Intelligent and Soft Computing Systems for Green Energy

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.

Table of Contents:
Preface xvii 1 Placement and Sizing of Distributed Generator and Capacitor in a Radial Distribution System Considering Load Growth 1 G. Manikanta, N. Kirn Kumar, Ashish Mani and V. Indragandhi 1.1 Introduction 2 1.2 Problem Formulation 3 1.3 Algorithm 5 1.4 Results & Discussions 9 1.5 Discussion 20 1.6 Conclusions 21 References 21 2 Security Issues and Challenges for the IoT-Based Smart Grid 25 Prathiga, Kavya K., Nanthitha N., Nithishkumar K., Ritika T. and Vishal T. 2.1 Introduction 25 2.2 Usage of IoT in the Smart Grid Context 27 2.3 Advantages of IoT-Based Smart Grid 29 2.4 Cybersecurity Challenges 30 2.4.1 Review of Recent Attacks 32 2.4.1.1 Tram Hack Lodz, Poland 32 2.4.1.2 Texas Power Company Hack 32 2.4.1.3 Stuxnet Attack on Iranian Nuclear Power Facility 32 2.4.1.4 Houston, Texas, Water Distribution System Attack 33 2.4.1.5 Bowman Avenue Dam Cyberattack 33 2.5 Other Major Challenges Hindering Growth of IoT Network 33 2.5.1 Standardization Protocols 33 2.5.2 Cognitive Capability 34 2.5.3 Power 34 2.5.4 Consumer Illiteracy 35 2.5.5 Weak Regulations 35 2.5.6 Fear of Reputational Damage 36 2.6 Future Prospects 36 2.7 Conclusion 38 References 39 3 Electrical Load Forecasting Using Bayesian Regularization Algorithm in Matlab and Finding Optimal Solution via Renewable Source 41 Chinmay Singh, Yashwant Sawle, Navneet Kumar, Utkarsh Jha and Arunkumar L. 3.1 Introduction 42 3.2 Algorithm 43 3.2.1 Levenberg-Marquardt Algorithm 43 3.2.2 Bayesian Regularization 45 3.2.2.1 Comparison of Bayesian Models 46 3.2.2.2 Bayesian Ways to Neural Network Modeling 46 3.2.3 Scaled Conjugate Gradient Algorithm 47 3.2.3.1 Steps of Algorithm 47 3.2.4 Gradient Descent 48 3.2.5 Conjugate Gradient 48 3.3 Methodology and Modelling 49 3.4 Results and Discussion 52 3.5 Conclusion 55 References 55 4 Theft Detection Sensing by IoT in Smart Grid 59 N. Siva Mallikarjuna Rao, M. Ramu and Lekha Varisa 4.1 Introduction 60 4.1.1 Power Theft Identification 60 4.1.2 Basic Structure of Smart Grid 60 4.2 Problem Identification 62 4.2.1 Power Theft Methods 62 4.3 Methodology for Implementation of IoT to Different Theft Mechanisms in Smart Grid 64 4.4 Conclusion 66 4.5 Future Work 67 References 67 5 Energy Metering and Billing Systems Using Arduino 69 M. Ramu, Lekha Varisa and N. Siva Mallikarjuna Rao 5.1 Introduction 69 5.2 Smart Meters and Billing Systems 72 5.2.1 Arduino Mega 72 5.2.2 Lcd 72 5.2.3 Proteus Software 73 5.3 Working 73 5.4 Applications 74 5.5 Time of Use 74 5.6 Observations 74 5.7 Equations 75 5.8 Results 75 5.9 Adoption in India 76 5.10 Excess Generation of Electricity 76 5.11 Commercial Use & Home Energy Monitoring 76 5.12 Conclusion 77 References 77 6 Smart Meter Vulnerability Assessment Under Cyberattack Events – An Attempt to Safeguard 79 Kunal Kumar and R. Raja Singh 6.1 Introduction 80 6.2 Advanced Metering Infrastructure Architecture 82 6.2.1 Smart Meter Architecture and Design 83 6.2.2 AMI Communication Network 83 6.2.3 Home Area Network 84 6.2.4 Data Concentrator 84 6.3 Possible Attacks on AMI 84 6.3.1 Manual Attacks 84 6.3.2 Cyberattacks 84 6.3.3 Threats and Countermeasures of Attacks on Smart Meter 87 6.4 RSA Attack Detection Model 87 6.4.1 RSA Keys Creation 89 6.5 Hash Code for Data Integrity 89 6.6 Results and Discussion 