Intelligent and Soft Computing Systems for Green Energy

Description

INTELLIGENT AND SOFT COMPUTING SYSTEMS FOR GREEN ENERGY Written and edited by some of the world’s top experts in the field, this exciting new volume provides state-of-the-art research and the latest technological breakthroughs in next-generation computing systems for the energy sector, striving to bring the science toward sustainability. Real-world problems need intelligent solutions. Across many industries and fields, intelligent and soft computing systems, using such developing technologies as artificial intelligence and Internet of Things, are quickly becoming important tools for scientists, engineers, and other professionals for solving everyday problems in practical situations. This book aims to bring together the research that has been carried out in the field of intelligent and soft computing systems. Intelligent and soft computing systems involves expertise from various domains of research, such as electrical engineering, computer engineering, and mechanical engineering. This book will serve as a point of convergence wherein all these domains come together. The various chapters are configured to address the challenges faced in intelligent and soft computing systems from various fields and possible solutions. The outcome of this book can serve as a potential resource for industry professionals and researchers working in the domain of intelligent and soft computing systems. To list a few soft computing techniques, neural-based load forecasting, IoT-enabled smart grids, and blockchain technology for energy trading. Whether for the veteran engineer or the student learning the latest breakthroughs, this exciting new volume is a must-have for any library. Cover Title Page Copyright Page Contents Preface Chapter 1 Placement and Sizing of Distributed Generator and Capacitor in a Radial Distribution System Considering Load Growth 1.1 Introduction 1.2 Problem Formulation 1.3 Algorithm 1.4 Results & Discussions 1.5 Discussion 1.6 Conclusions References Chapter 2 Security Issues and Challenges for the IoT-Based Smart Grid 2.1 Introduction 2.2 Usage of IoT in the Smart Grid Context 2.3 Advantages of IoT-Based Smart Grid 2.4 Cybersecurity Challenges 2.4.1 Review of Recent Attacks 2.4.1.1 Tram Hack Lodz, Poland 2.4.1.2 Texas Power Company Hack 2.4.1.3 Stuxnet Attack on Iranian Nuclear Power Facility 2.4.1.4 Houston, Texas, Water Distribution System Attack 2.4.1.5 Bowman Avenue Dam Cyberattack 2.5 Other Major Challenges Hindering Growth of IoT Network 2.5.1 Standardization Protocols 2.5.2 Cognitive Capability 2.5.3 Power 2.5.4 Consumer Illiteracy 2.5.5 Weak Regulations 2.5.6 Fear of Reputational Damage 2.6 Future Prospects 2.7 Conclusion References Chapter 3 Electrical Load Forecasting Using Bayesian Regularization Algorithm in Matlab and Finding Optimal Solution via Renewable Source 3.1 Introduction 3.2 Algorithm 3.2.1 Levenberg-Marquardt Algorithm 3.2.2 Bayesian Regularization 3.2.2.1 Comparison of Bayesian Models 3.2.2.2 Bayesian Ways to Neural Network Modeling 3.2.3 Scaled Conjugate Gradient Algorithm 3.2.3.1 Steps of Algorithm 3.2.4 Gradient Descent 3.2.5 Conjugate Gradient 3.3 Methodology and Modelling 3.4 Results and Discussion 3.5 Conclusion References Chapter 4 Theft Detection Sensing by IoT in Smart Grid 4.1 Introduction 4.1.1 Power Theft Identification 4.1.2 Basic Structure of Smart Grid 4.2 Problem Identification 4.2.1 Power Theft Methods 4.3 Methodology for Implementation of IoT to Different Theft Mechanisms in Smart Grid 4.4 Conclusion 4.5 Future Work References Chapter 5 Energy Metering and Billing Systems Using Arduino 5.1 Introduction 5.2 Smart Meters and Billing Systems 5.2.1 Arduino Mega 5.2.2 LCD 5.2.3 Proteus Software 5.3 Working 5.4 Applications 5.5 Time of Use 5.6 Observations 5.7 Equations 5.8 Results 