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共 9706 条记录，以下是61-70 订阅

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Integrative Optimization Framework for Strategic distributed Generation Placement and Sizing to Enhance Loss Minimization and Voltage Stability in Power Distribution Networks

Integrative Optimization Framework for Strategic Distributed...

引用

Intelligent Control, computing and Communications (IC3), international conference on

作者： Kashi Sai Prasad Aravinda K Jay Singh Atul Singla Savita Kumari Sajjad Ziara Gotlur Karuna Department of CSE-AI&ML MLR Institute of Technology Hyderabad Telangana India Electronics and Communication Engineering New Horizon College of Engineering Bangalore India Dept. of EEE GL Bajaj Institute of Technology and Management Gr. Noida U.P. India Lovely Professional University Phagwara India Department of Electrical Electronics & Communication Engineering Galgotias university Gerater Noida Uttar Pradesh India Radiology Techniques Department College of Medical Technology The Islamic University Najaf Iraq Department Computer Science Engineering (AIML) Gokaraju Rangaraju Institute of Engineering and Technology Hyderabad India

ISBN: (数字)9798331527495

ISBN: (纸本)9798331527501

The location and scale of distributed generation (DG) units are critical for minimizing losses and enhancing the performance of distribution networks. This research establishes the optimization approach for establishing the optimal location of the dg, especially solar PV and wind turbines using the IEEE 37-bus system as the test feeder. Having this in mind, this work applied a unified approach based on Pandapower, a versatile Python-based power systems tool, combining optimization and power flow computations. The algorithm analyzes a range of DG technologies and penetration levels to determine the effectiveness of decreasing loss, considering variability in renewable generation and load demand to increase realism. The single-tool forms presented in the paper show practical application potential and offer a better understanding of the best approaches to DG integration that would benefit grid stability and energy efficiency in the distribution networks of the future.

关键词： Renewable energy sources Electric potential Voltage fluctuations Uncertainty Distribution networks Power system stability Stability analysis distributed power generation Wind turbines Optimization

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Research on the Design and Implementation of Financial ERP System Based on grid Algorithm 25

Research on the Design and Implementation of Financial ERP S...

引用

Proceedings of the 2025 4th international conference on Big Data, Information and Computer Network

作者： Xinyue Zhang Zhe Yang Shuai Zhang Beiing China-Power Information Technology co. LTD Beijing China

ISBN: (纸本)9798400712425

Finance informatization is an important method that helps managers in companies to enhance the decision-making quality along with their efficiency. The finance ERP system enriched with the help of the grid algorithms facilitates data analytics and the following of funds, with the assistance of such computational resources, the status of which is that the deployment of computational resources is done effectively and the task scheduling model is efficient. During looking at these grid algorithms on a more detailed level, these are results that were obtained when classification methods such as dynamic scheduling algorithms and load balancing algorithms were performed, the ones of which can particularly be used for parallel and distributed computing along with a multitude of services or enhancing the financial system performance. An experiment's design included explicit environmental setups that were outlined and a myriad of test datasets, which facilitated the assessment of comparative efficiency. The response time and processing efficiency the ERP system achieves using grid algorithms are the main causes of enhanced system performance metrics (far beyond the traditional thresholds). Besides the smoothness and cost-effectiveness of the system, the new system will result in an economic advantage in the market for a design concept that also will provide enterprises with the outline of and help in the implementation of the system that will solve a variety of financial issues they face. The study result indicates refreshed views and suggestions for the future economic management, the result of which will be efficient financial decisions and better use of the resources.

关键词： grid algorithm

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Enhancing grid Resilience Entangled with Federated Learning for Secure Data Aggregation in Smart grids

Enhancing Grid Resilience Entangled with Federated Learning ...