90 6.6.1 Attack Detection System 90 6.6.2 Python Implementation 91 6.7 Conclusion 93 References 94 7 Power Quality Improvement for Grid-Connected Hybrid Wind-Solar Energy System Using a Three-Phase Three-Wire Grid-Interfacing Compensator 97 Boopathi R. and Dr. Indragandhi V. 7.1 Introduction 98 7.2 Proposed Current Control System 100 7.3 Simulation Analysis and Discussion 103 7.4 Conclusion 107 References 108 8 Energy Trading in Virtual Power Plant Enabled Communities Using Double Auction Technique and Blockchain Technology 111 Radhika Yadav, Balla Manoj Kumar, Saurav Baid and Padma Priya R. 8.1 Introduction 112 8.2 Related Work 113 8.3 Proposed Methodology 114 8.3.1 System Model 115 8.3.2 Problem Formulation 116 8.3.2.1 Objective 1 (Optimum Reimbursements for both the Traders) 116 8.3.2.2 Objective 2 (Shortest Line Routing System) 116 8.3.2.3 Utility Function (Maximum Social Welfare) 116 8.3.3 Our Approach 117 8.3.3.1 Double Auction 117 8.3.3.2 Shortest Line Route Detection 119 8.3.3.3 Blockchain 119 8.3.3.4 ElGamal Cryptography 120 8.4 Performance Evaluation 121 8.4.1 Evaluation Methodology 121 8.4.2 Evaluation Results 122 8.5 Conclusion 123 References 124 9 Sales Demand Forecasting for Retail Marketing Using XGBoost Algorithm 127 M. Kavitha, R. Srinivasan, R. Kavitha and M. Suganthy 9.1 Introduction 128 9.2 Related Work 129 9.3 Methodology 130 9.3.1 XGBoost Algorithm 130 9.3.2 Architecture 131 9.4 Experimental Results 131 9.4.1 Exploratory Data Analysis 132 9.4.1.1 Empirical Cumulative Distribution Function (ECDF) 132 9.4.1.2 Exploring the Dataset and Making Visualizations between Months and Sales 133 9.4.1.3 Correlation between each Feature or Attribute 134 9.4.1.4 Time Series Analysis 134 9.4.2 Model Prediction 137 9.5 Conclusion 138 References 139 10 Region-Based Convolutional Neural Networks for Selective Search 141 R. Kavitha, Srinivasan R, P. Subha and M. Kavitha 10.1 Introduction 142 10.2 Literature Review 143 10.3 Existing Method 145 10.4 Proposed Methodology 145 10.5 Implementation and Results 147 10.6 Conclusion 149 References 150 11 Design and Development of Mobility System for Double Amputees 151 Dr. Saravanan T S, Dr. Sagayaraj R, Dr. Sivaraman P R, Sivamani D, Jaiganesh R and Ragupathy P 11.1 Introduction 152 11.2 Block Diagram 152 11.3 Working Methodology 153 11.4 Design Calculation 154 11.5 Hardware Implementation 156 11.6 Conclusion 159 References 159 12 A Review: Precision Vehicle Control Using Internet of Things 163 R. Srinivasan, Kavitha R, Kavitha M and Sridhar K 12.1 Introduction 163 12.2 Related Works 164 12.3 Proposed Work 166 12.4 Existing System 167 12.4.1 Advantages 167 12.4.2 Disadvantages 168 12.4.3 Applications 168 12.5 Proposed System 169 12.6 Conclusion and Future Enhancement 170 References 171 13 A Process of Analyzing Soil Moisture with the Integration of Internet of Things and Wireless Sensor Network 173 R. Srinivasan, Kavitha R, V. Murugananthan and T. Mylsami 13.1 Introduction 174 13.1.1 Wsn 174 13.1.2 IoT 174 13.2 Literature Study 175 13.3 Proposed Work 176 13.3.1 Sensing and Transmitter Module 176 13.3.2 Receiver Unit 178 13.3.3 IoT Activation 178 13.3.4 Event Recognition Algorithm 179 13.4 Result and Discussion 180 13.5 Conclusion 182 References 183 14 Automatic Angular Position Stabilization of Ambulance Stretcher in Real Time 185 Vedant Joshi, Maheshwari S. and Kathirvelan J. 14.1 Introduction 