AI-Powered IoT in the Energy Industry: Digital Technology and Sustainable Energy Systems

Preface
Acknowledgments
Contents
About the Editors
Chapter 1: AI and Intermittency Management of Renewable Energy
1.1 Introduction
1.2 Renewable Energy Sources
1.2.1 Wind Energy
1.2.2 Solar Energy
1.2.3 Geothermal Energy
1.2.4 Hydro Energy
1.2.5 Ocean Energy
1.2.6 Bioenergy
1.2.7 Hydrogen Energy
1.3 Artificial Intelligence
1.3.1 Artificial Intelligence in Wind Energy
1.3.1.1 AI Application in Wind Mills
1.3.1.1.1 Detecting Signs of Imminent Damage in Advance
1.3.1.1.2 One Windmill Should Not Hamper Any Others
1.3.1.2 Artificial Intelligence in Solar Energy
1.3.1.2.1 AI Technology
1.3.1.2.2 Smart Grid Centralized Control Centers
1.3.1.2.3 Improved Integration of Microgrids, Safety, and Reliability
1.3.1.2.4 Expand the Market
1.3.1.2.5 Intelligent Energy Storage
1.3.1.3 Artificial Intelligence in Geothermal Energy
1.3.1.3.1 AI Use Geothermal Energy Cases
1.3.1.4 Artificial Intelligence in Hydro Energy
1.3.1.4.1 AI for Performance Optimization
1.3.1.4.2 AI for the Forecasting of Plant Parameters
1.3.1.4.3 AI in Monitoring and Control of Hydropower Plants
1.3.1.4.4 AI for Accuracy Evaluation and Capability Assessment
1.3.1.5 Artificial Intelligence in Ocean Energy
1.3.1.6 Artificial Intelligence in Bioenergy
1.3.1.7 Artificial Intelligence in Hydrogen Energy
References
Chapter 2: AI and ML Toward Sustainable Solar Energy
2.1 Introduction
2.1.1 Involving AI for Managing Sustainable Energy
2.2 Factors Which Influence the Efficacy of Solar Energy
2.2.1 Construct Smart Control Centers
2.2.2 Coordinated Microgrids
2.2.3 Security and Reliability
2.2.4 Market Expansion
2.2.5 Smart Storage Units
2.3 Machine Learning in Solar Energy Production
2.3.1 Shrewd Foundation Plan of Solar-Oriented Energy Frameworks
2.3.2 Smart Support of Solar Energy Plants
2.3.3 Solar Energy Creation Determination
2.3.4 Enhanced Transmission and Dispersion Organizations
2.3.5 Understanding the Solar-Oriented Energy Market
2.4 Enormous Information Blast and Improvement of AI Models
2.5 Applications of ML in Sustainable Energy
2.5.1 Solar Energy
2.5.2 Wind Energy
2.6 The Future of Renewable Energy in the Perception of AI and ML
2.7 Conclusion
References
Chapter 3: Energy Intelligence: The Smart Grid Perspective
3.1 Introduction
3.1.1 History of Energy Grids
3.1.2 Power Sources
3.1.3 Power Demand
3.1.4 Power Supply
3.1.5 Renewable Energy Sources and Green Energy
3.2 Energy Systems and Smart Grids
3.2.1 Differentiation Between Current and Futuristic Smart Grids
3.2.2 Communication Infrastructure of Smart Grids
3.2.2.1 Wide-Area Network (Core Tier)
3.2.2.2 Neighborhood Area Network (Distribution Tier)
3.2.2.3 Premise Network (Access Tier)
3.2.2.4 Smart Microgrids
3.2.2.5 Communication Technologies: Wired or Wireless?
3.2.3 Distributed Approaches
3.2.4 Data Collection, Storage, and Processing
3.2.4.1 Data Characteristics
3.2.4.2 Data Sources
3.2.4.3 Data Processing
3.2.4.3.1 Data Storage
3.2.4.3.2 Data Privacy and Security
3.2.5 Data Analysis
3.2.5.1 Data Visualization
3.2.5.2 Big Data Tools for Analytics
3.2.5.2.1 Batch Processing Tools
3.2.5.2.2 Real-Time Processing Tools
3.2.5.2.3 Hybrid Processing Tools
3.2.6 IoT-Enabled Smart Grid Information System
3.3 Energy Intelligence
3.3.1 Objectives of Energy Intelligence
