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共 8967 条记录，以下是51-60 订阅

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Short-Term Power Load Forecasting based on Distilled Temporal Convolutional Networks

Short-Term Power Load Forecasting based on Distilled Tempora...

引用

IEEE international conference on Pervasive computing and Communications (PerCom)

作者： He, Yu Luo, Fengji Yip, Lam Christine Ranzi, Gianluca Univ Sydney Sch Civil Engn Sydney NSW 2006 Australia

ISBN: (纸本)9798350304367;9798350304374

Short-Term Load Forecasting (STLF) aims to predict the future power load of a single household, supporting various downstream home management applications. Recently, deep learning models have become popular for STLF due to their proficiency in extracting nonlinear patterns from time series data. However, the increasing complexity of these models hinders their deployment in local household settings. To address this, we introduce a knowledge distillation- based approach in STLF, enabling the transfer of knowledge from a large model to a smaller one without compromising forecast accuracy. The proposed method employs a teacher-student network for data distillation, where a sophisticated 'teacher' network conveys forecasting insights to a small 'student' network, facilitating its use on local devices with limited resources. We conducted experiments and comparative studies to validate this approach, demonstrating its effectiveness while ensuring deployment feasibility and accuracy.

关键词： short-term load forecasting knowledge distillation demand side management deep learning smart grid

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Vertex Centric Weighted Edge Index to Accelerate Weighted Graph Traversal 4

Vertex Centric Weighted Edge Index to Accelerate Weighted Gr...

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4th international conference on Consumer Electronics and Computer Engineering, ICCECE 2024

作者： Lin, Jianchao Ren, Chunhui Liu, Siyan State Grid Smart Grid Research Institute Co. Ltd. State Grid Laboratory of Grid Advanced Computing and Applications Beijing China

ISBN: (纸本)9798350384062

Indexing is an important technique to optimize graph database performance. However, indexing in existing graph databases focuses mainly on property-value based query, and has not drawn much attention on graph traversal. We propose a new indexing technique, which maintains sorted indexing of vertex and weight values of the vertex's adjacent edges. With this proposed vertex centric adjacent weighted edge index, graph traversal algorithms based on weight values like Dijkstra's algorithm and Prim's algorithm have significant performance gains. © 2024 IEEE.

关键词： Graph Databases

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Enhancing MPI Communication Efficiency for grid-Based Stencil Computations

Enhancing MPI Communication Efficiency for Grid-Based Stenci...

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2024 IEEE international conference on computing, Semiconductor, Mechatronics, Intelligent Systems and Communications, COSMIC 2024

作者： Goudar, Santosh Iranagouda Nayaka, Premkumar Sj Girish, K.K. Bhowmik, Biswajit National Institute of Technology Karnataka Maharshi Sushrut CAS Lab BRICS Lab Department of Computer Science and Engineering SurathkalBharat Mangalore India

ISBN: (纸本)9798331517892

In parallel computing, where efficiency and speed are crucial, the Message Passing Interface (MPI) is a fundamental paradigm for managing large-scale distributed memory systems. MPI is critical to complex computational tasks, particularly in grid-based computations that solve intricate numerical problems by discretizing spatial domains into structured grids. However, MPI Cartesian communicators exhibit limitations in handling these computations effectively, especially when managing large-scale data exchanges and complex stencil patterns. This paper addresses these challenges by presenting an integrated approach that combines MPI collective and Cartesian communication methods. The proposed solution simplifies data distribution, eliminates redundant interfaces, and enhances communication efficiency. Experimental results show a 43% reduction in execution time and a 40% decrease in communication overhead, with scalability improvements achieving 12.5x speedup using 64 processes. These quantitative outcomes demonstrate the advan-tages of the proposed method over conventional MPI Cartesian approaches, establishing it as a reliable framework for advancing High-Performance computing (HPC) capabilities in grid-based applications. © 2024 IEEE.

关键词： Message passing

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Application of Intelligent Techniques in Smart grid Automation 4

Application of Intelligent Techniques in Smart Grid Automati...

