Intelligent and Soft Computing Systems for Green Energy

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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.

Author(s): A. Chitra, V. Indragandhi, W. Razia Sultana
Publisher: Wiley-Scrivener
Year: 2023

Language: English
Pages: 371
City: Beverly

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