res Lab Dept Power Mech Engn Hsinchu 300 Taiwan

ISBN: (纸本)9798350345971

electronic packaging technology undergoes Accelerated Thermal Cycling Test (ACTC) before hitting the market. Finite element analysis is commonly used to build models for electronic packaging products. However, simulation errors may arise due to differences in physical concepts and considerations among researchers. To overcome this challenge, we create a database through validated finite element models and combine it with machine learning. In the domain of machine learning models, training time is a crucial research focus. Nevertheless, grid search time is often overlooked, despite its significant impact on machine learning model efficiency. To address this issue, this study utilizes parallel computing to explore the search for optimized hyperparameters in the context of the Wafer Level Chip Scale Package (WLCSP) as a case study. Additionally, custom empirical formulas are utilized to enhance the efficiency of grid search methods, thereby improving the time-to-market and competitiveness of packaged products.

关键词： Wafer Level Packaging Finite element Analysis Thermal Cycle Load Reliability estimation Machine Learning Parallel computing grid Search

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Intelligent error Correction Method for electric Power Text Based on eLeCTRA 5

Intelligent Error Correction Method for Electric Power Text ...

引用

5th international conference on Intelligent computing and Human-Computer Interaction, ICHCI 2024

作者： Wang, Zhanying Wu, Tong Zhang, Mengzi Wang, Wende State Grid Liaoning Electric Power Co. Ltd Shenyang China

ISBN: (纸本)9798350368284

In the power industry, text information processing is a crucial task. Whether it's a day-To-day official document release, news writing, or an editorial response to a text related to the power system, a large amount of textual information needs to be processed precisely. With the continuous progress of technology and the expansion of application scope, text correction technology will bring more innovation and development opportunities to the power industry, and is of great significance to facilitate the sustainable progress of the power industry. In this paper, the statistical language model and the neural network-based pre-Trained model are fused to train and verify the correction of typos in the power text, and finally the model effect is evaluated through the comprehensive index F1. The results show that the F1 values of the single pre-Trained model and the single statistical language model are 0.5871 to 0.4738, respectively, which is lower than the F1 of the fusion model for text typo correction of 0.6354. This fusion method has a good effect on text typo correction in the power industry, and makes a positive impact in ensuring the quality of text related to the power system. © 2024 ieee.

关键词： eLeCTRA model natural language processing neural networks power text error correction

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A Decentralized Vehicle-to-Vehicle energy Trading System Based on efficient Sharding Services 21

A Decentralized Vehicle-to-Vehicle Energy Trading System Bas...

引用

21st ieee international Symposium on Parallel and Distributed Processing with Applications, 13th ieee international conference on Big Data and Cloud computing, 16th ieee international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Meng, Kun Sun, Lijun Chen, Xiao Wu, Haiqin Li, Shuaiyong Qingdao University of Science and Technology College of Information Science and Technology Shandong China University of Leicester School of Computing and Mathematical Sciences Leicester United Kingdom Software Engineering Institute Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing China

ISBN: (纸本)9798350329223

Vehicle-to-vehicle (V2V) energy trading stands as a significant technology, allowing electric vehicles (eVs) to share energy. This balances energy demand and supply, reducing pressure on the power grid. However, two substantial challenges require attention: 1) Creating a standardized protocol universally adoptable by eV manufacturers and energy trading participants to establish a common secure and reliable platform for real-time energy trading between eVs. 2) Determining a fair and transparent pricing and transaction management mechanism, accounting for factors such as energy demand and supply, location, and user preferences. To tackle these hurdles, this paper proposes a decentralized V2V energy trading system (VeTS) based on a novel high-performance sharding blockchain framework. VeTS incorporates a standard energy trading management protocol, achieving trustless and transparent transaction processing. It employs a blockchain sharding and parallel architecture for high transaction throughput, catering to a large number of eVs. Furthermore, an efficient consensus algorithm is developed to minimize service delays and adapt to real-time transaction demands. A practical testbed operationalizes VeTS, facilitating experimental analysis within a real-world cloud environment. © 2023 ieee.

关键词： Blockchain

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Facial grid environment for Vitiligo Detection: A Deep Reinforcement Learning Perspective 2

Facial Grid Environment for Vitiligo Detection: A Deep Reinf...

引用

2nd ieee international conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2024

作者： Adwayan, P.C. Anfas Hassan, V. Suresh, Navneeth Nisha, K.S. Sha, Akhbar Amrita Vishwa Vidyapeetham Amrita School of Computing Department of Computer Science and Engineering Amritapuri India

ISBN: (纸本)9798350360523

This research addresses the challenging task of vitiligo detection within facial images through the lens of Deep Reinforcement Learning (DRL). Leveraging the Skin Disease dataset from Kaggle, our study focuses on the integration of three distinct convolutional neural network architectures - ResNet, VGG, and efficientNet - within the DRL framework. Facial landmarks, crucial for spatial awareness, were extracted using OpenCV as a preprocessing step. The DRL agent navigates through a grid overlaying facial images, with states corresponding to grid cells, to reach the vitiligo-affected region and maximize cumulative rewards. Analysis of the models revealed ResNet's superior stability in the loss curve, indicative of its effective feature learning. The classification accuracy further reinforced ResNet's prominence, reaching an impressive 97%, outperforming VGG (94.5%) and efficientNet (95.3%). While VGG and efficientNet demonstrated competitive performances, ResNet's robustness and accuracy position it as the preferred architecture for vitiligo detection in facial images. This study contributes to the burgeoning field of dermatological diagnostics by showcasing the efficacy of DRL and different CNN architectures in automating vitiligo detection. The findings not only advance our understanding of the interplay between deep learning and dermatology but also lay the foundation for more accurate and efficient models in the broader landscape of skin disorder identification. © 2024 ieee.

