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1. |
Record Nr. |
UNISALENTO991004128749707536 |
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Autore |
Craca, Clotilde |
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Titolo |
Le possibilità della poesia : Lucrezio e la Madre frigia in De rerum natura II, 598-660 / Clotilde Craca |
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Pubbl/distr/stampa |
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ISBN |
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Descrizione fisica |
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Collana |
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Disciplina |
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Soggetti |
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Divinità nella letteratura |
Lucrezio Caro, Tito - De rerum natura - Saggio critico |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliografia: p. [161]-167. Indici. |
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2. |
Record Nr. |
UNINA9910830771803321 |
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Autore |
Shafiee Qobad |
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Titolo |
Microgrids : Dynamic Modeling, Stability and Control |
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Pubbl/distr/stampa |
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Newark : , : John Wiley & Sons, Incorporated, , 2024 |
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©2024 |
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ISBN |
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1-119-90623-7 |
1-119-90621-0 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (446 pages) |
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Altri autori (Persone) |
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NaderiMobin |
BevraniHassan |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Acknowledgments -- Acronyms -- Chapter 1 Introduction -- 1.1 Overview -- 1.2 Microgrid Concept and Capabilities -- 1.3 Microgrid Structure -- 1.4 Microgrids in the Future Smart Grids -- 1.5 Microgrids‐Integrated Power Grids -- 1.6 Current Trends and Future Directions -- 1.6.1 Dynamic Behavior of MGs and Their Impacts on Power Grids -- 1.6.2 Microgrid‐Based Ancillary Services -- 1.6.3 Dynamic Modeling and Control -- 1.7 The Book Content and Organization -- References -- Part I Individual Microgrids -- Chapter 2 Microgrid Dynamic Modeling: Concepts and Fundamentals -- 2.1 Introduction -- 2.2 Dynamics and Modeling -- 2.3 Fundamental Analysis Tools and Requirements -- 2.3.1 State‐Space (Small‐Signal) Modeling -- 2.3.1.1 Finding Differential Equations -- 2.3.1.2 Park and Clark Transformations -- 2.3.1.3 Linearization -- 2.3.1.4 State‐Space Representation -- 2.3.1.5 Interconnecting Modules -- 2.3.2 Detailed Modeling -- 2.3.3 Simplification Methods -- 2.3.3.1 Truncation (Regular Perturbation) -- 2.3.3.2 Residualization (Singular Perturbation) -- 2.3.3.3 Aggregation -- 2.3.3.4 Sensitivity Analysis -- 2.3.4 Prony Analysis -- 2.3.5 Large‐Signal Modeling -- 2.4 Small‐Signal Modeling of Microgrid Components -- 2.4.1 DC-AC Converter (Inverter) -- 2.4.2 AC-DC Converter (Rectifier) -- 2.4.3 DC-DC Converter (Chopper) -- |
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2.4.4 LC Filter -- 2.4.5 Power Network -- 2.4.5.1 Virtual Resistor Calculation -- 2.4.6 Loads -- 2.4.6.1 Constant RL Impedance Load -- 2.4.6.2 Constant Power Load (CPL) -- 2.4.6.3 Motor Load -- 2.4.6.4 Active Load -- 2.4.7 Energy Resources and Storages -- 2.4.7.1 Wind Generation Unit -- 2.4.7.2 Photovoltaic Generation Unit -- 2.4.7.3 Battery -- 2.4.7.4 Super‐Capacitor -- 2.5 Small‐Signal Modeling of Microgrid Controllers -- 2.5.1 Primary Control Strategies. |
