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Design and Optimization of an Integrated and Trustworthy WLAN Network Architecture Based on SDN for Power Systems 24

Design and Optimization of an Integrated and Trustworthy WLA...

引用

2024 international conference on Cloud computing and Big Data, ICCBD 2024

作者： Liu, Yuanlong Guan, Ti Zhang, Jian Liang, Dong Guan, Qingqin State Grid Shandong Electric Power Company China State Grid Shandong Electric Power Company Jinan Power Supply Company China

ISBN: (纸本)9798400710223

With the advancement of smart grid construction and digital transformation, higher requirements have been imposed on wireless communication networks in power systems. To address the issues of hardware ossification and complex network management faced by traditional networks, this paper investigates the architecture of trusted wireless local area network (WLAN) for power systems using the software-defined networking approach. The proposed architecture realizes unified management and security protection of the network through SDN centralized control and WAPI security authentication protocol. In addition, heterogeneous power network device decoupling and power grid communication protocol standardization are discussed to enhance device interoperability. To further optimize networks serving power system applications, this paper analyzes existing problems and proposes a series of optimization techniques and methods in five aspects - access control, load balancing, opportunistic routing, service migration/backup, and network security, so as to improve network management efficiency, load balancing capability, routing efficiency, service reliability and security. The research provides architectural support and optimization guidance for building more efficient, secure and reliable wireless communication networks in power systems. © 2024 ACM.

关键词： Smart power grids

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Efficient anomaly intrusion detection using Transformer based GAN network 7

Efficient anomaly intrusion detection using Transformer base...

引用

7th IEEE international Electrical and Energy conference, CIEEC 2024

作者： Feng, Junyao Wang, Chaohong Xue, Hao Zhang, Lijun Qinghai University Department of Computer Technology and Applications Xining China Huanghe Hydropower Development CO. Ltd. Xining China

ISBN: (纸本)9798350359558

With the rapid development of power grid terminals technology and the continuous increase in threats of network attacks, network anomaly intrusion detection for power grid terminals has become more complicated and crucial. However, due to the large number of network protocol fields and diverse network behaviors, existing methods still face challenges. Therefore, this text proposed a network anomaly intrusion detection method based on TransGAN, which combines the ideas of generative adversarial networks and Transformer models, to learn the correlation between different types of network intrusion behaviors and capture the dependency relationship of the network data. Besides, XGBoost was utilized for feature extraction to reduce computational cost without compromising detection performance. The experimental results show that the proposed anomaly detection method achieved an accuracy of 84.64% on NSL-KDD, while reducing the computational cost of training and testing by 9% and 6% respectively. It makes a valuable contribution to the research and practice of network security in the field of power grid terminals. © 2024 IEEE.

关键词： Anomaly detection

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Explainable Knowledge Reasoning on Power grid Knowledge Graph 19th

Explainable Knowledge Reasoning on Power Grid Knowledge Grap...

引用

19th international conference on Advanced Intelligent computing Technology and applications (ICIC)

作者： Zhang, Yingyue Huang, Qiyao Zheng, Zhou Liao, Feilong Yi, Longqiang Li, Jinhu Huang, Jiangsheng Zhang, Zhihong Xiamen Univ Sch Informat Xiamen 361005 Fujian Peoples R China State Grid Fujian Elect Power Res Inst Fuzhou 350007 Fujian Peoples R China Kehua Data Co Ltd Xiamen 361006 Fujian Peoples R China State Grid Info Telecom Great Power Sci & Technol Fuzhou 350003 Fujian Peoples R China

ISBN: (纸本)9789819947607;9789819947614

The smooth operation of the power grid is closely related to the national economy and people's livelihood. The knowledge graph, as a widely-used technology, has made considerable contributions to power grid dispatching and query answering. However, explainable reasoning on grid defects datasets is still of great challenge, most models cannot balance effectiveness and explainablity. Therefore, their assistance in grid defects diagnosis is minimal. To address this issue, we propose the rule-enhanced cognitive graph for power grid knowledge reasoning. Our model consists of two modules: expansion and reasoning. For the expansion module, we take into consideration that path-based methods often ignore graph structure and global information and combine the local cognitive graph and global degree distribution. For the reasoning module, weprovide reasoning evidence from two aspects: logical rule learning for strong evidence and cognitive reasoning for possible paths. Experiment results on our grid defects dataset make known that our model achieves better performance with explainablity.