3.3.2 Data Forecasting: The Key Component
3.3.2.1 Insights from Smart Grids
3.3.2.2 Modeling Intelligent Power Grids
3.3.2.2.1 Demand Forecasting Through Artificial Neural Networks
3.3.2.2.2 Markov Processes
3.3.2.2.3 AI-Powered Simulators
3.3.2.2.4 Random Fuse Networks
3.3.2.2.5 Biosystems and Meta-heuristic Algorithms
3.3.2.3 Making Cities Energy Intelligent
3.4 Role of Energy Intelligence in Modeling Smarter Future
3.4.1 Making Smart Grids Smarter
3.4.2 G2V and V2G for Electric Vehicles
3.4.2.1 Self-Learning System and Grid
3.4.2.2 Complete Automation
3.4.3 Internet of Energy
3.5 Conclusion
References
Chapter 4: IoT Infrastructure to Energize Electromobility
4.1 Introduction
4.2 Electromobility and the Internet of Things in Buildings: Building Automation Includes Electromobility
4.2.1 The Internet of Things Provides Us with This Capability
4.2.2 Data as an Extremely Powerful Tool
4.2.3 Enhancing User Comfort with Enhanced Technical Features
4.2.4 Dynamic Information Exchange Between the Vehicle and the Building
4.3 Typical Locations with Electric Vehicles and Charging Stations by 2030
4.4 IoT Infrastructure Plays a Crucial Role in Connecting Our Devices
4.4.1 Information and Communication Technology (ICT) Infrastructure
4.4.2 IoT Technology Services
4.4.3 IoT Cloud Computing and Fog Computing
4.4.4 Analysis of Big Data and IoT
4.4.5 Internet of Things Security
4.5 Stuttgart Network Load Analysis and Forecast
4.5.1 Energy and the Internet of Things
4.5.2 Energy Generation and IoT
4.5.3 Intelligent Cities
4.5.4 Renewable Sources of Energy
4.5.5 Built-In Intelligence
4.5.6 Making Industry More Energy-Efficient
4.5.7 Intelligent Transport
4.6 The Challenges of Implementing IoT
4.6.1 Total Energy Consumption
4.6.2 Internet of Things Integration with Subsystems
4.6.3 Personal Information of Users
4.6.4 Securing Information
4.6.5 Standards Are Interconnected
4.6.6 Design of the Architecture
4.7 Future Prospects
4.7.1 Blockchain and the Internet of Things
4.7.2 Social Networking and the Environment
4.8 Conclusions
References
Chapter 5: Internet of Things Toward Leveraging Renewable Energy
5.1 Introduction
5.2 Technologies of IoT
5.2.1 Hardware
5.2.2 Software
5.2.3 Platform
5.2.4 Communications
5.2.4.1 Bluetooth
5.2.4.2 Wi-Fi
5.2.4.3 RFID
5.2.4.4 Wireless Sensor Networks (WSN)
5.3 General Architecture of IoT
5.3.1 Application Layer
5.3.2 Network Layer
5.3.3 Perception
5.4 Computing IoT Data
5.4.1 Cloud Computing
5.4.2 Fog Computing
5.5 Applications of IoT in Various Fields
5.5.1 Healthcare Systems
5.5.2 Agriculture
5.5.3 Smart City
5.6 IoT in Leveraging Renewable Energy
5.6.1 Renewable Energy
5.6.2 Solar Energy
5.6.3 IoT in Energy Sector
5.6.4 IoT to Improve Overall Production
5.7 Smart Grids for Implementation of Renewable Energy Distribution
5.8 Context Awareness
5.9 Test Bed
5.10 Literature Survey
5.11 Energy Sector Challenges
5.12 Conclusion
References
Chapter 6: IOT Contribution in Construct of Green Energy
6.1 Energy and the Internet of Things
6.1.1 Introduction
6.1.2 Research Methods
6.2 Internet of Things (IoT) for Business
6.3 Self-Powered Internet of Things Devices Using Energy Harvesting
6.3.1 Combustion of Energy
6.3.2 The Harvesting of Solar Energy
6.4 System Using IoT to Harvest Energy
6.4.1 Alternative Energy Sources