引用

4th international conference on Power, Control and computing Technologies, ICPC2T 2025

作者： Babu, Manish Kumar Ray, Papia Swain, Anita Department of EE VSSUT Burla India Department of ECE BCE Khordha India

ISBN: (纸本)9798331530402

The smart grid is an advanced power system network that integrates cutting-edge technologies to enable efficient, reliable, and sustainable energy generation, distribution, and utilization. This paper provides a comprehensive survey of intelligent techniques, including machine learning for load forecasting and fault detection, optimization algorithms for demand-side management and renewable energy integration, and data analytics for real-time grid monitoring and decision-making. These approaches enhance grid performance by improving flexibility, operational efficiency, and resilience to disruptions. Specific examples, such as predictive maintenance using machine learning and optimization-based energy scheduling for microgrids, are discussed to illustrate their practical applications. The paper also explores challenges like cybersecurity and data quality, offering potential mitigation strategies. Additionally, successful implementations and their outcomes are highlighted, showcasing the transformative impact of intelligent techniques on smart grid automation. Finally, future research directions, such as leveraging blockchain for secure transactions and quantum computing for advanced optimizations, are identified to guide advancements in this field. © 2025 IEEE.

关键词： Qubits

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Multiport DC to AC Inverter with Intelligent Controller Integration for PV-Based grid Systems 7

Multiport DC to AC Inverter with Intelligent Controller Inte...

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7th international conference on Circuit Power and computing Technologies, ICCPCT 2024

作者： Chitra, L. Kavitha, G. Prakash, S. Vinayaka Missions Research Foundation Aarupadai Veedu Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu India

ISBN: (纸本)9798350372816

Modern power management solutions are desperately needed, as demonstrated by the exponential growth of photovoltaic (PV) systems for grid applications. The innovative multiport DC to AC inverter technology introduced in this project is specifically designed for PV-based grid configurations as a response. With four DC ports and one AC port, this project presents a multiport DC to AC inverter system intended for grid applications based on PV technology. Battery banks, PV arrays, supercapacitors (SC), and electric vehicle (EV) batteries may all be connected more easily thanks to the DC ports. Three power switches with PWM rectifiers running at fundamental frequency are used to link the EV port (EV) of a three-phase inverter to the switching nodes. A PI controller integrates a Luo converter that is managed by a solar panel. Bidirectional converters inside the DC connection link supercapacitors and batteries, enabling operation at times when solar panels are not in use and recharging when solar power is available. An Artificial Neural Network (ANN) controller synchronizes the three power sources, which are combined into a three-phase inverter for grid integration and DC to AC conversion. Comprehensive power control across the several DC ports is made possible by this integrated MPC inverter, which also makes communication with the electrical grid easier. With a voltage gain of 1:8, and an efficiency of 92%, the proposed Luo converter is quite effective. © 2024 IEEE.

关键词： Solar power generation

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Research on Pseudo Measurement Generation Method Based on 1D-CNN and Transfer Learning for Medium-Voltage Distribution Networks 2

Research on Pseudo Measurement Generation Method Based on 1D...

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2nd international conference on Cyber-Energy Systems and Intelligent Energy, ICCSIE 2024

作者： Sun, Zhiqing Lei, Shuya Yi, Xuan Zhang, Wense Wang, Yishen Ni, Xiabing Wang, Qifeng Liang, Xiao Huang, Yan State grid Hangzhou power supply company Zhejiang China State Grid Smart Grid Research Institute Co. Ltd. State Grid Laboratory of Grid Advanced Computing and Applications Zhejiang China State Grid Smart Grid Research State Grid Laboratory of Grid Advanced Computing and Applications Zhejiang China Tsinghua University Sichuan Energy Internet Research Institute Chengdu China

ISBN: (纸本)9798350373318

With the increasing scale and complexity of new power systems, ensuring the safe and optimized operation of distribution networks becomes particularly important. Due to constraints such as economic factors, the comprehensive deployment of real-time measurement devices in mediumvoltage distribution networks faces significant challenges, resulting in insufficient observability of the distribution network. To address this issue, this paper proposes a method that combines one-dimensional convolutional neural networks (1D-CNN) with transfer learning for pseudo measurement generation. This method first constructs a 1D-CNN pseudo measurement generation model using a large amount of historical measurement data, and then trains and optimizes the 1D-CNN model through transfer learning to achieve pseudo measurement generation even under topological changes. The test results of actual engineering data demonstrate that the proposed method can generate high-frequency pseudo measurement data for nodes in medium-voltage distribution networks in real time, accurately, and efficiently. Additionally, the proposed method exhibits good adaptability when the distribution network topology changes. In this way, this paper provides a new technical path for the perception of the operational status of medium-voltage distribution networks and provides technical support for the safe and optimized operation of distribution networks. © 2024 IEEE.

关键词： Power distribution networks

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Data Processing Optimization of Power grid Dispatching Control Cloud Based on Edge-Cloud Collaborative computing 3

Data Processing Optimization of Power Grid Dispatching Contr...