2.5.1.1 Grid‐Forming Strategy -- 2.5.1.2 Grid‐Following Strategy -- 2.5.2 Secondary Control -- 2.5.3 Higher Control Levels -- 2.6 Large‐Signal Modeling: An Example -- 2.6.1 Governing Equations on Synchronverter -- 2.6.2 Nonlinear State‐Space Representation -- 2.7 Summary -- References -- Chapter 3 Microgrid Dynamic Modeling: Overall Modeling and Case Studies -- 3.1 Introduction -- 3.2 Overall Microgrid Dynamic Modeling -- 3.2.1 Common Reference Frame -- 3.2.2 Microgrid General State‐Space Model -- 3.2.3 Grid Model -- 3.3 Small‐Signal Modeling of DC and AC Microgrids -- 3.3.1 A Grid‐Connected PV -- 3.3.2 Grid‐Connected AC Microgrids -- 3.3.3 Islanded AC Microgrids: The Detailed Model -- 3.3.4 Islanded AC Microgrids: A Sensitivity Analysis‐Based Simplified Model -- 3.3.4.1 Removing/Reconfiguration Process of Modules -- 3.3.4.2 DLFMs Comparison of the Detailed and Simplified Models -- 3.3.4.3 The Oscillatory DLFM Comparison -- 3.3.5 Islanded AC Microgrids: Aggregated Single‐Order Model -- 3.3.5.1 General Steps of Modeling -- 3.3.5.2 Virtual Swing Equation‐Based Single‐Order Model -- 3.3.6 Islanded DC Microgrid -- 3.4 Large‐Signal Modeling of Microgrids -- 3.4.1 Model Validation -- 3.4.2 Time‐Domain Simulations -- 3.5 Summary -- References -- Chapter 4 Microgrids Stability -- 4.1 Introduction -- 4.2 Stability Definition and Classification -- 4.3 Basic Requirements -- 4.3.1 Eigenvalue Analysis -- 4.3.2 Participation Matrix -- 4.3.3 Sensitivity Analysis -- 4.4 Small‐Signal Stability Analysis -- 4.4.1 Grid‐Connected PV -- 4.4.1.1 Sensitivity Analysis: LC Filter Parameters -- 4.4.1.2 Sensitivity Analysis: Coupling/Grid Line Length -- 4.4.1.3 Sensitivity Analysis: PLL Gains -- 4.4.1.4 Sensitivity Analysis: Current Control Gains -- 4.4.1.5 Sensitivity Analysis: DC Voltage Control gains -- 4.4.2 Grid‐Connected AC Microgrids. |
4.4.2.1 Sensitivity Analysis: Grid Strength Study -- 4.4.2.2 Sensitivity Analysis: Interaction of GFL DERs -- 4.4.3 Islanded AC Microgrids -- 4.4.3.1 Sensitivity Analysis of Droop Gains -- 4.4.3.2 Sensitivity Analysis of Virtual Impedance -- 4.4.3.3 Stability Analysis of Secondary Control -- 4.4.3.4 Sensitivity Analysis of GFL DER Parameters -- 4.4.3.5 Weakness of AC Microgrids -- 4.4.3.6 Relative Stability Improvement Using Grid‐Supporting Control Strategy -- 4.4.4 Islanded DC Microgrids -- 4.5 Transient Stability -- 4.5.1 Power Sharing Stability in AC Microgrids -- 4.5.2 Synchronverter Stabilization -- 4.5.2.1 Adaptive Backstepping Stabilizing Method -- 4.5.2.2 Simulation Results -- 4.6 Summary -- References -- Chapter 5 Microgrid Control: Concepts and Fundamentals -- 5.1 Introduction -- 5.2 Fundamentals and Requirements -- 5.2.1 Introduction to Control Systems -- 5.2.2 Control Objectives and Challenges -- 5.2.3 Control Architectures -- 5.3 Control Strategies for Power Converters -- 5.3.1 Introduction -- 5.3.2 Grid‐Following Power Converters -- 5.3.2.1 Current Control -- 5.3.2.2 Synchronization Algorithm -- 5.3.3 Grid‐Forming Power Converters -- 5.4 Hierarchical Control -- 5.4.1 The Control Hierarchy -- 5.4.2 Control Layers -- 5.5 Primary Control -- 5.5.1 Droop Control -- 5.5.1.1 Droop Control for Inductive Grids -- 5.5.1.2 Droop Control for Resistive Grids -- 5.5.1.3 Droop Control for Resistive-Inductive Grids -- 5.5.1.4 Discussion on the Conventional Droop Control -- 5.5.1.5 Droop Control for DC Grids -- 5.5.2 Virtual Impedance -- 5.5.3 |
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A Simulation Study for Primary Control of AC Microgrids -- 5.5.3.1 Case Study -- 5.5.3.2 Simulation Results -- 5.6 Secondary Control -- 5.6.1 Secondary Control Functions and Strategies -- 5.6.1.1 Secondary Control Functions -- 5.6.1.2 Secondary Control Strategies -- 5.6.2 Centralized Secondary Control. |
5.6.3 Distributed Secondary Control -- 5.6.3.1 Communication Network as a Graph -- 5.6.3.2 Average‐Based DISC -- 5.6.3.3 Consensus‐Based DISC -- 5.6.3.4 Event‐Triggered DISC -- 5.6.4 Decentralized Secondary Control -- 5.6.4.1 Washout Filter‐Based DESC -- 5.6.4.2 Local Variable‐Based DESC -- 5.6.4.3 Estimation‐Based DESC -- 5.6.5 A Simulation Study for Secondary Control of AC Microgrids -- 5.6.5.1 Case Study and Controller Implementation -- 5.6.5.2 Simulation Results -- 5.7 Central Control -- 5.8 Global Control -- 5.9 Summary -- References -- Chapter 6 Advances in Microgrid Control -- 6.1 Introduction -- 6.2 Advanced Control Synthesis -- 6.2.1 Advanced Control Techniques -- 6.2.1.1 Optimal Control -- 6.2.1.2 Robust Control -- 6.2.1.3 Nonlinear Control -- 6.2.1.4 Intelligent Control -- 6.2.2 Model Predictive Control -- 6.2.2.1 MPC for Microgrids -- 6.2.2.2 Finite Control Set Model Predictive Control -- 6.2.3 Model Predictive Control of DC Microgrids with Constant Power Loads -- 6.2.3.1 Case Study and Dynamic Modeling -- 6.2.3.2 Design Methodology -- 6.2.3.3 Real‐Time Hardware in the Loop Results -- 6.2.4 Hybrid Fuzzy Predictive Control for Smooth Transition of AC