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