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13th international conference of Information and Communication Technology, ICTech 2024

作者： Tang, Rui Wang, JiHui Shenyang Institute of Computing Technology Chinese Academy of Sciences Shenyang110168 China University of Chinese Academy of Science Beijing100049 China

ISBN: (纸本)9798350376258

It takes a lot of time and manpower to create and edit the traditional power grid topology. With the advent of the era of intelligent power, the scale of power system is expanding, and the requirements of power grid users for the display effect of power grid topology are also increasing. Therefore, the maintenance workload of topology is increasing. If there is a feasible, efficient and beautiful topological graph automatic generation method to solve this problem, the work efficiency of distribution network production can be further improved. In order to solve this problem, this paper proposes an improved force-oriented algorithm to automatically generate the power grid layout under the condition of given power line data and node initial coordinates. The automatic layout algorithm is used to achieve better topology visualization by reorganizing the topology layout. The application example shows that the power grid topology graph created by this method contains fewer intersections and the nodes are evenly arranged, which can significantly improve the visualization effect of the network graph. ©2024 ieee.

关键词： Power grids

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On-grid Photovoltaic System Using A Solid-State Transformer

On-Grid Photovoltaic System Using A Solid-State Transformer

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2024 international conference on Green energy, computing and Sustainable Technology, GeCOST 2024

作者： Tumbelaka, Hanny H. Khoswanto, Handry Ananda, Stephanus A. Liong Hoat, Thiang Hwang Petra Christian University Department of Electrical Engineering Department of Engineer Profession Education Surabaya Indonesia Petra Christian University Department of Informatics Surabaya Indonesia Petra Christian University Department of Electrical Engineering Surabaya Indonesia

ISBN: (纸本)9798350357905

This paper explains a single-phase on-grid PV system employing a solid-state transformer (SST) which consists of a DC-AC converter, a high-frequency transformer, a simple rectifier, and a Voltage Source Inverter (VSI). The DC-AC converter converts the PV panel output voltage to a high-frequency three-level square wave required by the transformer operation. The pulse width of the square wave determines the PV operating points. The high-frequency transformer provides voltage level matching and galvanic isolation between the PV panels and the grid. While a simple rectifier produces a DC bus voltage for the VSI. The VSI has a grid current controller and a DC bus voltage controller to regulate the electrical power flow of the grid, the load, and the PV panel. Computer simulation results prove that the PV power can be delivered to the load and the grid through SST, while the grid current is kept sinusoidal and in phase with the grid voltage. © 2024 ieee.

关键词： High frequency transformers

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Global Localization of Mobile Robots Based on Dynamic Partitioning Global Descriptor

Global Localization of Mobile Robots Based on Dynamic Partit...

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2024 ieee international conference on Real-Time computing and Robotics, RCAR 2024

作者： Xue, Shiyun Wang, Jingchuan Xiao, Peng Guo, Rui Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China State Grid Intelligence Technology CO. LTD China

ISBN: (纸本)9798350372601

Global localization is a challenging problem as it is difficult for a mobile robot to obtain the current pose without the prior pose. It relies on prior environmental maps and sensor information. When the robot is in an environment with similar features or sparse features, using existing global localization methods may cause localization failure. In order to solve the localization failure of mobile robots in both indoor and outdoor environments, this paper proposes a global localization system based on dynamic partition global descriptors for 3D point cloud maps. The system is evaluated in indoor corridors and outdoor campus environments. The results show that dynamic partition global descriptors can improve the overall success rate of localization, which reaches more than 90% in different scenarios. The method effectively balances the accuracy and speed of global localization, optimizing the global localization system. © 2024 ieee.

