
Applied Artificial Intelligence (AI) to Green Power Technology
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Content
- Intro
- Contents
- Preface
- Acknowledgments
- Chapter 1
- Energy Management and Artificial Intelligence
- Abstract
- Introduction
- Energy Management
- Overview
- Objectives
- Energy Management Process
- Electric Grid and Energy Management
- Artificial Intelligence
- AI for Energy Management
- Conclusion
- References
- Biographical Sketches
- Chapter 2
- Issues and Challenges of Latest Green Energy Technology Such as Fuel Cell, Waste to Energy and Application of AI
- Abstract
- Introduction
- Fuel Cell
- Artificial Intelligence Techniques
- Artificial Neural Networks
- Multi-Layer Perceptrons (MLPs)
- Radial Basis Functions (RBF)
- Fuzzy Logic
- AI Applications in Renewable Energy
- AI in Solar Energy
- AI in Wind Energy
- AI in Geothermal
- Challenges in AI Techniques for Green Energy
- Conclusion
- References
- Chapter 3
- Voltage Improvement of Short Shunt Self-Excited Induction Generators Using Gravitational Search Algorithms and Genetic Algorithms
- Abstract
- Introduction
- Literature Review
- Problem Structure
- Artificial Intelligence Techniques
- Gravitational Search Algorithm (GSA)
- Procedure to Be Followed for SEIG Operation
- Genetic Algorithm (GA)
- Steps to Be Followed for Genetic Algorithm in SEIG
- Result and Discussion
- Conclusion
- Appendix
- References
- Chapter 4
- Micro/Pico Hydropower Generation System Using Self-Excited Induction Generators and Applications of AI for Its Performance Improvement
- Abstract
- Introduction
- Description of Micro/Pico Hydropower Generation System
- Self-Excited Induction Generator: An Overview
- Problem Formulation
- Estimation of Hydro Capacity
- Application of AI for Performance Improvement
- Machine Learning
- Deep Learning
- Artificial Neural Network (ANN)
- Fuzzy Logic
- Adaptive Neuro-Fuzzy Interface System (ANFIS)
- Conclusion
- References
- Chapter 5
- An Investigation of Various Maximum Power Point Tracking Techniques Applied to Solar Photovoltaic Systems
- Abstract
- Introduction
- Basics of Solar Energy
- Solar Module Characteristics
- Maximum Power Point Tracking Techniques
- Perturb and Observe (P&O) Technique
- P&O Based Multiple Power Sample MPPT Technique
- Adaptive Perturb and Observe Technique
- Incremental Conductance Method
- Regulated Incremental and Conductance MPPT Technique
- Variable Step Incremental Conductance Technique
- Fractional Open Circuit Voltage Method (FOCV)
- Semi-Pilot Cell FOCV MPPT Technique
- Fractional Short Circuit Current (FSCC) Method
- Soft Computing Techniques
- Fuzzy Logic Control (FLC)
- Artificial Neural Network (ANN) Control
- Evolutionary Computing Control
- Comparison between Various MPPT Techniques
- