This second volume in a two-volume set continues to present the state of the art for the concepts, practical applications, and future of renewable energy and how to move closer to true sustainability.
Table of ContentsPreface
23. Energy Economics and EnvironmentP. Sanjeevikumar, Morteza Azimi Nasab, Mohammad Zand, Farnaz Hassani and Fatemeh Nikokar
Abbreviations
23.1 Introduction
23.1.1 The Concept of Microgrids
23.2 Benefits and Drawbacks of Microgrids
23.3 Causes of Increase in Power Plants
23.4 Demand Side Management in Microgrids
23.5 Centralized Control of Smart Grid
23.6 Decentralized Smart Grid Control
23.7 DER Resource Control Strategies in the Smart Grid
23.8 DER Participation Strategy in Smart Grid
23.9 Topics Raised in the Smart Grid
23.10 Smart Grid Protection
23.11 Detection of Smart Grid Islands
23.12 Smart Grid Optimization
23.13 Power Quality
23.14 Frequency and Voltage Control
23.15 Balance between Production and Power Consumption
23.16 Ability to Easily Connect Distributed Generation Sources
23.17 Smart Network Security
23.18 Resynchronization after Network Connection
23.19 Smart Grid Control Glasses
23.20 Economic Dimensions
23.21 Losses
23.22 Non-Technical Network Losses
23.23 Power System Loss Analysis
23.24 The Impact of the Electricity Market on the Performance of Distribution Companies
23.25 Power Quality in the Restructured Electricity Market
23.26 Conclusion
References
24. Stringent Energy Management Strategy during Covid-19 PandemicNagajayanthi B.
24.1 Introduction
24.2 Energy Management
24.3 Smart Grid Design
24.3.1 Ground Station
24.3.2 Gateway
24.3.3 Cloud
24.4 Smart Grid Design and Testing
24.5 Implementation of Smart Grid
24.6 Energy Management to Check Overload Conditions
24.6.1 With Varying Input Voltage and Without Load
24.6.2 With Increased Input Voltage but Without Load
24.6.3 With Optimum Input Voltage and Load
24.7 Features of Smart Grid System
24.8 Conclusion and Future Work
References
25. Energy Management Strategy for Control and PlanningAnmol D. Ganer
25.1 Energy Management and Audit
25.1.1 Steps for Energy Audit Management
25.1.2 How An Energy Audit can be An Effective Energy Management
25.1.3 Power Conservation through Energy Audit
25.1.4 Study of Energy Management and Audit
25.2 The Different Steps of an Energy Management Approach
25.2.1 State-Wise Generation Capacity till 2019
25.2.2 The Effective Plan should Incorporate Four Basic Steps
25.3 Preliminary Technical and Economic
25.3.1 Assessment of Synthetic Gas to Fuel and Chemical with Emphasis on the Potential for Biomass Derived Syngas
25.3.2 Natural Gas Storage/Co-Fired Retrofit System
25.4 Evaluation of Energy-Saving Investments
25.4.1 Power Survey – Energy Inspection
25.5 Off-Line and On-Line Procedures
25.5.1 Concept
25.6 Personnel Training
25.6.1 Training Method for Electricity Work Safety
25.7 A Successful Energy Management Program
25.7.1 Introduction
25.7.2 Power Administration Project
25.7.3 Corporate Structure
25.7.4 Energy Management Managers
25.8 Centralize Control of Process and Facility Plants
25.8.1 Centralized and Decentralized Waste Water Management
25.8.2 Central Jurisdiction System
25.8.3 Centralized Process Control System
25.9 Energy Security
25.9.1 Energy Security Concept
25.9.2 Smart Grid Security
25.10 Evaluate Energy Performances
25.10.1 Concept
25.10.2 Building Energy Performance
25.10.3 Illumination and Energy Performance
25.10.4 Energy Performance of Water Chillers
25.11 Energy Action Planning
25.12 Energy Economics
25.13 Case Study
References
26. Day-Ahead Solar Power Forecasting Using Statistical and Machine Learning MethodsAadyasha Patel and O.V. Gnana Swathika
Abbreviations
26.1 Introduction
26.2 Durations of Forecasting
26.3 Forecasting Techniques
26.4 Statistical Methods
26.4.1 Grey-Box Model (GB)
26.4.2 Grey Theory (GT)
26.4.3 Markov Chain Model (MM)
