IoT and Analytics in Renewable Energy Systems, Volume I: Sustainable Smart Grids & Renewable Energy Systems

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Editors
Contributors
Chapter 1 Policies for a Sustainable Energy-Dependent India
1.1 Introduction
1.2 The Need for Policies on Alternate Sources of Energy to Power India's Economy
1.3 Conclusion
Bibliography
Chapter 2 A Review on Internet of Things with Smart Grid Technology
2.1 Introduction: General
2.2 IoT-Enabled Smart Grid with Energy Efficiency in Various Aspects
2.2.1 Radio Networking
2.2.2 Cyberattacks
2.2.3 Energy-Efficient Management
2.2.4 Edge and Fog Computing
2.2.5 Applications, Fault Analysis, and Distributions
2.2.6 Blockchain-Based IoT
2.3 Real-Time Applications of IoT-Enabled Smart Grid
2.3.1 IoT-Based Smart Applications
2.4 IoT-Based Smart Grid Architecture
2.5 Detection for IoT-Enabled Smart Grid System
2.6 Recent Advancements in IoT-Smart Grid Technology
2.7 Conclusion
References
Chapter 3 Securing Smart Power Grids Against Cyber-Attacks
3.1 Introduction
3.1.1 History of Smart Electricity Networks
3.1.2 Comparison of Current Electricity Networks with Smart Electricity Networks
3.2 Necessary Technology for Smart Grid
3.3 Security Threats in Smart Electricity Networks
3.4 Data Attack on Smart Power Grids
3.5 Conservation-Based Designs
3.5.1 Protection of a Set of Basic Measurements
3.5.2 PMU-Based Protection
3.5.3 Diagnosis-Based Designs
3.5.4 Detection of Attacks Based on State Estimation Methods
3.5.5 Attack Detection Using Machine Learning Algorithms and Neural Networks
3.5.6 Other FDIA Defense Strategies
3.6 Mode Estimation in Smart Grids
3.7 Bad Data
3.7.1 Bad Data Types in the Power System
3.7.2 Machine Learning Performance
3.8 Summary
References
Chapter 4 Design and Modelling of a Stability Enhancement System for Wind Energy Conversion System
4.1 Introduction
4.1.1 Horizontal-Axis Wind Turbines
4.1.2 Vertical-Axis Wind Turbines
4.1.3 Power System Stabilization
4.1.4 Grid-Connected Requirements
4.2 Modelling of Wind Turbine
4.3 Proposed Research Work
4.3.1 FACTS Devices
4.3.2 Different Methodologies
4.4 Implemented Methodology
4.5 Implemented Fuzzy Rule
4.6 Simulation and Result
4.6.1 Software: MATLAB® Version R2019a
4.6.2 Result Analysis and Simulation
4.7 Conclusion
Bibliography
Chapter 5 Solar-Powered Smart Irrigation System
5.1 Introduction
5.1.1 Literature and Background Survey
5.1.2 Objectives
5.1.3 Functioning of the Prototype
5.2 Description
5.3 Design Aspect
5.4 Demonstration
5.4.1 Simulation
5.4.2 Graphs of Irrigation Module
5.4.3 Solar Tracker Graphs
5.4.4 Hardware Setup
5.4.5 Mobile App
5.5 Conclusion
5.5.1 Future Scope
References
Chapter 6 Future Transportation: Battery Electric Vehicles and Hybrid Fuel Cell Vehicles
6.1 Introduction
6.2 Electric Vehicle
6.2.1 Battery Electric Vehicles
6.2.2 Hydrogen Fuel Cell Vehicles (HFCVs)
6.3 Comparison Between Battery Electric Vehicle (BEV) and HFCV
6.3.1 Efficiency and Emission
6.3.2 Materials Availability
6.3.3 Infrastructure
6.3.4 Cost
6.3.5 Vehicle Weight and Sustainability
6.3.6 Benefits of FCV
6.3.7 Comparison with ICE
6.4 Conclusion
References
Chapter 7 Application of AI to Power Electronics and Drive Systems: Mini Review
7.1 Introduction
7.2 Neural Network
7.3 Fuzzy
7.4 Fault
7.5 Other Prediction Algorithms
7.6 Conclusion
References
Chapter 8 Analysis of Economic Growth Dependence on Energy Consumption
8.1 Introduction
8.2 Literature Review
8.3 Materials and Methods
8.4 Methodology
8.5 Estimation
8.6 Results
8.7 Potential Limitations of Results
8.8 Conclusion
References
Chapter 9 Artificial Intelligence Techniques for Smart Power Systems
9.1 Introduction
9.2 Smart Power System
9.3 Artificial Intelligence
9.3.1 Expert Systems
9.3.2 Database
9.3.3 Inference Engine
9.3.4 Supervised Learning
9.3.5 Unsupervised Learning Algorithms
9.3.6 Reinforcement Learning
9.4 Artificial Intelligence in Smart Power Systems
9.4.1 Smart Power System
9.4.2 Forecasting
9.4.3 Network Security
9.4.4 Economic Dispatching
9.4.5 Consumer and Resource
9.4.6 Resources Management
9.4.7 Home Energy Management