关键词： Mobile robots

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AJAS: A high performance direct solver for advancing high precision astrometry

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JOURNAL OF COMPUTATIONAL science 2025年 87卷

作者： Ryabinin, Konstantin Sarras, Gerasimos Loeffler, Wolfgang erokhina, Olga Biermann, Michael Heidelberg Univ Ctr Astron Astron Rechen Inst Monchhofstr 12-14 D-69120 Heidelberg Germany

In astrometry, the determination of three-dimensional positions and velocities of stars based on observations from a space telescope suffers from the uncertainty of random and systematic errors. The systematic errors are introduced by imperfections of the telescope's optics and detectors as well as in the pointing accuracy of the satellite. The fine art of astrometry consists of heuristically finding the best possible calibration model that will account for and remove these systematic errors. Since this is a process based on trial and error, appropriate software is needed that is efficient enough to solve the system of astrometric equations and reveal the astrometric parameters of stars for the given calibration model within a reasonable time. This paper is an extended version of the conference paper published and discussed at the international conference on Computational science 2024. In this work, we propose a novel software architecture and corresponding prototype of a direct solver optimized for running on supercomputers. The main advantages expected from this direct method over an iterative one are the numerical robustness, accuracy of the method, and the explicit calculation of the variance-covariance matrix for the estimation of the accuracy and correlation of the unknown parameters. This solver can handle astrometric systems with billions of equations within several hours. To reach the desired performance, we use state-of-the-art libraries and methods for hybrid parallel and vectorized computing. The calibration model based on Legendre polynomials is tested by generating synthetic observations on grid-shaped constellation with specified distortions. For these small-sized test data, the solver can recover perfectly the correct physical solution under the condition that the correct amount of eigenvalues is zeroed out. During the space mission, the calibration model should be carefully fine-tuned according to the real operating conditions. The developed solver

关键词： Astrometry Instrument calibration High-performance computing Least Squares Method eigenproblem Pseudo-inverse matrix

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Topology Identification Technology for Low-voltage Distributed Photovoltaic Distribution Network Lines 3

Topology Identification Technology for Low-voltage Distribut...

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3rd international conference on energy and electrical Power Systems (ICeePS)

作者： Zheng, Guoquan Zhu, enguo Zhang, Hailong Liu, Yan Wang, Junlong Liu, Zhe China Elect Power Res Inst Beijing Peoples R China State Grid Hebei Elect Power Beijing Peoples R China

ISBN: (纸本)9798350375145;9798350375138

The large-scale penetration of distributed photovoltaic (PV) power generation systems has brought new challenges to the topology identification and detection of traditional distribution networks. This article mainly studies the topology identification technology (TIT) of distributed PV low-voltage (LV) distribution network lines, aiming to design a topology identification method that can adapt to the dynamic changes of the power grid, have large-scale capacity, and improve system accuracy under the same conditions. At the same time, the data processing speed has been improved. This article first constructs a system model, including node model, edge model, and parameter model. It mathematically represents the topology structure of the power grid using graph theory and designs a topology recognition algorithm based on optimization techniques and state estimation. This algorithm is used to solve the distributed characteristics of power grid topology recognition, the difficulty of data collection, the dynamic diversity of power grid structure, the uncertainty of equipment parameters, the high computational complexity of data processing, and the communication constraints of power grid topology recognition. This algorithm adopts modern programming languages and parallel computing frameworks, making it easy to implement efficiently. The results on the simulation platform show that the highest recall rate for 22 test cases is 93.8%, and the response time for test cases is 425 ms to 980 ms, providing a fast response to the information space of the grid.

关键词： Low-voltage Distributed Photovoltaic Distribution Network Topology Identification Technology Simulation Platform Recall Ratio

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Lightweight Authenticated Key Agreement Protocol for Smart Power grid Systems Using PUF

IEEE Open Journal of the Communications Society

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ieee Open Journal of the Communications Society 2024年 5卷 3568-3580页

作者： Zahoor, Amina Mahmood, Khalid Saleem, Muhammad Asad Badar, Hafiz Muhammad Sanaullah Le, Tuan-Vinh Das, Ashok Kumar Department of Computer Science Sahiwal57000 Pakistan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China Emerson University Multan Department of Emerging Computing Technologies Multan61000 Pakistan Fu Jen Catholic University Bachelor's Program of Artificial Intelligence and Information Security New Taipei City24206 Taiwan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India