185 14.2 Materials and Methods 187 14.2.1 Interior and Flaws 187 14.2.2 Proposed Position of the Stretcher 188 14.2.3 Hardware and Software 188 14.2.4 Methodology 189 14.3 Results and Discussion 192 14.3.1 Results 192 14.4 Discussion 194 14.5 Conclusion 195 References 195 15 Automated Ploughing Seeding with Water Management System 199 Anto Sheeba J., Shyam D., Sivamani D., Sangari A., Jayashree K. and Nazar Ali A. 15.1 Introduction 199 15.2 Block Diagram 200 15.3 Working Methodology 201 15.4 Design Calculation 202 15.5 Simulation 203 15.6 Hardware Implementation 205 15.7 Conclusion 208 References 208 16 Detecting Fraudulent Data Using Stacked Auto-Encoding: A Three-Layer Approach 211 P. Saravanan, V. Indragandhi and V. Subramaniyaswamy 16.1 Introduction 211 16.1.1 Deep Learning 212 16.1.2 Auto-Encoders 212 16.2 Related Work 214 16.3 Proposed Methodology 215 16.4 Results and Discussion 218 16.5 Conclusion 221 Acknowledgment 221 References 221 17 Artificial Intelligence-Based Ambulance 223 Dr. R. Sumathi, R.M. Gokul, M. Gokulakrishnan, K. Ganesh Babu and S. Pavithra 17.1 Introduction 224 17.1.1 Problem Statement 224 17.1.2 Field of the Project 224 17.1.3 Objectives 225 17.2 Proposed System 225 17.2.1 Block Diagram of Traffic Signal Control System 225 17.2.2 Block Diagram of Biometric-Based Medical Records 226 17.3 Implementation of Traffic Signal Control System 226 17.3.1 Flowchart of Traffic Signal Control System 226 17.3.2 Algorithm of Biometric-Based Medical Records System 228 17.3.3 Methodology of Traffic Signal Control System 228 17.3.3.1 Normal Mode 229 17.3.3.2 Emergency Mode 230 17.3.4 Methodology of Biometric-Based Medical Records System 230 17.3.4.1 Smpt 230 17.4 Result and Discussion 231 17.4.1 Comparison of Results 231 17.4.2 Hardware Result 231 17.5 Conclusion 234 17.6 Future Scope 234 References 235 18 LoRa-Based Flaw Location Detection in HT Line Using GSM 237 Dr. M. Senthilkumar, Abisheck D., Gnana Prakash K., Hari Babu S. and Hariharan R. 18.1 Introduction 238 18.1.1 Different Types of Transmission Line Fault 238 18.1.1.1 Single Line-to-Ground Fault 238 18.1.1.2 Line-to-Line Fault 238 18.1.1.3 Double Line-to-Ground Fault 239 18.1.1.4 Balance Three-Phase Fault 239 18.2 Objective 240 18.3 Literature Survey 240 18.4 Proposed System 241 18.5 Flow Chart 244 18.6 Result and Discussion 244 18.7 Novelty of Work 248 18.8 Conclusion 250 18.9 Future Enhancement 251 References 252 19 Classification Models for Breast Cancer Detection 255 Varsha B., Sneka P., Tanuja A. and Shana J. 19.1 Introduction 255 19.2 Related Work 256 19.3 Research Objective 257 19.4 Methodology 257 19.4.1 Dataset Description 258 19.4.2 Data Preprocessing 258 19.4.3 Exploratory Data Analysis 258 19.5 Model Selection 260 19.5.1 Logistic Regression 260 19.5.2 Decision Tree Classifier 261 19.5.3 Random Forest Classifier 261 19.6 Results and Discussion 261 19.6.1 Confusion Matrix 261 19.6.2 Model Evaluation and Prediction 262 19.7 Conclusion 263 References 263 20 T-Count Optimized Quantum Comparator Circuit 265 Gayathri S. S., R. Kumar and Samiappan Dhanalakshmi 20.1 Introduction 265 20.2 Related Works 268 20.3 Proposed Quantum Comparator 268 20.3.1 Multi-Qubit Magnitude Comparator 268 20.4 Conclusion 270 References 270 21 IoT-Based Heart Rate Monitoring System for Smart Healthcare Applications 273 Jaba Deva Krupa Abel, Samiappan Dhanalakshmi, Sanjana N.L. and