26.4.4 Bayesian Optimization
26.4.5 Linear Pool Ensemble (LPE)
26.4.6 Variational Mode Decomposition (VMD)
26.4.7 Autoregressive Integrated Moving Average (ARIMA)
26.4.8 Quantile Regression Averaging (QRA)
26.4.9 Logistic Model Trees
26.4.10 k-Nearest Neighbours (kNN)
26.5 Machine Learning Techniques
26.5.1 Machine Learning (ML)
26.5.2 Automatic Machine Learning (AML)
26.5.3 Extreme Learning Machine (ELM)
26.5.4 Quantile Random Forest (QRF)
26.5.5 Support Vector Regression (SVR)
26.5.6 Least-Square Support Vector Machine (LSSVM)
26.5.7 Principal Component Analysis (PCA)
26.5.8 Hierarchical Similarity-Based Forecasting Model (hSBFM)
26.5.9 Local Sensitive Hashing Algorithm (LSH)
26.6 Deep Learning (DL)
26.6.1 Artificial Neural Network (ANN)
26.6.2 Feed Forward Neural Network (FFNN)
26.6.3 Convolutional Neural Network (CNN)
26.6.4 Elman-Based Neural Network (ENN)
26.6.5 Deep Belief Network (DBN)
26.6.6 Long Short-Term Memory (LSTM)
26.6.7 Autoencoder Long Short-Term Memory (AE-LSTM)
26.6.8 Self-Organizing Maps (SOM)
26.7 Evaluation Index and Metrics
26.8 Conclusions
References
27. A Review on Optimum Location and Sizing of DGs in Radial Distribution SystemP. Tejaswi and O.V. Gnana Swathika
Abbreviations
27.1 Introduction
27.1.1 DG Planning Based on Multi-Objective Optimization Techniques
27.1.2 Optimal Placement and Sizing of DG Based on Multi-Objective Optimization Techniques
27.2 Proposed Location and Sizing of DGs in RDS Using Analytical and PSO Methods
27.2.1 Methodology
27.2.1.1 Distribution Load Flow Solution
27.2.1.2 Multiple DG Allocation and DG Size
27.2.1.3 PSO Algorithm
27.2.2 Multi-Objective Function
27.3 Result
27.4 Conclusion
27.5 Appendix: List of Symbols
References
28. High Step Up Non-Isolated DC-DC Converter Using Active-Passive Inductor CellsKanimozhi, G., Amritha, G. and O.V. Gnana Swathika
28.1 Introduction
28.2 Proposed Converter
28.2.1 Features of the Suggested Converter
28.3 Modes of Operation
28.4 Design Considerations
28.5 Simulation
28.5.1 Simulation for n=1
28.5.2 Simulation Results for n=2
28.6 Hardware Results
28.7 Conclusion
References
29. A Non-Isolated Step-Up Quasi Z-Source Converter Using Coupled InductorShashank, P.C. and Kanimozhi, G.
29.1 Introduction
29.2 Improved Quasi Z Source Converter with Coupled Inductor
29.3 Modes of Operation
29.4 Simulation Results
29.5 Comparison
29.6 Conclusion
References
30. Datalogger Aided Stand-Alone PV System for Rural ElectrificationAashiq A., Haniya Ashraf, Supraja Sivaviji, Aadyasha Patel and O.V. Gnana Swathika
Abbreviations and Nomenclature
30.1 Introduction
30.1.1 Motivation
30.1.2 Objectives
30.2 Work Description
30.2.1 Overview of the Work
30.2.2 Literature Review
30.2.3 Methodologies
30.2.4 Optimization Techniques
30.2.5 IoT and Smart Technologies
30.2.6 Conclusion
30.3 Design and Realisation of DL
30.3.1 DL Description
30.3.2 Solar Panel
30.3.3 Arduino Uno and IDE
30.3.4 Voltage Sensor
30.3.5 Current Sensor
30.3.6 PLX-DAQ Data Acquisition Tool
30.3.7 Software Specifications
30.3.8 Methodology
30.3.8.1 Data Logging into Excel Macro Spreadsheet
30.3.8.2 Prediction Using Mathematical Model
30.4 Results
30.4.1 Prediction Results
30.4.2 Performance Metrics
30.4.2.1 MAPE
30.5 Conclusion
30.5.1 Cost Calculation
30.5.2 Scope of Work
30.5.3 Summary
References
31. Working and Analysis of an Electromagnet-Based DC V-Gate Magnet Motor for Electrical ApplicationsG. Naveen Kumar, K. Indrasena Reddy and P. Ravi Teja
31.1 Conceptual Introduction
31.2 Existing Technologies to Review
31.3 Proposed Design
31.4 Block Schematic
31.5 Motor Assembly and Control Structure
31.6 Control Operation of the V-Gate Magnet Motor
31.7 Results and Analysis
31.8 Conclusion and Further Scope of Research
References
32. Design and Realization of Smart and Energy-Efficient DoorbellShubham Pandiya, Saurabh Shukla, Saransh, Anantha Krishnan V. and Gnana Swathika O.V.