关键词： Power grid Knowledge Graph Knowledge Reasoning Cognitive Graph

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Energy-Efficient computing Offloading Policy for MEC-assisted Power Sensor Network: A D3QN Approach

Energy-Efficient Computing Offloading Policy for MEC-assiste...

引用

2023 international conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Guan, Ti Yao, Yushun Yuan, Chao Liu, Fuhao Liu, Yirong Gu, Rentao State Grid Shandong Electric Power Company Jinan China Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing China State Grid Laiwu Electric Power Supply Company Jinan China State Grid Binzhou Electric Power Supply Company Binzhou China

ISBN: (纸本)9798350312492

With the deep and close integration of massive renewable and controllable terminals into the next generation smart power grid, the amount of data and various applications with different quality requirements will increase greatly, which will be tough challenges for the power sensor network to provide real-time data collecting and processing, global monitoring, and quick response, etc. Meanwhile, due to the limitation in energy supplement and computing capacity, it is a second issue for the sensor network how to work in an energy-efficient way. In this paper, our work sets out to study a reinforcement learning (RL) based computing offloading policy in the mobile edge computing (MEC) assisted power sensor network. By jointly optimizing task scheduling and resource allocation, we propose a new scheme to optimize data latency and energy efficiency. The optimization problem is modeled as a Markov decision process (MDP), and Dueling Double Deep Q Network (D3QN) algorithm is employed to solve this MDP problem. Simulation results demonstrate the effectiveness of the proposed algorithm and its outperformance in reduction of data latency and energy consumption as well as convergence and stability, compared with other benchmarks. © 2023 IEEE.

关键词： Markov processes

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Empowering Smart Homes with Fog computing for IoT Connectivity

Empowering Smart Homes with Fog Computing for IoT Connectivi...

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2024 international conference on Decision Aid Sciences and applications, DASA 2024

作者： Ahmed, Amjed Abbas Najim, Ali Hamza Mahdi, Ali Jafer Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Al-Diwaniyah Iraq AI-Zahraa University for Women Department of Scientific Affairs Bangi43600 Malaysia College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Innovative grid technology leverages Information and Communication Technology (ICT) to enhance energy efficiency and mitigate losses. This paper introduces a 'novel three-tier hierarchical framework for smart homes within the Internet of Things (IoT)' ecosystem, addressing the current shortage of intelligent solutions that underutilize IoT advantages. Our framework's primary objective is to elevate smart homes to the microgrid level, enabling the seamless integration from the microgrid's renewable distributed energy sources and attaining maximum energy efficiency. In addition to traditional data processing, we propose the application of fog computing in smart homes. Through a rigorous simulation using real smart meter datasets, our study demonstrates that fog computing, mainly when using predictive filtering, may drastically cut down on the amount of data being sent and the load on the home's network. This innovation holds immense potential for revolutionizing energy management and resource allocation in the context of smart homes, thus contributing to a sustainable and efficient future. This research represents a critical step towards harnessing the power of IoT and fog computing in smart grids and homes, offering a promising path towards more intelligent, eco-friendly, and energy-efficient living spaces. © 2024 IEEE.

关键词： Smart homes

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Edge computing-Based Adaptive Data Compression Method for D-PMU in Digital Distribution Networks 2nd

Edge Computing-Based Adaptive Data Compression Method for D-...

引用

2nd international conference on Smart Electrical grid and Renewable Energy, SEGRE 2024

作者： Liu, Yinliang Duan, Shuyin Yuanlv, Zerui Yu, Lei Yang, Hao Yu, Binrong Bu, Yuntao Guangzhou510663 China China Southern Power Grid Co. Ltd. Guangzhou510663 China Key Laboratory of Smart Grid of Ministry of Education Tianjin University Tianjin300072 China

ISBN: (纸本)9789819619641

The widespread use of distribution-level phasor measurement units (D-PMUs) in digital distribution networks has introduced significant pressure on communication and storage systems due to the high precision and data transmission rates of these devices. This paper presents an adaptive compression algorithm for D-PMU data from edge computing devices in digital distribution networks. Utilizing a filter-based swing door trending compression algorithm combined with state discrimination methods, the proposed method applies distinct compression strategies for stable and fault operational states, achieving adaptive data compression. Validation of the algorithm’s effectiveness was performed through testing on system data during both stable and fault conditions. The results demonstrate that the proposed method effectively reduces the load on communication and storage systems while maintaining data accuracy and real-time performance, thereby proving its feasibility and efficacy in practical applications. This approach ensures that critical data is preserved during fault conditions while efficiently compressing data during stable operation, thus enhancing the overall efficiency of digital distribution networks. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Phasor measurement units

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SG-CIM Model Verification and Validation Framework in Business Middle Platform 8

SG-CIM Model Verification and Validation Framework in Busine...

