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.

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.

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

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