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3rd IEEE international conference on Power, Electronics and Computer applications, ICPECA 2023

作者： Sheng, Lei Wang, Chunying Liu, Yan Zhang, Ningning Wang, Zhaohe State Grid Henan Electric Power Company Information & Telecommunication Company Zhengzhou China

ISBN: (纸本)9781665472784

Cloud computing technology is widely used in power grid systems. In response to the data with strict delay requirements and a large amount of data generated by the operation of the power grid system. New challenges are raised to the delay of business processing. In order to achieve the goal of minimizing the system average latency time of task processing, based on the power grid dispatching cloud architecture, a delay optimization method based on SDN edge-cloud collaborative computing is proposed. The goal is to minimize the system average delay of task processing. Introduce continuously variable edge and cloud and task distribution coefficients. The delay optimization problem is transformed into the task allocation coefficient optimization problem. And finally get the task allocation optimization strategy based on the model calculation. The experimental results show that when the edge node tasks are reasonably loaded into the cloud center for processing, the system delay of the business can be effectively reduced. Compared with the previous methods, the edge-cloud collaborative computing method proposed in this paper reduces the system delay and utilizes the control mechanism of SDN that can coordinate cloud computing and edge computing. The algorithm can be used in the power system cloud platform system based on SDN. © 2023 IEEE.

关键词： Edge computing

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international conference on Integrated Circuits, Communication, and computing Systems, ICIC3S 2024 - Proceedings

International Conference on Integrated Circuits, Communicati...

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2024 international conference on Integrated Circuits, Communication, and computing Systems, ICIC3S 2024

ISBN: (纸本)9798350364088

The proceedings contain 92 papers. The topics discussed include: optimization of energy management and anomaly detection in smart grid analytics using deep learning;optimization of energy management and anomaly detection in smart grid analytics using deep learning;design and evaluation of low power 2 to 4 decoder circuit using three and four transistors NAND gates;analyzing distinct change detection methods for identifying spectral and spatial variation using planetscope satellite data;a novel approach for approximating the dynamics of fisher's equation based on physics-informed neural networks;decoding the eye: ai-driven diabetic retinopathy classification for precision healthcare;and security system for IoT applications based on hybrid fuzzy possibility c-means clustering.

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Research on Non-intrusive Load Identification Method Based on Edge computing 7

Research on Non-intrusive Load Identification Method Based o...

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7th IEEE international conference on Information Systems and Computer Aided Education, ICISCAE 2024

作者： Jiang, Zhibo Wang, Jie Zhang, Jiajun Mao, Zhixiang Zhao, He State Grid Zhejiang Electric Power Co. LTD. Kaihua County Power Supply Company Kaihua Zhejiang China

ISBN: (纸本)9798350350760

This study proposes a non-intrusive load identification method based on edge computing. By constructing a repository of load steady-state characteristics and employing temporal and spectral feature analysis techniques, precise identification of operational states of various electrical appliances in household or industrial environments is achieved. The study introduces a load monitoring technology roadmap tailored for edge computing frameworks and develops a platform for load equipment analysis and testing. Furthermore, the paper explores load identification methods based on statistical and machine learning algorithms (such as XGBoost and enhanced AlexNet network), validating their effectiveness and reliability through experiments in practical applications. This research not only offers novel insights into load management for smart grids but also advances the application of edge computing technology in the energy sector. ©2024 IEEE.

关键词： Domestic appliances

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Proceedings - 2024 international conference on Smart grid and Energy, ICSGE 2024

Proceedings - 2024 International Conference on Smart Grid an...

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2024 international conference on Smart grid and Energy, ICSGE 2024

ISBN: (纸本)9798350308945

The proceedings contain 12 papers. The topics discussed include: determining user's indirect carbon emissions considering green electricity trading decomposition;influence of damp status on leakage current of ZnO lightning arrester;fault point detection for recovery planning of resilient grid;fault point detection for recovery planning of resilient grid;a novel supplying strategy of isolated power generation for offshore islands;research on transparent electrodes for flexible perovskite solar cells;deadbeat control with parameter identification for extended phase-shift based DAB converter;RFID temperature measuring system design for high-voltage switchgear and its reliability;peer-to-peer (P2P) energy trading prototype implementation with private Ethereum blockchain and WebSocket;and synthesis and characterization of iron oxide nanoparticles for bio-medical and neuromorphic computing applications.

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