Microgrids -- 6.2.4.1 Case Study and Dynamic Modeling -- 6.2.4.2 Control System Design -- 6.2.4.3 Simulation Results -- 6.3 Virtual Dynamic Control -- 6.3.1 Concept and Structure -- 6.3.2 Virtual Synchronous Generator (VSG) -- 6.3.2.1 VSG Applications -- 6.3.3 Virtual Dynamic Control of DC Microgrids -- 6.3.3.1 Dynamic Improvement of DC Microgrids Using Virtual Inertia Concept -- 6.3.3.2 Case Study and Simulation Results -- 6.4 Resilient and Cybersecure Control -- 6.4.1 Microgrid as a Cyber‐Physical System -- 6.4.2 Communication Requirements -- 6.4.3 Cybersecurity -- 6.4.3.1 Network/Data Cyber Threats on Microgrids -- 6.4.3.2 Distributed Secondary Control Under Network Cyber Attacks. |
6.4.3.3 Cyberattack Detection -- 6.4.3.4 Cyberattack Mitigation -- 6.4.4 Event‐Triggered Control -- 6.4.4.1 Event‐Triggered Secondary Control of AC Microgrids -- 6.4.4.2 Physical and Control Layers -- 6.4.4.3 Secondary Control Design -- 6.4.4.4 Case Study and Simulation Results -- 6.5 Summary -- References -- Part II Interconnected Microgrids -- Chapter 7 Interconnected Microgrids: Opportunities and Challenges -- 7.1 Introduction -- 7.2 An Overview -- 7.3 Architectures of Interconnected Microgrids -- 7.4 Benefits, Challenges, and Research Fields -- 7.5 Operation of Interconnected Microgrids -- 7.6 Vacancies for Future Research -- 7.6.1 IMG Dynamic Modeling -- 7.6.2 IMG Stability Analysis -- 7.6.3 IMG Control -- 7.7 Summary -- References -- Chapter 8 Modeling of Interconnected Microgrids -- 8.1 Introduction -- 8.2 Interconnection Method -- 8.3 Module Modeling -- 8.3.1 Microgrid Modeling -- 8.3.1.1 Modeling of Secondary Control for CB‐IMGs -- 8.3.1.2 Other MG Modules -- 8.3.1.3 Overall MG Model -- 8.3.2 Interlinking Line Modeling -- 8.3.3 Back‐to‐Back Converter Modeling -- 8.3.3.1 AC Side of the BTBC -- 8.3.3.2 DC Side of the BTBC -- 8.3.3.3 Dependent Current and Voltage Sources -- 8.3.3.4 BTBC Power Part Interconnection -- 8.3.3.5 Power Controller -- 8.3.3.6 DC Voltage Controller -- 8.3.3.7 Synchronizing PLLs -- 8.3.3.8 Complete Interconnection of BTBC Modules -- 8.3.4 Circuit Breaker Modeling -- 8.4 Overall IMG Modeling -- 8.4.1 Comprehensive Modeling of CB‐IMGs -- 8.4.2 Comprehensive Modeling of BTBC‐IMGs -- 8.5 Model Validation -- 8.5.1 Model Validation Procedure -- 8.5.2 Real‐Time Simulator -- 8.5.3 Validation of CB‐IMG Modeling -- 8.5.3.1 |
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Case Study Information -- 8.5.3.2 Prony Analysis Results -- 8.5.3.3 Comparison Results -- 8.5.4 Validation of BTBC‐IMG Modeling -- 8.6 Reduced‐Order Models. |
8.6.1 Simplified Model Application in CB‐IMG Frequency Control. |
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3. |
Record Nr. |
UNINA9911047816103321 |
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Autore |
Kadoch Michel |
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Titolo |
Information Processing and Network Provisioning : Third International Conference, ICIPNP 2024 Spring, Beijing, China, June 14–16, 2024, Proceedings, Part II / / edited by Michel Kadoch, Mohamed Cheriet, Xuesong Qiu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2026 |
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ISBN |
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Edizione |
[1st ed. 2026.] |
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Descrizione fisica |
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1 online resource (558 pages) |
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Collana |
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Communications in Computer and Information Science, , 1865-0937 ; ; 2417 |
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Altri autori (Persone) |
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CherietM (Mohamed) |
QiuXuesong |
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Disciplina |
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Soggetti |
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Computer engineering |
Computer networks |
Cloud computing |
Signal processing |
Computer networks - Security measures |
Internet of things |
Computer Engineering and Networks |
Computer Communication Networks |
Cloud Computing |
Digital and Analog Signal Processing |
Mobile and Network Security |
