Intelligent and Soft Computing Systems for Green Energy (eBook, PDF)

Redaktion: Chitra, A.; Sultana, W. Razia; Indragandhi, V.

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: John Wiley & Sons
• Seitenzahl: 384
• Erscheinungstermin: 3. Mai 2023
• Englisch
• ISBN-13: 9781394167517
• Artikelnr.: 67973407

Autorenporträt

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.

Inhaltsangabe

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