引用

international conference on Advanced Communication Technology (ICACT)

作者： Muhammad Adnan Khan School of Computing Skyline University College Sharjah United Arab Emirates

ISBN: (数字)9791188428137

ISBN: (纸本)9798331507602

Accurate load forecasting is crucial for the optimized operation and planning of smart power grids. However, the increasing penetration of renewable energy sources and the emergence of flexible loads like electric vehicles create significant uncertainties and complexities in load patterns. Traditional centralized forecasting models struggle with data privacy concerns, communication overheads, and lack of model adaptiveness. This paper proposes a privacy-preserving federated learning-based framework for short-term load forecasting in smart grids. Local machine learning models are trained on distributed private datasets across different stations of the grid and only the model parameters are communicated to a central server to create an aggregated global model for load forecasting, without exchanging any raw private data. The proposed approach harnesses edge resources efficiently through decentralized on-device training while providing enhanced accuracy and personalization over centralized models. Several experiments conducted on electricity consumption data validate the effectiveness of proposed approach in handling complex spatiotemporal load changes and generating station-specific adaptive forecasts. By adopting a decentralized approach, proposed methodology seeks to enhance grid resilience by preserving data privacy, mitigating security risks, and optimizing the efficiency of smart microgrid operations. The proposed solution can enable optimized capacity planning and retail pricing for sustainable grids of the future.

关键词： Adaptation models Accuracy Load forecasting Federated learning Predictive models Data models Smart grids Security Load modeling Resilience

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Intelligent data-driven methods for enhancing distributed excitation control in electrical grid

Intelligent data-driven methods for enhancing distributed ex...

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international conference on Energy, Power, Environment, Control and computing (ICEPECC 2025)

作者： Hafiz Ghulam Murtza Qamar Muhammad Imran Fareed Ahmad Ayesha Riaz Adil Ashraf Muhammad Zain Yousaf Imran Khan School of Electrical Engineering Yanshan University Qinhuangdao 066004 People's Republic of China Department of Electrical Electronics and Computer Systems University of Sargodha People's Republic of China Center for Renewable Energy and Microgrids Huanjiang Laboratory Zhejiang University Zhuji Zhejiang 311816 People's Republic of China

ISBN: (数字)9781837243150

This paper proposes a decentralized excitation control method based on synchronized estimation using asynchronous measurements from voltage/current transformers (VT/CT), addressing the challenges of decentralized excitation control caused by asynchronous updates. Due to the high cost and limited use of Phasor Measurement Units (PMUs), synchronized generator output measurements are often not feasible. The proposed method establishes a framework for decentralized excitation control that aligns with synchronized estimation in multi-machine power systems. It develops an estimation model for synchronized acquisition of excitation control feedback inputs, even under asynchronous sampling conditions. Simulation results using IEEE standard test systems demonstrate that synchronized estimated values offer a more accurate representation of the system’s status compared to asynchronous measurements, with better compatibility with the network structure. The findings show that decentralized excitation control based on synchronized estimation significantly enhances power system stability compared to traditional control methods that rely on asynchronous feedback.

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602933

The proceedings contain 158 papers. The special focus in this conference is on Life System Modeling and Simulation and Intelligent computing for Sustainable Energy and Environment. The topics include: A Method for Evaluating the Operating Health of Wind Turbines Under Wake Effect;toward Next-Generation Buildings: A Review of Renewable Energy Integration and Intelligent Building Energy Management Technologies;improving the Construction of a Multi-modal Underwater Image Recognition System for Anomaly Detection in Nuclear Power Plant Cooling Source Areas;A Novel Anti-noise Fault Diagnosis Method for Nuclear Energy Steam Turbine Based on VCformer;Short-Term Photovoltaic Power Forecasting Using Multi-timescale Information Based FFTformer Model;wind Power Forecasting Model Based on Feature Processing and Deep Hybrid Kernel Extreme Learning Machine;optimal User-Side Energy Arbitrage Strategy in Electricity Market with Accurate Battery Model Using Benders Decomposition;a Novel distributed Economic Dispatch Method for Smart grid with Time-Varying Feedback Gain;benefits, Barriers, and Human Factors of V2X Implementation – A Brief Review;a General Pattern of Permanent Magnet Arrangement for Design Optimization of a Reluctance Magnetic Gear with Enhanced Torque Density for Electric Vehicles;wind Power Scheduling Deviation Compensation Based on Dual-Frequency Pulse Control;a Comprehensive Simulation and Validation of Single Particle Aging Mechanism Model for Lithium-Ion Batteries;semi-supervised State of Health Estimation for Lithium-Ion Batteries via Dynamical Self-encoding;a Reduce-Order Model to Understand the Multiscale Coupling of Battery Electrochemical-Thermal Performance;RUL Prediction for Lithium-Ion Batteries Based on Sequence Decomposition and Transformer Networks;An Estimation Method of State of Health of Sodium-Ion Batteries Based on TCN.