6.4.2 Using IOT to Improve Wind Turbine Reliability
6.4.3 Internet of Things in Power
6.5 Technology and AI
6.5.1 Artificial Intelligence as a Global Development Tool
6.6 AI for a Sustainable Future
6.7 Sensor-Based Energy Management in Wireless Sensor Networks
6.7.1 Overview
6.7.2 Modeling and Managing Energy-Efficient Sensors
6.7.3 Organization for Sensing Adaptive
6.7.4 Hierarchical Analysis Methods
6.8 Conclusion
References
Chapter 7: Building Sustainable Changing Infrastructure – Smart Solutions
7.1 Introduction
7.1.1 Environment
7.1.2 The Emergence of Sustainability
7.2 Smart Solutions
7.2.1 Constructions
7.2.2 Energy
7.2.3 Water
7.2.4 Food
7.2.5 Healthcare
7.3 Conclusion
References
Chapter 8: Biomass Renewable Energy: Introduction and Application of AI and IoT
8.1 Introduction
8.2 Renewable Energy
8.3 Types of Renewable Energy
8.3.1 Wind Power
8.3.2 Solar Power
8.3.3 Geothermal Energy
8.3.4 Hydro Energy
8.3.5 Tidal Energy
8.3.6 Nuclear Energy
8.3.7 Hydrogen Energy
8.4 IoT in Renewable Energy
8.4.1 Challenges of IoT Implementation in Renewable Energy
8.5 AI in Renewable Energy
8.5.1 Challenges of AI in Energy Industry
8.5.2 Subsidy Given by the Government for Generation of Renewable Energy
8.6 Future of Renewable Energy
8.7 Conclusion
References
Chapter 9: AI and IoT in Improving Resilience of Smart Energy Infrastructure
9.1 Introduction
9.2 Smart Energy, Smart Grid, and Smart Energy Systems
9.3 Smart Energy System
9.4 IoT and Smart Energy Systems
9.5 IoT and Energy Sectors
9.5.1 IoT and Solar Energy
9.5.2 IoT and Geothermal Energy Generation
9.5.3 IoT and Wind Energy
9.5.4 IoT in Hydropower
9.6 IoT Applications in Energy Sector
9.6.1 Supervisory Control and Data Acquisition (SCADA)
9.6.2 Energy Resource Optimization
9.6.3 Microgrids’ Empowerment
9.6.4 Advanced Metering Infrastructure (AMI)
9.6.5 Proactive Mechanism for Repair
9.6.6 Smart Meter Technology
9.6.7 Remote Monitoring of Assets
9.7 IoT Challenges in Energy Sector
9.7.1 More Energy Consumption
9.7.2 IoT Integration with System Components
9.7.3 Privacy
9.7.4 Security
9.7.5 Architecture Design
9.8 AI and Energy Sector
9.8.1 AI and Wind Energy
9.8.1.1 AI and Prediction
9.8.1.2 Artificial Intelligence (AI) in Operations and Management (O&M)
9.8.2 AI and Solar Energy
9.8.2.1 AI-Based Forecasting System
9.8.2.2 AI for Power Grids and Storage
9.8.2.3 Inspecting Solar Panels with AI-Enabled Drones
9.8.2.4 AI and Market Growth
9.9 AI in Improving Energy Sources
9.9.1 Weather Prediction
9.9.2 Grid Balancing
9.9.3 Detect Grid Faults and Failure
9.9.4 Real-Time Monitoring of Brownouts
9.9.5 Prevent Electric Grid Failures
9.10 Conclusion
References
Chapter 10: Empowering Renewable Energy Using Internet of Things
10.1 Introduction
10.2 Renewable Energy Subsectors
10.2.1 Solar and Wind: A Major Subsector
10.2.2 Tidal Energy
10.2.3 Wave Energy
10.2.4 Hydro Energy
10.2.5 Biomass
10.3 Integration of Renewable Energy and IoT
10.3.1 IoT in Wind and Solar Energy
10.3.2 IoT in Tidal Energy
10.3.3 IoT in Wave Energy
10.3.4 IoT in Hydro Energy
10.3.5 IoT in Biomass
10.4 Overall Benefits of IoT in Renewable Energy
10.4.1 Automation of Process to Increase Productivity
10.4.2 Enhanced Cost Efficiency
10.4.3 Excellent Grid Management
10.4.4 Smart Distribution
10.4.5 Smart Residence
10.4.6 Comparison of Renewable Energy with IoT