9.4.8 Energy Storage System
9.4.9 EV Charging Station
9.5 Conclusion
References
Chapter 10 IoT Contribution in Construct of Green Energy
10.1 Introduction
10.2 LoRa and IoT Monitoring System
10.3 Hybrid Microgrid with IoT
10.4 Hybrid Green Energy Harvesting Using IoT
10.5 Conclusion
References
Chapter 11 Smart IoT System-Based Performance Improvement of DC Power Distribution within Commercial Buildings Using Adaptive Nonlinear Ascendant Mode Control Strategy
11.1 Introduction: Background and Driving Forces
11.2 Research Background
11.3 Materials and Methods
11.3.1 Modelling of PV Cell
11.3.2 DC-DC Boost Converter
11.3.2.1 Boost Converter Circuit
11.3.2.2 Controller Design and Modes of Operation
11.3.3 AC-DC Converter
11.3.3.1 Buck-Boost Converter Circuit
11.3.3.2 Switching Pulse Generation of Buck-Boost Converter
11.3.3.3 Modes of Operation of Buck-Boost Converter
11.4 Optimization and Power Management Analysis of Converters Using Adaptive Nonlinear Ascendant Mode Control Strategy
11.4.1 Anam – Algorithm Steps
11.5 IoT Data Control System
11.5.1 IoT Data Communication
11.6 Results and Discussion
11.6.1 Performance Analysis of Solar-Based DC-DC Converter
11.6.2 Performance Analysis of AC-DC Converter
11.7 Conclusion
References
Chapter 12 Artificial Intelligence Methods for Hybrid Renewable Energy System
12.1 Introduction
12.2 Renewable Energy Sources
12.3 Application of Artificial Intelligence (AI) to Hybrid Energy Systems
12.3.1 AI for Power Grid and Smart Grid
12.3.2 AI in Electricity Trading
12.4 Hybrid Renewable Energy Systems (HRESs) with Machine Learning
12.5 Renewable Energy Forecasting Approaches
12.5.1 Prediction of Solar Energy
12.5.2 Prediction of Wind Energy
12.5.3 Prediction of Hydropower Energy
12.5.4 Prediction of Biomass Energy
12.6 Neural Network Techniques Applied in the Prediction of Renewable Energy
12.6.1 MLP Models
12.6.2 CNN Models
12.6.3 RNN Models
12.7 Learning Algorithms for ANN Training
12.8 Conclusion
References
Chapter 13 Bidirectional Converter Topology for Onboard Battery Charger for Electric Vehicles
13.1 Introduction
13.2 Working Principle of the OBC
13.3 Modes of Operation
Mode 1 – Grid-to-Vehicle (G2V) Mode
Mode 2 – Vehicle-to-Grid Mode (V2G)
Mode 3 – High-Power Low-Voltage Charging (HP-LVC) Mode
Mode 4 – Low-Power Low-Voltage Charging (LP-LVC) Mode
13.4 Design Specifications
13.5 Simulation Results
13.5.1 Mode 1 and Mode 2 Operation
13.5.2 Mode 3 – HP-LVC Circuit
13.5.3 Mode 4 – LP-LVC Circuit
13.6 Conclusion
References
Chapter 14 Design and Analysis of Split-Source Inverter for Photovoltaic Systems
14.1 Introduction
14.2 Topology Study of Inverters
14.2.1 Voltage-Source Inverter
14.2.2 Z-Source Inverter
14.2.3 Quasi-Z-Source Inverter
14.2.4 Single-Phase Split-Source Inverter (SSSI)
14.3 Simulation of Different Topologies
14.3.1 Gate Pulse Generation for Various Topologies
14.4 Comparison and Results
14.5 Conclusion
References
Chapter 15 Electric Vehicles and Smart Grid: Mini Review
15.1 Introduction: Background and Driving Forces
15.2 EV Charging
15.3 Vehicle to Grid and Grid to Vehicle
15.4 Vehicle to Grid and Grid to Vehicle
15.5 Effects in Vehicle Electrification
15.6 Conclusion
References
Chapter 16 Artificial Intelligence for the Operation of Renewable Energy Systems
16.1 Introduction
16.2 Global Energy Sector
16.2.1 Renewable Energy Sources
16.2.1.1 Wind Energy
16.2.1.2 Solar Energy
16.2.1.3 Geothermal Energy
16.2.1.4 Hydro Energy
16.2.1.5 Bioenergy
16.2.1.6 Hydrogen Energy
16.2.1.7 Hybrid Renewable Energy System (HRES)
16.3 Artificial Intelligence – Overview
16.4 Classification of AI for Renewable Energy Application – Review of AI Techniques
16.4.1 Artificial Neural Networks or Neural Network
16.4.2 Wavelet and Neural Networks (WNNs)
16.4.3 Genetic Algorithms and Particle Swarm Optimisation
16.4.4 Fuzzy Logic
16.4.5 Statistical Methods
16.4.6 Decision-Making Techniques
16.4.7 Hybrid System
16.5 AI Role and Application in the Renewable Energy System
16.5.1 AI in Wind Energy
16.5.2 Role of AI in Hydrogen Energy
16.5.3 AI in Hydropower Energy
16.5.4 AI in Solar Energy