Internet of Things |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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-- ICIPNP 2024-Spring. -- Inter-system Interference and Optimal |
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Utilisation of Resources in 1800MHz Band 5G Networks. -- Multi-Domain Fusion Method for Power Business Data on Data Middle Platform. -- Research on Engineering Cost Information Processing and Database Construction Based on BIM. -- A Lightweight Human Activity Recognition Method based on Machine Learning. -- Advancements and Challenges in Wireless Multimedia Communications: A Comprehensive Review. -- The Prediction of Crystallizer Liquid Level Fluctuations in Continuous Casting Based on HECNN-LSTM Model. -- Cross-Layer Design for Wireless Multimedia Communications: Optimal Resource Allocation and PerformanceOptimization. -- IEEE802.11ax Multi-frame Transmission Resource Allocation Method for Fault Tolerance. -- Wavelet Transform And SRResNet Based Image Compression And Transmission Scheme With Beidou ShortMessage. -- Connector Fixture Temperature Monitoring for Railroad Infrastructure Maintenance. -- Research on the Evaluation of Wireless Quality. -- Research on Key Technology of Navigation and Positioning Based on GAGAN and Analysis of SystemAccuracy. -- Compatibility Assessment of 5G Macro Stations with GSM-R Systems in High-Speed Railway. -- Wireless Multimedia Communication in Smart Cities: Applications and Challenges. -- Advancements in Onboard Real-Time Processing for SAR Satellite Imaging. -- Exploration of Technical and Economic Data Governance of Power Generation Engineering. -- Enhancing Rail Network Efficiency with Advanced 5G Connectivity Solutions. -- A Satellite-positioning Assisted Mobility Management Method for Satellite Fusion Networks. -- Deployment of Multiple Aerial Base Stations in Dynamic Traffic Scenarios. -- Resource Allocation for NOMA-Assisted Mobile Edge Computing System with Data Compression. -- Big Data Exploration and Practice of Non-equipment Work Package for Nuclear Island Installation Based onFocused Business System Collaboration. -- Telemetry Service Visualization for Computing and Network Convergence Environment. -- Green Communications for Wireless Multimedia: Energy-Efficient Solutions and Sustainability Perspectives. -- A Review of Base Station Navigation Technology for Integrated Communication and Navigation. -- Multimodal Sensing-assisted Communication Beamforming with Lightweight Feature Learning. -- Research on Time Synchronization Error Analysis and Compensation Based on Data Link RTT under HighDynamic. -- Research on Performance Test Method of Real Time Locating System. -- Fuzz Testing for Database Management System Configuration Errors. -- Advanced Task Offloading Techniques in Integrated Satellite-Terrestrial Networks: An In-Depth Analysis. -- Study and Application of Adjacent Frequency Interference For 5G System in 900MHz Band. -- Leveraging Artificial Neural Networks for Accurate ShortTerm Traffic Prediction in Centralized SDN Archite. -- Study on Intelligent Digital Manufacturing of Engine Connecting Rods. -- Multi-Access Edge Computing-Assisted Satellite-Terrestrial Integrated Networks. -- Exploration and Implementation of Heavy Haul Railway Catenary System Advanced Intelligent MonitoringTechnology. -- Research on Vehicle Target Recognition Based on Improved YOLO Algorithm. -- Ultra-Reliable Low-Latency Communications (URLLC) in Wireless Multimedia: Prospects and Challenges. -- In-situ Synthesis of C4N@CNT Composites for Ultra Low-temperature Proton Battery. -- Data Categorization with Transformer and Associative Attention in Data Middle Platform. |
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Sommario/riassunto |
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The four-volume set CCIS 2416, 2417, 2418 and 2419 constitutes the refereed post-conference proceedings of the Third International Conference on Information Processing and Network Provisioning, ICIPNP 2024 Spring, held in Beijing, China, during June 14–16, 2024. |
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The 152 revised full papers presented in these proceedings were carefully reviewed and selected from 347 submissions. They focus on topics ranging from 5G/6G evolution and AI in network optimization to quantum communication and green computing. |
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