Resilient Community Microgrids

• Autore: Swathika O. V. Gnana
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2025; ©2025
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (605 pages)
• Altri autori: KarthikeyanK
• Nota di contenuto: Cover -- Series Page -- Title Page -- Copyright Page -- Contents -- Preface -- Chapter 1 AI-Based Virtual Advisor for Smart Climate Farming -- 1.1 Introduction -- 1.2 Research on Smart Farming Technologies and AI Applications -- 1.3 AI and IoT in Smart Farming -- 1.4 Sustainable Agriculture and Climate-Smart Farming -- 1.5 Conclusion -- References -- Chapter 2 Swappable Battery Pack System for Electric Two-Wheelers: Design, Infrastructure, and Implementation -- 2.1 Introduction -- 2.2 Swappable Battery Technology -- 2.3 Battery Swapping Infrastructure and Optimization -- 2.4 Battery Management System -- 2.5 Business Models and Economic Implications -- 2.6 Conclusion -- References -- Chapter 3 Implementation of High Gain Bidirectional Interleaved DC/DC Converter for Electric Vehicles with Supercapacitors -- 3.1 Introduction -- 3.2 Proposed Converter -- 3.3 Operating Principle of the HGBID Converter -- 3.4 Design Considerations -- 3.5 Characteristics of SC -- 3.6 Simulation Results -- 3.7 Conclusion -- References -- Chapter 4 Fault Over-Ride and Minimization of Losses in a PV Integrated Transmission Network Using STATCOM -- 4.1 Introduction -- 4.2 Problem Statement -- 4.3 Contingency Analysis and Contingency Selection -- 4.4 Test System, Software and Components Used -- 4.4.1 Test System and Software -- 4.4.2 PV Generators Integration -- 4.4.3 Static Synchronous Compensator (STATCOM) -- 4.5 Results and Analysis -- 4.5.1 Bus Network Integrated with Solar Photo-Voltaic Generators -- 4.5.2 Test Bus Network with One STATCOM Installed at Bus 6 -- 4.6 IEEE 14 Bus Network with Two STATCOMs Installed at Bus 2 and Bus 6 -- 4.7 Conclusion -- 4.8 Future Scope -- References -- Chapter 5 Oscillating Water Column as Clean Energy Source for Sustainable Power Generation -- 5.1 Introduction to Technology -- 5.2 Hardware Implementation. ; 5.3 Three-Dimensional Design of Hardware Components in Solid Edge Software -- 5.4 Hardware Implementation Results and Performance Analysis of Oscillating Water Column (OWC) -- 5.5 Conclusion -- 5.6 Future Scope -- References -- Chapter 6 Cloud-Based Big Data Architecture and Infrastructure -- 6.1 Introduction -- 6.1.1 Overview of the Difficulties Caused by the Quantity, Speed and Diversity of Big Data -- 6.1.2 The Significance of Adaptable and Scalable Approaches to the Storage, Processing and Analysis of Huge Datasets -- 6.2 Big Data Architecture for the Cloud Fundamentals -- 6.3 Overview of Methods for Ingesting Data, Including Batch Operations and Live Streaming -- 6.3.1 A Description of Distributed Computing Architectures and How They Support Large-Scale Cloud Data Processing -- 6.4 Technologies for Big Data on the Cloud -- 6.4.1 Examining Virtualization and Containerization Technologies and How They Affect the Use of Large Data -- 6.5 Overview of Server Less Computing and Its Benefits for Cost Optimization and Scaling -- 6.5.1 An Examination of Cloud-Native Technologies and How Big Data Platforms Integrate with Them -- 6.6 Big Data Architectural Models for the Cloud -- 6.6.1 