关键词： Reinforcement learning

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A Novel Fuzzy Identity-Based encryption with Wireless PUF for IoT Device Authentication 25

A Novel Fuzzy Identity-Based Encryption with Wireless PUF fo...

引用

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： Chen, Ye Song, Yubo Cai, Yihan Shan, Qiuhong Zhang, Bo Zhang, Tao School of Cyber Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories Nanjing China State Grid Smart Grid Research Institute Nanjing China

ISBN: (纸本)9798350330014

Identity-Based encryption algorithm generates public-private key with identity, reduces the key management complexity of IoT devices. However, traditional IBe algorithm is vulnerable to spoofing attacks. This paper proposes a novel Fuzzy Identity-Based encryption algorithm, defines the fuzzy identity as an attribute set composed of multidimensional physical features of IoT devices. The algorithm extracts device fuzzy identity from their unique physical characteristics, establish a linkage between device physical attributes and logical identity. Moreover, this paper introduces the concept of fuzziness to overcome the impact of physical noise. We calculate the fuzziness of individual attributes within the attribute set, as well as the overall fuzziness among the sets to match fuzzy identity. To achieve low-cost device identity authentication for multiple wireless IoT devices in a contactless scenario, this paper proposes a Physical Unclonable Function to extract device-related physical attributes based on Channel State Information. The stimuli response of the PUF constitute the fuzzy identity of IoT devices. Formal security analysis indicates that the security of our method can be reduced to the hardness of the Decisional Modified Bilinear Diffie-Hellman (MBDH) assumption and provides Chosen Ciphertext Attack security. Our approach achieves a 96.9% success rate in extracting public-private keys despite physical noise, even in scenarios with concurrent access by multiple wireless IoT devices. © 2023 ieee.

关键词： Fuzzy systems

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Research on Digital Mining Model Algorithm of Computer 3D science Knowledge Graph Visualization Technology 6

Research on Digital Mining Model Algorithm of Computer 3D Sc...

引用

2023 ieee 6th international conference on Information Systems and Computer Aided education, ICISCAe 2023

作者： Zhang, Nan Sun, Zhen Shang, Yingnan Nari Group Co. Ltd State Grid Electric Power Research Institute Nanjing China

ISBN: (纸本)9798350313444

Through the visibility of knowledge map and the use of map visibility to express the correlation between different types of information. Firstly, the paper mines the multimodal data related to the field of computer science and establishes a more systematic multimodal knowledge base. Combined with association extraction rules, association extraction was carried out. A multimodal computer domain knowledge map which can be automatically extracted from relational ternary associations is constructed. The simulation results show that this method can be used to integrate academic resources in a deep level. It provides advanced knowledge services to the online community. © 2023 ieee.

关键词： 3D science digitization knowledge map mining model algorithm visualization technology

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Research on the Application of Knowledge Management System and Digital Service in Smart grid 2

Research on the Application of Knowledge Management System a...

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2nd international conference on Mechatronics, IoT and Industrial Informatics, ICMIII 2024

作者： Zeng, Liangbo Shi, Yadong Li, Liang Zhu, Junwei Tan, Rongyin Management Science Research Institute of Guangdong Power Grid Co. Guangzhou China

ISBN: (纸本)9798350386639

This paper studies the application of cloud network cooperation technology in intelligent power networks. The overall framework and main functional modules of the system are introduced. The integrated software of communication and acquisition, fault detection and monitoring, safety protection and dispatching, energy and power distribution management, analysis, evaluation and decision optimization is developed. The system can be dynamically operated and managed according to user requirements. This is the so-called "data-driven"intelligent power system. The collaborative management mode suitable for cloud and fog computing is studied to reduce the demand from the client to the cloud and shorten the response speed of users to fog data. At the same time, the optimal response and the optimal processing time of the virtual machine are reasonably configured. A new type of service Agent is used to manage the data center. The load balancing method combining PSO and simulated annealing (PSO-SA) is introduced into virtual machine in data center, and the effectiveness of the two methods is verified by simulation experiments. © 2024 ieee.

关键词： Fog computing

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LVRT and HVRT analysis of grid connected Solar PV system

LVRT and HVRT analysis of Grid connected Solar PV system

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2023 ieee international conference on Power electronics, Smart grid, and Renewable energy, PeSGRe 2023

作者： Sreedevi, J. Sannappaiah, Honnesh C Cpri Power Systems Division Bangalore India

ISBN: (纸本)9798350310573

Growing technologies in the field of energy harvesting from renewables (majorly Solar and Wind) lead the way to competitive inverter-based generation (IBG), with low cost and integration to the utility grid. The increased grid penetration of IBGs may affect the grid by decreasing the stability there by violating the grid code limitations. The countries having high renewable energy penetration reviewed their grid codes to maintain sustainable power supply. The standard test system is modelled in PSS/e software to study the dynamic stability of system with solar PV Plant is studied. The Western electricity coordinating Council (WeCC) 2nd generation controllers are modelled to access the dynamic performance of the system for different penetration level. © 2023 ieee.

关键词： grid code High Voltage Ride Through ieee 9 bus system Low Voltage Ride Through Point of Common Coupling Unity Power Factor

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