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602315

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

8th International Conference on Life System Modeling and Sim...

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8th international conference on Life System Modeling and Simulation, LSMS 2024 and 8th international conference on Intelligent computing for Sustainable Energy and Environment, ICSEE 2024

ISBN: (纸本)9789819602247

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Advances on P2P, Parallel, grid, Cloud and Internet computing: Proceedings of the 11th international conference 1

引用

丛书名： Lecture Notes on Data Engineering and Communication Technologies 1

2016年

作者： Fatos Xhafa, Leonard Barolli, Flora Amato (eds.)

ISBN: (纸本)3319491083;9783319491080

P2P, grid, Cloud and Internet computing technologies have been very fast established as breakthrough paradigms for solving complex problems by enabling aggregation and sharing of an increasing variety of distributed computational resources at large scale. The aim of this volume is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to P2P, grid, Cloud and Internet computing as well as to reveal synergies among such large scale computing paradigms. This proceedings volume presents the results of the 11th international conference on P2P, Parallel, grid, Cloud And Internet computing (3PGCIC-2016), held November 5-7, 2016, at Soonchunhyang University, Asan, Korea

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Research and Application of Power Digital Control Platform Based on Big Data 24

Research and Application of Power Digital Control Platform B...

引用

Proceedings of the 2024 4th international conference on Big Data, Artificial Intelligence and Risk Management

作者： Xiaoxia Liu State Grid East Inner Mongolia Information & communication company Hohhot Inner Mongolia China

ISBN: (纸本)9798400709753

By applying cloud storage, big data, distributed computing and other technologies, integrating business data and real-time data from departments such as marketing, scheduling, and production in power operation, a power production big data platform has been constructed, achieving functions such as metadata modeling, data cleaning, data extraction, DM (Data Mining), data analysis, data presentation, and data services. By utilizing the power production big data platform, the problems in power production operation and inspection management have been addressed, An Corresponding ***-time power production control system that monitors, controls, and analyzes various abnormal power situations has been implemented, achieving functions such as fault tripping control, shutdown control, load control, low voltage control, three-phase imbalance control, risk assessment and warning, reliability and benefit analysis, providing favorable technical support for power operation, maintenance, and maintenance management.

关键词： Data processing and analysis

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TruChain: A Blockchain-based Access Control to Improve the Security of Smart Water grid Systems

TruChain: A Blockchain-based Access Control to Improve the S...

引用

international Communication Systems and Networks and Workshops, COMSNETS

作者： Susmita Mondal Suchetana Chakraborty Department of Computer Science and Engineering Indian Institute of Technology Jodhpur

ISBN: (数字)9798331531195

ISBN: (纸本)9798331531201

Water is a significant resource in day-to-day life, and it usually requires technological association for comprehensive management. Smart Water grids (SWG) typically use cyberphysical systems (CPS) to monitor several parameters associated with water quality and distribution, leveraging the possibility of performing remote operations. For robust architecture, remote operations rely on application-specific sensors, communication networks, edge control, and cloud computation. Needless to say, the centralized control of edge and cloud infrastructure is prone to attacks and failures, such as unauthorized access or single-point-of-failure. We propose TruChain, a Blockchain-based access control mechanism to eliminate the probability of access takeover and aggregate quorum-based validation on sensory data for transparent provenance reliability. We also provide access revocation to strengthen security by restricting access to sensitive data stored in a privately distributed cloud. We believe our solution has empirical decentralization and a verifiable authorization method by maintaining a tamper-evident, auditable trail of interactive events, building trust without third-party intervention.

关键词： Cloud computing Smart contracts Systems architecture Water quality Throughput Reliability Sustainable development Water resources Intelligent sensors Monitoring

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