5.9 Adoption in India 5.10 Excess Generation of Electricity 5.11 Commercial Use & Home Energy Monitoring 5.12 Conclusion References Chapter 6 Smart Meter Vulnerability Assessment Under Cyberattack Events – An Attempt to Safeguard 6.1 Introduction 6.2 Advanced Metering Infrastructure Architecture 6.2.1 Smart Meter Architecture and Design 6.2.2 AMI Communication Network 6.2.3 Home Area Network 6.2.4 Data Concentrator 6.3 Possible Attacks on AMI 6.3.1 Manual Attacks 6.3.2 Cyberattacks 6.3.3 Threats and Countermeasures of Attacks on Smart Meter 6.4 RSA Attack Detection Model 6.4.1 RSA Keys Creation 6.5 Hash Code for Data Integrity 6.6 Results and Discussion 6.6.1 Attack Detection System 6.6.2 Python Implementation 6.7 Conclusion References Chapter 7 Power Quality Improvement for Grid-Connected Hybrid Wind-Solar Energy System Using a Three-Phase Three-Wire Grid-Interfacing Compensator 7.1 Introduction 7.2 Proposed Current Control System 7.3 Simulation Analysis and Discussion 7.4 Conclusion References Chapter 8 Energy Trading in Virtual Power Plant Enabled Communities Using Double Auction Technique and Blockchain Technology 8.1 Introduction 8.2 Related Work 8.3 Proposed Methodology 8.3.1 System Model 8.3.2 Problem Formulation 8.3.2.1 Objective 1 (Optimum Reimbursements for both the Traders) 8.3.2.2 Objective 2 (Shortest Line Routing System) 8.3.2.3 Utility Function (Maximum Social Welfare) 8.3.3 Our Approach 8.3.3.1 Double Auction 8.3.3.2 Shortest Line Route Detection 8.3.3.3 Blockchain 8.3.3.4 ElGamal Cryptography 8.4 Performance Evaluation 8.4.1 Evaluation Methodology 8.4.2 Evaluation Results 8.5 Conclusion References Chapter 9 Sales Demand Forecasting for Retail Marketing Using XGBoost Algorithm 9.1 Introduction 9.2 Related Work 9.3 Methodology 9.3.1 XGBoost Algorithm 9.3.2 Architecture 9.4 Experimental Results 9.4.1 Exploratory Data Analysis 9.4.1.1 Empirical Cumulative Distribution Function (ECDF) 9.4.1.2 Exploring the Dataset and Making Visualizations between Months and Sales 9.4.1.3 Correlation between each Feature or Attribute 9.4.1.4 Time Series Analysis 9.4.2 Model Prediction 9.5 Conclusion References Chapter 10 Region-Based Convolutional Neural Networks for Selective Search 10.1 Introduction 10.2 Literature Review 10.3 Existing Method 10.4 Proposed Methodology 10.5 Implementation and Results 10.6 Conclusion References Chapter 11 Design and Development of Mobility System for Double Amputees 11.1 Introduction 11.2 Block Diagram 11.3 Working Methodology 11.4 Design Calculation 11.5 Hardware Implementation 11.6 Conclusion References Chapter 12 A Review: Precision Vehicle Control Using Internet of Things 12.1 Introduction 12.2 Related Works 12.3 Proposed Work 12.4 Existing System 12.4.1 Advantages 12.4.2 Disadvantages 12.4.3 Applications 12.5 Proposed System 12.6 Conclusion and Future Enhancement References Chapter 13 A Process of Analyzing Soil Moisture with the Integration of Internet of Things and Wireless Sensor Network 13.1 Introduction 13.1.1 WSN 13.1.2 IoT 13.2 Literature Study 13.3 Proposed Work 13.3.1 Sensing and Transmitter Module 13.3.2 Receiver Unit 13.3.3 IoT Activation 13.3.4 Event Recognition Algorithm 13.4 Result and Discussion 13.5 Conclusion References Chapter 14 Automatic Angular Position Stabilization of Ambulance Stretcher in Real Time 14.1 Introduction 14.2 Materials and Methods 14.2.1 Interior and Flaws 14.2.2 Proposed Position of the Stretcher 14.2.3 Hardware and Software 14.2.4 Methodology 14.3 Results and Discussion 14.3.1 Results 14.4 Discussion 14.5 Conclusion References Chapter 15 Automated Ploughing Seeding with Water Management System 15.1 Introduction 15.2 Block Diagram 15.3 Working Methodology 15.4 Design Calculation 15.5 Simulation 15.6 Hardware Implementation 15.7 Conclusion References Chapter 16 Detecting Fraudulent Data Using Stacked Auto-Encoding: