Internet of energy for smart cities : machine learning models and techniques /: machine learning models and techniques. (2021)

• Record Type: Book
• Further Information: Note: Edited by Gagangeet Singh Aujla, Neeraj Kumar, Anish Jindal.
• Editors: Aujla, Gagangeet Singh; (Computer scientist), Kumar, Neeraj; Jindal, Anish
• Contents: SECTION I Overview; Chapter 1 Smart City: The Verticals of Energy Demand and Challenges; Sumedha Sharma, Ashu Verma, and B.K. Panigrahi; 1.1 Introduction; 1.2 Smart Energy Distribution; 1.2.1 Demand Response; 1.2.2 Demand Side Management; 1.3 Real-Time Grid Analytics and Data Management; 1.3.1 Energy System Operations; 1.3.2 Energy Management Systems; 1.3.3 Design and Formulation of Optimizer Model; 1.3.4 Real-Time Optimization; 1.3.4.1 Robust Optimization; 1.3.4.2 Stochastic Programming with Recourse; 1.3.4.3 Chance-Constrained Optimization; 1.3.5 Big Data Analytics; 1.3.6 Energy Blockchain; 1.4 Intelligent Cloud based Grid Applications; 1.4.1 Centralized Control; 1.4.2 Decentralized Control; 1.4.3 Distributed Control; 1.4.4 Multi-Agent Systems; 1.5 Conclusion SECTION II Smart Grids; Chapter 2 Conventional Power Grid to Smart Grid; Dristi Datta and Nurul I Sarkar; 2.1 Introduction; 2.2 Evolution: From Power Grid to Smart Grid; 2.3 Benefits of Smart Grid System; 2.3.1 Technological Benefits; 2.3.2 Benefits to Customers; 2.3.3 Benefits to Stakeholders; 2.4 Smart Grid: Standards and Technologies; 2.4.1 Standards; 2.4.1.1 Revenue Metering Information Model; 2.4.1.2 Building Automation; 2.4.1.3 Substation Automation; 2.4.1.4 Powerline Networking; 2.4.1.5 Home Area Network Device Communication; Measurement and Control; 2.4.1.6 Application-Level Energy Management; Systems; 2.4.1.7 Inter-Control and Interoperability Center; Communications; 2.4.1.8 Cyber Security; 2.4.1.9 Electric Vehicles; 2.4.2 Technologies; 2.4.2.1 Storage Systems; 2.4.2.2 Telecommunication Systems; 2.4.2.3 ICT Infrastructure; 2.5 Implementation Aspects; 2.6 Challenges of Implementing Smart grid; 2.6.1 Technical Challenges; 2.6.2 Socio-economic Challenges; 2.6.3 Miscellaneous; 2.7 Open Research Questions; 2.8 Concluding Remarks Chapter 3 Smart Grids: An Integrated Perspective; Rafael S. Salles, B. Isa´ıas Lima Fuly, and Paulo F. Ribeiro; 3.1 Introduction; 3.2 Design challenges and philosophical considerations; 3.2.1 Challenges and Technical Barriers; 3.2.1.1 Renewable Generation Sources; 3.2.1.2 Management and Market Complexity; 3.2.1.3 Power Quality Issues; 3.2.1.4 Cybersecurity; 3.2.2 Holistic Normative Engineering Design for; Smart Grids; 3.3 Smart grid architectures and technologies; 3.3.1 The Communication Structure and Technologies; 3.3.2 Smart Metering, Measurements, Control and; Automation; 3.3.3 Microgrids and Key Technologies; 3.4 Interoperability and scalability; 3.4.1 Moving for Interoperability in Smart Grids; 3.4.2 Scalability Aspects for the Modern Grid Model; 3.5 Applications; 3.5.1 Distributed Energy Resources Management; 3.5.2 Energy Storage; 3.5.3 Metering and Automation SECTION III Internet of Energy (IoE); Chapter 4 Internet of Energy: Solution for Smart Cities; Ash Mohammad Abbas; 4.1 Introduction; 4.2 Constituents of Smart Cities; 4.2.1 Participation of Citizen; 4.2.2 Residential Buildings; 4.2.3 Street Lights; 4.3 Need of IoE in Smart Cities; 4.4 Problems to be Solved Using IoE; 4.5 Operation of IoE; 4.6 Integration of Electrical Vehicles to IoE; 4.7 Infrastructure Required for IoE; 4.8 IoE Tools; 4.9 Conclusion Chapter 5 IoE Applications for Smart Cities; Manju Lata and Vikas Kumar; 5.1 Introduction; 5.2 Energy Challenges in IoE; 5.2.1 Reliability and Scalability; 5.2.2 Security and Privacy intended for Data Access; 5.2.3 Cost and Expenditure; 5.2.4 Climate Conditions; 5.2.5 Legislation; 5.2.6 Education and Engagement of Citizens; 5.2.7 Infrastructure and Capacity Building; 5.3 Resolutions to IoE Energy Challenges; 5.4 Smart Applications of IoE; 5.5 Conclusion Chapter 6 IoE Design Principles and Architecture; Rania Salih Abdalla, Sara A. Mahbub, Rania A. Mokhtar, Elmustafa; Sayed Ali, and Rashid A. Saeed; 6.1 Introduction; 6.2 IoE Architecture Models; 6.2.1 An EMS-Based Architecture; 6.2.2 A Fog Based Architecture; 6.3 Embedding Intelligence in IoE Design; 6.3.1 Cloud Computing; 6.3.2 Fog Computing; 6.3.3 Blockchain; 6.4 IoE Standards8; 6.4.1 