16.5.5 AI in Bioenergy
16.5.6 AI in Geothermal Energy
16.5.7 AI in Hybrid Renewable Energy
16.6 Benefits of AI Application in Renewable Energy System
16.6.1 Energy Storage
16.6.2 Fault Prediction
16.6.3 Energy Efficiency Decision-Making
16.6.4 Utility Energy Planning and Management
16.6.5 Using AI to Identify Theft of Energy
16.6.6 Predictive Maintenance Monitoring and Energy Trading
16.6.7 Informing Policy
16.6.8 Reducing Fossil Fuel Impacts
16.7 Limitations of AI Application in the RES
16.7.1 Lack of Theoretical Background
16.7.2 Lack of Practical Expertise
16.7.3 Outdated Infrastructure
16.7.4 Economic or Financial Pressure
16.7.5 Vulnerability: To Cyberattacks
16.8 Prospects and Advancement in Artificial Intelligence for Effective Application in Renewable Energy Systems
16.8.1 The Proliferation of Data and the Advancement of ML Models
16.8.2 Increased Computational Ability and Intelligent Robotics
16.8.3 The Use of Artificial Intelligence to Guard Against and Identify Cyber-Crime
16.8.4 Enhance Renewable Energy Integration and Energy Efficiency Optimisation
16.8.5 The Relevance of Artificial Intelligence in the Smart Grid and the Internet of Things
16.8.6 Precision Stabilisation and Dependability, and Information Transfer and Communication
16.9 Conclusions
Acknowledgement
References
Chapter 17 Application of Back Propagation Algorithm for Solar Radiation Forecasting in Photovoltaic System
17.1 Introduction
17.2 Problem Formulation
17.3 Solar Energy
17.3.1 Limitations of Solar Energy
17.4 Neural Networks
17.4.1 Introduction
17.4.2 Neural Networks Architecture
17.4.3 Back Propagation Algorithm
17.4.4 Application of NN in Solar Forecasting
17.5 Solar Radiation Forecasting
17.5.1 Input Parameters
17.5.2 Output Parameter
17.5.3 MATLAB® Training
17.5.3.1 Training Functions
17.5.4 Adaptation Learning Functions
17.5.5 Steps to Be Followed to Simulate and Train the Neural Network
17.6 Results
17.7 Conclusion
Bibliography
Chapter 18 Technical and Feasibility Analysis of Interconnected Renewable Energy Sources in Three Separate Regions: A Comparative Study
18.1 Introduction
18.2 Profile of Renewable Energy Resources
18.2.1 Solar Irradiation and Temperature Parameter
18.2.2 Specification of Wind Speed
18.2.3 Details of Biomass Resource
18.3 Explanation of HRES
18.3.1 Mathematical Modelling
18.3.1.1 Solar/PV System
18.3.1.2 Wind Farm
18.3.1.3 Generator
18.3.2 Component Parameter Utilized for Simulation
18.3.2.1 Solar/PV System
18.3.2.2 Wind Farm
18.3.2.3 System Converter
18.3.2.4 Generator
18.3.2.5 Grid
18.3.3 Problem Formulation
18.3.4 Economic Parameters Introduction
18.3.4.1 Total Investment Cost
18.3.4.2 Initial Capital Cost
18.3.4.3 Replacement Cost
18.3.4.4 Operation & Maintenance Cost
18.3.4.5 Salvage Value
18.3.4.6 Life Cycle Cost
18.3.4.7 Annualized Cost
18.3.4.8 Operating Cost
18.4 Optimization Results
18.4.1 Comparative Analysis of Optimization Results of Three Different Regions
18.5 Conclusion
References
Chapter 19 IoT-Based Prioritized Load Management Technique for PV Battery-Powered Building: Mini Review
19.1 Introduction
19.2 Internet of Things (IoT) in Smart Buildings
19.3 Photovoltaic Power Systems Integrated to Smart Buildings
19.4 Conclusion
References
Chapter 20 Application of Artificial Intelligence Techniques in Grid-Tied Photovoltaic System – An Overview
20.1 Introduction
20.2 Summary of AI and Grid-Tied PV System
20.3 Application and Role of AI Techniques in Grid-Tied PV Systems
20.3.1 PV Panel Array Reconfiguration
20.3.2 Islanding Detection
20.3.3 Harmonics Reduction
20.3.4 Meteorological Data
20.3.5 MPPT during Partial Shading
20.3.6 Optimal PV Sizing
20.4 Comparative Evaluation of AI
20.4.1 Speed
20.4.2 System Complex
20.4.3 Tuning
20.4.4 Monitoring and Implementation
20.5 Conclusion
References
Chapter 21 A Critical Review of IoT in Sustainable Energy Systems
21.1 Introduction: Background and Driving Forces
21.2 Data-Driven Smart Cities
21.3 Communication and AI
21.4 Sustainable Energy Management
21.5 Edge Computing
21.6 Energy Harvesting – A Future
21.7 Conclusion
References
Index