引用

8th IEEE international conference on Smart Cloud, SmartCloud 2023

作者： Lv, Jun Chen, Lei Lv, Guangxian Liu, Riliang Xu, Chongyou Lu, Yiming Du, Jian State Grid Corporation of China Co. Ltd Beijing China State Grid Zhejiang Electric Power Co. Ltd Zhejiang Hangzhou China State Grid Shanghai Energy Interconnection Research Institute Co. Ltd. Shanghai China Ningbo Supply Power Co. State Grid Zhejiang Electric Power Co. LTD. Zhejiang Ningbo China

ISBN: (纸本)9798350313505

With the continuous development of State grid middle platforms and expansion of power grid applications, SG-CIM model verification has received increasing attention. It plays a crucial role in ensuring the data accuracy and consistency for information applications tailored to the needs of different professional departments in the power industry. This paper provides an overview of the SG-CIM middle platform, emphasizing its crucial role in supporting data sharing and analysis applications between different professional and operational units. We outline key steps involved in the verification and validation process for SG-CIM models, including input checks, model validation, sensitivity analysis, and model evaluation modules. Furthermore, the paper also highlights how this framework fosters collaboration between different parts of an organization by ensuring that data used in these applications is accurate and consistent across different business processes. ©2023 IEEE.

关键词： Sensitivity analysis

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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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Performance Investigations of PV grid-Integrated Modular Multilevel Inverter 7

Performance Investigations of PV Grid-Integrated Modular Mul...

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7th international conference on computing Methodologies and Communication, ICCMC 2023

作者： Parimalasundar, E. Sravanti, P. Razzak, S.K. Abdul Abhigna, P. Naga Maruthi Hussain, S.M.M.D. Zubair Mandal, Ram Krishna Electrical and Electronics Engineering Sree Vidyanikethan Engineering College Tirupati India

ISBN: (纸本)9781665464086

This paper proposes a single-phase multilevel inverter with seven levels output for grid connected photovoltaic applications. With the appropriate gate signal configuration, the seven-level inverters which are proposed keep producing seven-level alternating current (AC) root mean square output voltages. In this photovoltaic (PV) based multilevel inverters are currently focusing on minimizing the number of power electronics switches and DC input sources with an acceptable total harmonic distortion of the voltage waveform output in order to reduce expenses and losses. The proposed seven-level inverter can reduce power dissipation and voltage stresses in power semiconductor converters. The proposed converter has fewer power switches and is more dependable. © 2023 IEEE.

关键词： Electric inverters

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Dynamic Scalability Mechanisms for Microservices in Federated Cloud Platform 5

Dynamic Scalability Mechanisms for Microservices in Federate...

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5th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Bi, Qing Liu, Yiyi Zhang, Lishou Kang, Kai Yang, Di Min, Sikai Information and Communication Company of State Grid Shanghai Electric Power Company State Grid Shanghai China

ISBN: (纸本)9798350310603

In recent years, cloud platforms tailored for the development of microservices applications have garnered significant attention. Traditional cloud computing platforms suffer from remoteness from end-users and unreliable network connectivity, making them ill-suited for meeting real-time task requirements. Moreover, the complex and dynamic nature of cloud computing environments, coupled with the collaborative nature of microservices applications, introduces a substantial risk of service failures in cloud services. Existing cloud platforms primarily rely on service load elasticity to mitigate service failures but fail to consider the dynamic nature of federated cloud clusters, resulting in service oscillations and delayed fault handling, thereby compromising the reliability of microservices applications in federated clouds. To address these challenges, we propose a dynamic microservices adjustment framework based on the MAPE control model. The framework regularly collects runtime service data and proactively identifies and adjusts abnormal services. It employs a dynamic window-based elasticity approach, enhanced by fast scaling and slow shrinking adjustment strategies, to enhance service stability in the face of fluctuating workloads. In real-world operational scenarios, experimental results demonstrate the effectiveness of the proposed approach compared to traditional methods. © 2023 IEEE.

关键词： Elasticity

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