IEEE 2030 Standard; 6.4.2 IEEE 802.15.4g; 6.4.3 IEEE 21450 and IEEE 21451; 6.4.4 The 4th G -Based Low Power Wide Area (LPWA); 6.5 IoE Interoperability; 6.6 IoE Privacy and Security; 6.6.1 IoE Cyber Security; 6.6.2 IoE Hardware Security; 6.7 Conclusion SECTION IV Machine Learning Models; Chapter 7 Machine Learning Models for Smart Cities; Dristi Datta and Nurul I Sarkar; 7.1 Introduction; 7.2 Machine Learning Frameworks; 7.2.1 Machine Learning Approaches; 7.2.2 Machine Learning Models; 7.2.2.1 Supervised Learning Models; 7.2.2.2 Unsupervised Learning Models; 7.2.2.3 Semi-supervised Learning Models; 7.2.2.4 Reinforcement Learning Model; 7.3 Problem-solving using Machine Learning Techniques; 7.4 Smart City Design Infrastructure; 7.5 Smart City Design Challenges; 7.5.1 Technical Challenges; 7.5.2 Social Challenges; 7.5.3 Economic Challenges; 7.5.4 Miscellaneous Challenges; 7.6 Implications of ML Models in the Design of Smart Cities; 7.7 Concluding Remarks Chapter 8 Machine Learning Models in Smart Cities - Data-Driven Perspective; Seyed Mahdi Miraftabzadeh, Michela Longo, and Federica Foiadelli; 8.1 Introduction; 8.2 Artificial Intelligence and the smart cities; 8.3 Machine Learning; 8.3.1 Categories of machine learning techniques; 8.3.2 Big Data and Machine learning; 8.4 Data terminology; 8.4.1 Data definitions; 8.4.2 Data type; 8.4.3 Dataset in machine learning; 8.5 Machine learning model; 8.5.1 Model performance analysis (Error); 8.5.2 Validation Set; 8.5.3 Model performance’s evaluation metrics; 8.5.3.1 Classification metrics; 8.5.3.2 Regression metrics; 8.5.4 Machine learning algorithms; 8.5.4.1 Classification algorithms; 8.5.4.2 Regression algorithms SECTION V Case Studies and Future Directions; Chapter 9 Case Study - 1: Machine Learning Techniques for Monitoring of PV Panel; Haba Cristian-Gyozo; 9.1 Introduction; 9.2 Solar panel monitoring; 9.3 Photovoltaic operation degradation; 9.4 Preventing measures; 9.5 Real time data acquisition and analytics; 9.5.1 Data sources ; 9.5.1.1 Local data acquisition systems; 9.5.1.2 Meteorological mini stations; 9.5.1.3 Astronomical data; 9.5.1.4 Cloud services; 9.5.1.5 Alerting systems; 9.6 Machine learning techniques in PV panel operation; monitoring; 9.7 Case study of system for PV panel monitoring; 9.7.1 Photovoltaic systems in Romania; 9.7.2 Description of the photovoltaic system; 9.7.3 Weather station prototype; 9.7.4 Data sources; 9.7.4.1 Data from PV system; 9.7.4.2 Weather ministations; 9.7.4.3 Cloud services; 9.7.5 ML Methodology; 9.7.5.1 Data collection; 9.7.5.2 Data Preprocessing; 9.7.5.3 Model selection; 9.7.5.4 Feature selection; 9.7.5.5 Training and Validation; 9.8 Conclusions Chapter 10 Case Study - 2: Intelligent Control System for Smart Environment; Chintan Bhatt, Riya Patel, Siddharth Patel, Hussain Sadikot; Akrit Khanna, and Esha Shah; 10.1 Introduction; 10.2 Related Work; 10.3 Methodology; 10.3.1 Privileged Access; 10.3.2 Manual control of Electrical Appliances; 10.3.3 Automatic control of electrical appliances; 10.4 Experimental Set-up and Results; 10.5 Discussion and Conclusion; 10.6 Limitations; 10.7 Future Enhancements Chapter 11 Pathway and Future of the IoE in Smart Cities; Sharda Tripathi and Swades De; 11.1 Introduction; 11.2 IoE Application case studies; 11.2.1 Smart monitoring of civic infrastructure and; amenities; 11.2.2 Smart wireless services; 11.2.3 Advanced power metering; 11.2.4 Smart grid monitoring; 11.3 Roles of big data and context-specific learning in future; IoE; 11.3.1 Roles and challenges of big data; 11.3.2 Node- and network-level data-driven optimization; 11.4 Role and challenges of smart grid in IoE energy sustainability; 11.4.1 Energy sustainability; 11.4.2 Stability and controllability of power grid; 11.5 Concluding remarks
• Edition: 1st
• Publisher Details: Boca Raton : CRC Press
• Publication Date: 2021
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 621.3102854678; Electric power systems -- Automatic control; Electric power distribution -- Data processing; Cities and towns -- Technological innovations; Internet -- Industrial applications
• Languages: English
• ISBNs: 9781000411003; 9781000410983; 9781003047315
• Related ISBNs: 9780367497750
• Notes: Note: Description based on CIP data; resource not viewed.
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