The Smart Power grid (SPG) is pivotal in orchestrating and managing demand response in contemporary smart cities, leveraging the prowess of Information and Communication Technologies (ICTs). Within the immersive SPG environment, the ubiquitous deployment of smart meters stands as a testament to their paramount importance in the realm of vigilant monitoring and oversight. These smart meters are installed on high-tension electricity lines and transmit information about electricity outages and other issues to the utility center. To access services from utility centers, smart meters need to communicate securely over a public channel, even though the network itself is insecure. However, potential attacks from adversaries ( Ad) can exploit this communication. Therefore, protecting this communication is of utmost importance. Several privacy-preserving authentication protocols designed for SPG have been introduced in the literature. Nevertheless, a significant number of these protocols exhibit vulnerabilities to diverse security attacks. This article introduces a lightweight and anonymous authentication protocol specifically designed to address these concerns in the SPG environment. Our protocol ensures both security and efficiency, surpassing other comparable protocols in terms of its lightweight nature. By employing both formal and informal analysis, we showcase the robustness of our protocol against significant attacks while remaining lightweight. The proposed protocol provides added security features and incurs 23.8879% lower computation cost than related protocols. Consequently, our protocol is highly suitable for implementation in the SPG system. © 2020 ieee.

关键词： Hash functions

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Research on Software Isomerization Technology Based on Diversified Compilation 9

Research on Software Isomerization Technology Based on Diver...

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9th international conference on Intelligent computing and Signal Processing, ICSP 2024

作者： He, Chuan Zhang, Bo Xi, Zesheng Wang, Yunfan Chen, Lu Lv, Zhuo State Grid Smart Grid Research Institute co. Ltd. State Grid Key Laboratory of Information & Network Nanjing China Information and Communication Branch of State Grid Anhui Electric Power co. Ltd. Nanjing China State Grid Henan Electric Power Research Institute Zhengzhou China

ISBN: (纸本)9798350376548

This article first focuses on the implementation difficulties of software heterogeneous variants, studies the basic principles and implementation mechanisms of pre runtime software intermediate language diversification compilation technology, and combines the characteristics of endogenous security defense architecture. Through efficient equivalent transformation technology at the source code, intermediate representation, binary and other levels, and corresponding code generation technology, it provides multi-level diversified compilation strategies and means, and provides a source code level heterogeneous redundant variant implementation framework for endogenous security defense. Then, to address the issue of software heterogeneity at the intermediate code level, study the compilation process during the intermediate code generation stage;Research and analyze methods such as equivalent instruction replacement, control flow obfuscation, and blank instruction insertion. Propose diversified transformation methods for intermediate languages in application source code, implement diversified compilation techniques based on intermediate language transformation compilation, and achieve software heterogeneity in endogenous security defense architecture. Finally, build a testing environment to support the feasibility verification of the system architecture and key technologies. © 2024 ieee.

关键词： Application programs

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Comparing Connectivity-To-Reservoir Conversion Methods for Connectome-Based Reservoir computing

Comparing Connectivity-To-Reservoir Conversion Methods for C...

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international Joint conference on Neural Networks (IJCNN)

作者： Nishimura, Ryo Fukushima, Makoto Hiroshima Univ Grad Sch Adv Sci & Engn Hiroshima Japan

ISBN: (纸本)9798350359329;9798350359312

The reservoir computing approach has been used in recent studies to investigate the functional aspects of an empirical network consisting of a complete set of structural connections in the brain (i.e., the connectome). These studies use the echo state network as a model for reservoir computing and determine the connections between nodes in the reservoir layer based on the wiring patterns in the connectome. Various methods have been used to convert structural brain connectivity weights to nodeto-node weights in the connectome-based reservoir. Comparison of the conversion methods has just begun, and it is not well understood which factors in the conversion methods are the keys to better learning performance. Here, we compare a variety of conversion methods with respect to the learning performance of the connectome-based reservoir in a standard memory capacity task. As main results, we find that the directionality of the weights and their signs in the connectome-based reservoir are crucial for achieving higher performance and that randomly multiplying the reservoir weights by 1 or improves the inferior performance of the method in which the structural connectivity weights purely determine the reservoir weights. This study provides useful insights for those who wish to improve the learning performance while preserving the information of the structural connectivity weights in the connectome-based reservoir.