Detailed Description of Data Lakes and How They Function How They Process and Store Large Amounts of Heterogeneous Data -- 6.6.2 A Description of Real-Time Streaming Systems and How They are Used to Process High-Speed Data Streams -- 6.7 Integration of Cloud Services and Big Data -- 6.7.1 How to Combine Big Data Platforms with Cloud Services Including Analytics, Compute and Storage -- 6.8 Examining Data Integration and ETL (Extract, Transform, Load) Methods Based on the Cloud -- 6.9 Overview of Cloud-Based Big Data Environments' Data Governance and Metadata Management -- 6.10 Analysis of Cloud-Based Big Data Architectures' Scalability Issues. ; 6.11 Examining Vertical and Horizontal Scaling Methods to Succeed in Processing Demands and Growing Data Volumes -- 6.11.1 Horizontal Scaling -- 6.11.2 Vertical Scaling -- 6.12 Introduction to Cloud-Based Big Data Architectures' Performance Optimization Strategies -- 6.12.1 Data Partitioning -- 6.12.2 Caching -- 6.12.3 Parallel Processing -- 6.13 Big Data Based on the Cloud is Secure and Private -- 6.13.1 Discussion of the Security Issues and Factors in Cloud-Based Big Data Environments -- 6.14 A Description of the Mechanisms for Data Encryption, Access Regulation and Identity Administration -- 6.14.1 Data Encryption -- 6.14.2 Access Control -- 6.14.3 Identity Management -- 6.15 Examination of Privacy Issues and Data Protection Laws Compliance -- 6.15.1 Data Privacy Principles -- 6.15.2 Compliance with Data Protection Laws -- 6.15.3 Data Governance and Documentation -- 6.15.4 Security Measures -- 6.16 Case Studies and Real-World Applications -- 6.16.1 Case Study 1 -- 6.16.2 Case Study 2 -- 6.16.3 Case Study 3 -- 6.16.4 Case Study 4 -- 6.17 Future Directions and Trends -- 6.17.1 Examining New Trends and Technologies in the Architecture and Infrastructure for Big Data on the Cloud -- 6.17.2 Discussion on the Potential of AI, Edge Computing and Machine Learning to Enhance Cloud-Based Big Data Systems -- 6.18 Future Developments Prediction and Scalable and Efficient Data Processing Implications -- 6.19 Conclusion -- 6.20 Emphasis on Cloud-Based Big Data Architecture and Infrastructure's Potential for Transformation -- 6.21 Motivating Companies to Adopt Cloud-Based Big Data Technologies -- Chapter 7 RISC-V Processor Hardware Modelling with Custom Instruction Set for SHA-3 Acceleration -- 7.1 Introduction -- 7.2 State of the Art -- 7.3 Keccak Algorithm in SHA-3 -- 7.4 RISC-V Instruction Set Architecture -- 7.4.1 Base Instruction Set Architecture. ; 7.4.2 Cryptography Extensions -- 7.5 Custom Instructions for SHA-3 Hashing -- 7.5.1 Instruction DMPL -- 7.5.2 Instruction DMPH -- 7.5.3 Instruction ACC -- 7.5.4 Instruction ROT -- 7.6 Proposed Processor Microarchitecture -- 7.6.1 Standard Modules -- 7.6.2 Extension Modules -- 7.6.3 SHA-3 Module -- 7.7 Results and Discussion -- 7.7.1 Functional Verification Results -- 7.7.2 Logical Synthesis Results -- 7.7.3 Physical Synthesis Results -- 7.8 Conclusion -- References -- Chapter 8 SSL Vulnerability Exploitation Analysis Tool to Provide a Secure and Sustainable Network for Smart Cities -- 8.1 Introduction -- 8.2 Related Work -- 8.3 Research Methodology -- 8.4 Experimental Results -- 8.5 Conclusion -- References -- Chapter 9 Service-Oriented Smart City Vigilant