R. Kumar 21.1 Introduction 274 21.2 Related Work 275 21.3 Methodology 276 21.3.1 Fractional Fourier Transform 278 21.3.2 Amazon Web Services 280 21.4 Results and Discussion 281 21.5 Conclusion 283 References 284 22 Neural Collaborative Filtering-Based Hybrid Recommender System for Online Movies Recommendation 287 S. Priyanka, P. Saravanan, V. Indragandhi and V. Subramaniyaswamy 22.1 Introduction 288 22.2 Related Works 289 22.3 Proposed Methodology 290 22.3.1 Dataset Used for the Proposed System 291 22.3.2 Architecture Diagram 291 22.3.3 Sentiment Analysis 292 22.3.4 Hybrid Recommendation 293 22.3.4.1 Filtering Based on Content 293 22.3.4.2 Collaborative Filtering 293 22.3.5 Neural Collaborative Filtering (NCF) 294 22.3.6 User-Based Recurrent Neural Networks (RNN) 296 22.4 Results and Discussion 297 22.5 Conclusion and Future Work 299 References 300 23 Farmer’s Eye Using CNN 303 Elam Cheren S., Yuvan Raj Kumar M., Vivek G., Udhayakumar N. and Saravanakumar M. V. 23.1 Introduction 303 23.2 Related Works 304 23.3 PV Module 305 23.4 Hardware Description 306 23.5 Software Implementation 309 23.6 Hardware Implementation 311 23.7 Conclusion 313 References 313 24 Solar Powered Density and Emergency-Based Traffic Control System Using NI LabVIEW 315 M. Devika Rani, G. Bhavani, K. Kartheek, A. Sindhura and D. Nikhila 24.1 Introduction 315 24.2 Literature Review 316 24.3 Methodology 317 24.3.1 Block Diagram 317 24.3.2 LabVIEW 319 24.4 Components 322 24.4.1 Main Components 322 24.4.1.1 Solar Panel 322 24.4.1.2 Battery 323 24.4.1.3 Buck Converter 323 24.4.1.4 IR Sensor 323 24.4.1.5 NI my RIO 324 24.4.1.6 NPN Transistor 324 24.4.1.7 Glue Sticks 324 24.4.1.8 Heat Sink Slive Tubes 325 24.4.1.9 Toggle Switch 325 24.4.2 Supporting Components 326 24.4.2.1 Connecting Pins 326 24.4.2.2 Leds 326 24.5 Result 328 24.5.1 SIM View 328 24.6 Implementation of Hardware Components 330 24.7 Conclusion 332 Applications 332 References 332 25 Observation of TCSU: Travel Cold Storage Unit Operated by SPV Technology 335 Devesh Umesh Sarkar, Tapan Prakash, Madhur Zadegaonkar, Ritu Bhimgade, Abhijeeta Gupta and Nidhi Ambekar 25.1 Introduction 335 25.2 Working Methodology 336 25.3 Tools & Platform 338 25.4 Design & Implementation 338 25.5 Advantages & Application 341 25.6 Conclusion 341 References 342 Index 345

About the Author :
A. Chitra is an associate professor in the School of Electrical Engineering, at Vellore Institute of Technology, Vellore, India. She has published many papers in reputed journals and conferences and is a Board of Studies member at Pondicherry Engineering College, where she received a Gold Medal while studying for her MTech and also where she earned her PhD. V. Indragandhi, PhD, is an associate professor in the School of Electrical Engineering, VIT, Vellore, Tamilnadu. She received her PhD from Anna University in Chennai, India. She has over 12 years of experience in the area of power electronics and renewable energy systems and has authored over 100 research articles in leading peer-reviewed international journals. She has filed three patents and has one book to her credit. She has also received the best researcher award from NFED, Coimbatore and from VIT. W. Razia Sultana, PhD, is an associate professor in the School of Electrical Engineering, at the Vellore Institute of Technology University, Vellore, Tamil Nadu, India, where she also received her PhD.