关键词： Reservoir computing Artificial neural networks Memory capacity Brain connectivity Connectome

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A Deployable edge computing Solution for Machine Condition Monitoring

A Deployable Edge Computing Solution for Machine Condition M...

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ieee international Instrumentation and Measurement Technology conference (I2MTC)

作者： Zhao, Xijia Wang, Peng Univ Kentucky Dept Elect & Comp Engn Lexington KY 40506 USA Univ Kentucky Dept Elect & Comp Engn Dept Mech & Aerosp Engn Lexington KY 40506 USA

ISBN: (纸本)9798350380903;9798350380910

Machine condition monitoring and predictive maintenance are critical components of smart manufacturing. The realization of machine predictive maintenance relies on synthetic integration of advanced sensing, Internet of Things (IoT), cloud computing, and Artificial Intelligence (AI)-enabled data analytics for machine condition diagnosis and prognosis. One challenge that hurdles the manufacturing shop floor from implementing predictive maintenance is its outdated hardware and limited internet bandwidth, which prevents the floor from transmitting all collected data to the cloud for centralized data analytics. One promising solution is edge-cloud computing and decision-making architecture. In such an infrastructure, collected sensing data will be first processed on edge to directly obtain machine diagnosis results (e.g., normal vs. abnormal), and only extracted features or selected raw data will be transmitted to the cloud for further analytics (e.g., remaining life prognosis). To improve the affordability and applicability of edge computing, this study proposed a novel and deployable edge device that adopts a feature-based Tiny Machine Learning (Tiny ML) model to achieve vibration data processing and machine condition monitoring while maintaining the modeling generalizability and computing efficiency. It integrates a Microelectromechanical Systems (MeMS) accelerometer for vibration data sampling (up to 20 kHz) and a microcontroller for edge computing and communication to the cloud. The integral IoT system, which involves the edge device, cloud services, and wireless communication between the edge and cloud is presented, emphasizing its plug-and-play capability. In this framework, MQTT protocol is adopted for communication among edge, cloud, and end users, allowing processed signal information and machine diagnosis results to be published to end users in real-time. extensive experiments have been conducted in the context of industrial motor condition monitoring and faul

关键词： edge computing Tiny ML machine condition monitoring fault diagnosis

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An Innovation Development of Decentralized Prove Piercing Data Recuperation Using Improved Red in Mobile grid computing 2

An Innovation Development of Decentralized Prove Piercing Da...

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2nd ieee international conference on Distributed computing and electrical Circuits and electronics, ICDCeCe 2023

作者： Karthikeyan, S. Thomas, Merin Faculty of Engineering and Technology Department of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798350347456

The recent advancements in mobile computing have opened up the possibilities of decentralized data recovery in mobile grid computing. With the help of improved Red (Recovery of erased Data) technique, data recovery can be done in a decentralized manner. This method is a combination of distributed computing, data replication, and data recovery algorithms which improves the data recovery process. The improved Red technique uses distributed computing to replicate the data and store it in multiple nodes in the grid. This helps to ensure that the data is distributed and available in multiple nodes for recovery. Data recovery is done by the Red algorithm which traverses the grid and identifies the nodes which have the data and then recovers it. The algorithm uses a technique called "greedy search"to identify the nodes which have the data. This helps to reduce the time and cost associated with the recovery process. The improved Red technique also makes use of data replication which helps to improve the data recovery process. The data is replicated and stored in multiple nodes which helps to improve the speed of data recovery. The replication process helps to ensure that the data is always available and can be recovered quickly. The improved Red technique also makes use of distributed computing to improve the scalability of the data recovery process. The distributed computing helps to ensure that the data recovery process can be done efficiently and quickly. The data recovery process can also be done on a large scale which helps to improve the speed of data recovery. © 2023 ieee.

关键词： Recovery

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