Data Hub for Social Innovation -- 9.1 Introduction -- 9.2 Background and Literature Review -- 9.3 App Architecture and Technology Stack -- 9.4 User Registration and Authentication -- 9.4.1 Streamlined User Onboarding -- 9.4.1.1 Simple Registration Process -- 9.4.1.2 Verification and Security -- 9.4.1.3 Efficient Authentication Mechanisms -- 9.5 Features and Functionality -- 9.5.1 Interactive Forum for Smart City Development -- 9.5.1.1 Project Exploration -- 9.5.1.2 User-Friendly Interface -- 9.5.2 Empowering User Engagement -- 9.5.2.1 Upvoting and Downvoting -- 9.5.2.2 Commenting and Collaborative Discussions -- 9.5.3 Personalized User Profiles and Notifications -- 9.5.3.1 User Profiles -- 9.5.3.2 Timely Notifications -- 9.5.4 Efficient Search and Filtering -- 9.5.4.1 Keyword Search -- 9.5.4.2 Category and Tag Filtering -- 9.5.5 Active User Feedback Submission -- 9.5.5.1 New Feedback Submission -- 9.5.5.2 Category and Tag Filtering -- 9.5.6 Empowered Administrative Dashboard -- 9.5.6.1 Moderation and Oversight -- 9.5.6.2 User Activity Insights -- 9.6 User Experience and Interface Design. ; 9.6.1 Intuitive User Experience (UX) -- 9.6.1.1 Simplicity and Clarity -- 9.6.1.2 Effortless Navigation -- 9.6.1.3 Responsive Design -- 9.6.2 Thoughtful User Interface (UI) -- 9.6.2.1 Visual Consistency -- 9.6.2.2 Engaging Visual Elements -- 9.6.2.3 Strategic Color Palette -- 9.6.2.4 Natural Interaction -- 9.7 Data Privacy and Security -- 9.7.1 Protecting User Data -- 9.7.1.1 Firebase Security Rules -- 9.7.1.2 Secure Authentication -- 9.7.1.3 Encryption -- 9.7.2 Ensuring User Privacy -- 9.7.2.1 Data Minimization -- 9.7.2.2 User Consent -- 9.7.2.3 Opt-Out Options -- 9.7.3 Secured Cloud Operations -- 9.7.3.1 Cloud Storage -- 9.7.3.2 Real-Time Updates -- 9.7.4 Regular Security Audits -- 9.7.4.1 Ongoing Monitoring -- 9.7.4.2 Prompt Updates -- 9.8 Real-Time Updates and Push Notifications from the App -- 9.8.1 Real-Time Updates -- 9.8.2 Push Notifications -- 9.9 Scalability and Performance Optimization -- 9.9.1 Scalability Design -- 9.9.1.1 Distributed Architecture -- 9.9.1.2 Elastic Resources -- 9.9.1.3 Load Balancing -- 9.9.2 Performance Optimization Strategies -- 9.9.2.1 Caching Mechanisms -- 9.9.2.2 Image Compression -- 9.9.2.3 Asynchronous Processing -- 9.9.2.4 Database Indexing -- 9.10 User Engagement Analytics -- 9.11 Impact and User Engagement -- 9.11.1 Impact -- 9.11.1.1 Amplified Citizen Voices -- 9.11.1.2 Inclusive Dialogue -- 9.11.1.3 Fostering Togetherness -- 9.11.1.4 Transparency in Action -- 9.11.2 Increasing User Engagement -- 9.11.2.1 Gamification and Rewards -- 9.11.2.2 Moderation and Content Quality -- 9.11.2.3 Data Privacy and Security -- 9.11.2.4 Feedback Loop -- 9.11.2.5 User Training and Onboarding -- 9.12 Citizen User Flow and Admin Access User Flow -- 9.13 Conclusion -- 9.14 Future Potential -- 9.14.1 Increased Citizen Engagement -- 9.14.1.1 Number of Registered Users -- 9.14.1.2 Frequency and Quality of Feedback Submissions. ; 9.14.1.3 Active Participation in Discussions and Collaborations.
• Titolo autorizzato: Resilient Community Microgrids
• ISBN: 9781394272549; 1394272545; 9781394272525; 1394272529; 9781394272532; 1394272537
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911018957403321
• Lo trovi qui: Univ. Federico II