32.1 Introduction
32.2 Methodology
32.3 Design and Specification
32.3.1 Software-Based Approach
32.3.1.1 Component Used
32.3.1.2 Circuit Diagram
32.3.2 Hardware-Based Approach
32.3.2.1 Components Used
32.3.2.2 Circuit Diagram
32.4 Result and Discussion
32.5 Conclusion
References
33. Optimal Solar Charging Enabled Autonomous Cleaning RobotAastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
33.1 Introduction
33.2 Methodology
33.2.1 Design Specification
33.2.2 Trash Detection
33.2.3 Movement Algorithm
33.2.4 Solar Charging
33.2.5 Remote Monitoring
33.3 Results
33.3.1 Trash Detection Results
33.3.2 Solar Charging Results
33.3.3 Remote Monitoring Dashboard
33.4 Conclusion
References
34. Real-Time Health Monitoring System of a Distribution TransformerAastha Malhotra, Anagha Darshan, Naman Girdhar, Prantika Das, Rohan Bhojwani, Anantha Krishnan V. and O.V. Gnana Swathika
34.1 Introduction
34.2 Flow Diagram
34.3 Operating Principle
34.4 Observation and Result
34.5 IFTTT Email Notification (in case of a fault)
34.6 Conclusion
References
35. Analysis of Wide-Angle Polarization-Insensitive Metamaterial Absorber Using Equivalent Circuit Modeling for Energy Harvesting ApplicationKanwar Preet Kaur and Trushit Upadhyaya
35.1 Introduction
35.2 Absorber Theory and Proposed Unit Cell Design
35.3 Equivalent Circuit Model
35.4 Simulation Results
35.4.1 Retrieval of the Effective MMA Parameters
35.4.2 Absorption Mechanism
35.4.3 Polarization Angle and Oblique Angle Variations
35.4.4 Resistive Load Variations
35.5 Experimental Results
35.6 Conclusion
References
36. World Energy DemandSatish R. Billewar, Gaurav Londhe and Pradip Suresh Mane
36.1 Energy End Users
36.2 Rural Electrification
36.3 Residential and Non-Residential Buildings
36.3.1 Urban and Semi-Urban Zones Power Requirement
36.3.2 Rural Residential Requirements
36.3.3 Non Residential Buildings
36.4 Industry
36.4.1 Industrialization, the Environment, and Pollution
36.4.2 Green Industry Initiative
36.5 Transport
36.5.1 The United Nations Environment Programme (UNEP)
36.5.2 The Initiatives of Countries
36.5.3 Sustainable Development Goals (SDGs)
36.5.4 Economic Sector Initiatives
36.5.5 Social Sector Initiatives
36.5.6 Environmental Sector Initiatives
36.5.7 The ASI Approach
36.6 Agriculture
36.6.1 Soil Fertility and Irrigation
36.6.2 Pesticides and Biomass Pollution Control
36.6.3 Agroforestry
36.6.4 Biotechnologies
36.7 Performance Mapping in Conjunction with Technological Evolution
References
37. Education in Energy Conversion and ManagementSatish R. Billewar, Karuna Jadhav and Gaurav Londhe
37.1 Role of University
37.2 Personnel Training
37.3 Awareness of Energy Conversion and Management as an Intersectoral Discipline
37.4 Climate Change
37.5 Economic Policy Options
37.6 Policy in Practice
37.7 Green Economy
37.8 The Relationship between the Economy and the Environment
37.8.1 Assessing Pollution’s Environmental Impact
37.8.2 Ecosystem Recovery and Rehabilitation
37.8.3 Sustainable Development Ideology
37.9 Industrial Ecology
37.9.1 Ecosystem’s Health and Adaptability
37.10 Does Protecting the Environment Harm the Economy?
37.10.1 Market and Accounting Mechanism
37.10.2 UN Environment Program (UNEP)
37.11 Creating a Green Economy
37.11.1 Green Project Financing
37.11.2 Natural Capital Sustainably
37.11.3 Partnerships
37.11.4 Educational Sustainability
37.11.5 Environment Friendly Technologies
References
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