10.5 International Market Scenario for IoT in Renewable Energy
10.6 Challenges Faced by IoT in Renewable Energy
10.7 Conclusion
References
Chapter 11: Modernization of Rural Electric Infrastructure
11.1 Introduction
11.1.1 Challenges for Rural Electrification
11.2 Traditional and Modern Technology for Electric Power Systems
11.2.1 Traditional Power Grids
11.2.2 Smart Grids
11.3 Demand and Supply of Electricity in Rural Areas
11.3.1 Sources of Electricity Used by Rural People
11.3.2 Hurdles Preventing Affordability
11.3.3 Demand for Electricity
11.4 Electric Energy Storage
11.4.1 Hydroelectric Power Stations
11.4.2 Wind Mills
11.4.3 Batteries
11.4.4 Thermal Power Station
11.5 Security Concerns over Electrical Power Systems
11.6 Smart-Grid Policies
11.7 Issues on the Implementation of Modern Technologies
11.8 Renewable Energy for Sustainable Development
11.8.1 Solar Energy
11.8.2 Wind Energy
11.8.3 Hydro-Electric Energy
11.8.4 Biomass Energy
11.8.5 Advantages of Renewable Energy Sources
11.8.6 Disadvantages of Renewable Energy Sources
11.9 Recent Trends in Electrical Power Systems
11.10 Innovation for the Deployment of Modern Technologies
11.11 Future Implications in the Rural Electricity Infrastructure
11.11.1 Connecting Unelectrified Rural Homes
11.11.2 Providing the Supply of a Required Quality of Power
11.11.3 Electricity at Marginable Rates
11.11.4 Ensuring Clean and Sustainable Electricity as a Product
11.11.5 Innovations
11.12 Conclusion
References
Chapter 12: The Role of Artificial Intelligence in Renewable Energy
12.1 Introduction
12.2 Renewable Energy
12.2.1 Renewable Energy Source
12.2.1.1 Solar
12.2.1.2 Biomass
12.2.1.3 Hydrogen
12.2.1.4 Oceans
12.2.1.5 Geothermal
12.2.1.6 Wind
12.3 Challenges for Renewable Energy
12.3.1 Weather Unpredictability
12.3.2 Energy Storage Technology
12.4 AI and Renewable Energy Systems
12.4.1 Robotics
12.4.1.1 Flying Drones
12.4.1.2 Crawling Robots
12.4.1.3 Driving Robots
12.4.1.4 Sailing Robots
12.4.1.5 Diving Robots
12.4.2 Smart and Centralized Control Systems
12.4.3 Smart Grids and Intelligent Storage
12.4.4 Wind Flow Speed Prediction
12.4.5 Modeling of a Solar Steam Generator
12.4.6 Improve Safety and Reliability
12.5 RE Technology Organizations and AI
12.5.1 Xcel Energy
12.5.2 PowerScout
12.5.3 General Electric
12.6 Conclusion
References
Chapter 13: Powering the Geothermal Energy with AI, ML, and IoT
13.1 Introduction
13.2 Highlights of AI, ML, and IoT
13.3 Overview of GT Energy
13.4 Hotspots of GT Energy
13.5 Power Production
13.5.1 Dry (Direct) Steam System
13.5.2 Flashing Power System
13.5.3 Binary Cycle System
13.6 Advantages and Disadvantages
13.6.1 Benefits of GT Energy
13.6.2 Drawbacks of GT Energy
13.7 GT Reservoir Management
13.8 AI-Powered IoT
13.8.1 In the Identification of Hotspots
13.8.2 In Power Production
13.8.3 In Reservoir Management
13.9 Conclusion
References
Chapter 14: IoT and Sustainability Energy Systems: Risk and Opportunity
14.1 Introduction
14.1.1 Smart Technologies Are Needed
14.1.2 Scope of Applications
14.1.3 Methodology for Reviewing
14.2 Efficiency of IoT in Sustainable Energy and Environmental Management
14.2.1 The Role of IoT in Maximizing Energy Efficiency and Sustainability
14.2.2 The Internet of Things Is Transforming the Energy Industry
14.3 Conclusion
References
Index