A Three-Layer Approach 16.1 Introduction 16.1.1 Deep Learning 16.1.2 Auto-Encoders 16.2 Related Work 16.3 Proposed Methodology 16.4 Results and Discussion 16.5 Conclusion Acknowledgment References Chapter 17 Artificial Intelligence-Based Ambulance 17.1 Introduction 17.1.1 Problem Statement 17.1.2 Field of the Project 17.1.3 Objectives 17.2 Proposed System 17.2.1 Block Diagram of Traffic Signal Control System 17.2.2 Block Diagram of Biometric-Based Medical Records 17.3 Implementation of Traffic Signal Control System 17.3.1 Flowchart of Traffic Signal Control System 17.3.2 Algorithm of Biometric-Based Medical Records System 17.3.3 Methodology of Traffic Signal Control System 17.3.3.1 Normal Mode 17.3.3.2 Emergency Mode 17.3.4 Methodology of Biometric-Based Medical Records System 17.3.4.1 SMPT 17.4 Result and Discussion 17.4.1 Comparison of Results 17.4.2 Hardware Result 17.5 Conclusion 17.6 Future Scope References Chapter 18 LoRa-Based Flaw Location Detection in HT Line Using GSM 18.1 Introduction 18.1.1 Different Types of Transmission Line Fault 18.1.1.1 Single Line-to-Ground Fault 18.1.1.2 Line-to-Line Fault 18.1.1.3 Double Line-to-Ground Fault 18.1.1.4 Balance Three-Phase Fault 18.2 Objective 18.3 Literature Survey 18.4 Proposed System 18.5 Flow Chart 18.6 Result and Discussion 18.7 Novelty of Work 18.8 Conclusion 18.9 Future Enhancement References Chapter 19 Classification Models for Breast Cancer Detection 19.1 Introduction 19.2 Related Work 19.3 Research Objective 19.4 Methodology 19.4.1 Dataset Description 19.4.2 Data Preprocessing 19.4.3 Exploratory Data Analysis 19.5 Model Selection 19.5.1 Logistic Regression 19.5.2 Decision Tree Classifier 19.5.3 Random Forest Classifier 19.6 Results and Discussion 19.6.1 Confusion Matrix 19.6.2 Model Evaluation and Prediction 19.7 Conclusion References Chapter 20 T-Count Optimized Quantum Comparator Circuit 20.1 Introduction 20.2 Related Works 20.3 Proposed Quantum Comparator 20.3.1 Multi-Qubit Magnitude Comparator 20.4 Conclusion References Chapter 21 IoT-Based Heart Rate Monitoring System for Smart Healthcare Applications 21.1 Introduction 21.2 Related Work 21.3 Methodology 21.3.1 Fractional Fourier Transform 21.3.2 Amazon Web Services 21.4 Results and Discussion 21.5 Conclusion References Chapter 22 Neural Collaborative Filtering-Based Hybrid Recommender System for Online Movies Recommendation 22.1 Introduction 22.2 Related Works 22.3 Proposed Methodology 22.3.1 Dataset Used for the Proposed System 22.3.2 Architecture Diagram 22.3.3 Sentiment Analysis 22.3.4 Hybrid Recommendation 22.3.4.1 Filtering Based on Content 22.3.4.2 Collaborative Filtering 22.3.5 Neural Collaborative Filtering (NCF) 22.3.6 User-Based Recurrent Neural Networks (RNN) 22.4 Results and Discussion 22.5 Conclusion and Future Work References Chapter 23 Farmer’s Eye Using CNN 23.1 Introduction 23.2 Related Works 23.3 PV Module 23.4 Hardware Description 23.5 Software Implementation 23.6 Hardware Implementation 23.7 Conclusion References Chapter 24 Solar Powered Density and Emergency-Based Traffic Control System Using NI LabVIEW 24.1 Introduction 24.2 Literature Review 24.3 Methodology 24.3.1 Block Diagram 24.3.2 LabVIEW 24.4 Components 24.4.1 Main Components 24.4.1.1 Solar Panel 24.4.1.2 Battery 24.4.1.3 Buck Converter 24.4.1.4 IR Sensor 24.4.1.5 NI my RIO 24.4.1.6 NPN Transistor 24.4.1.7 Glue Sticks 24.4.1.8 Heat Sink Slive Tubes 24.4.1.9 Toggle Switch 24.4.2 Supporting Components 24.4.2.1 Connecting Pins 24.4.2.2 LEDS 24.5 Result 24.5.1 SIM View 24.6 Implementation of Hardware Components 24.7 Conclusion Applications References Chapter 25 Observation of TCSU: Travel Cold Storage Unit Operated by SPV Technology 25.1 Introduction 25.2 Working Methodology 25.3 Tools & Platform 25.4 Design & Implementation 25.5 Advantages & Application 25.6 Conclusion References Index EULA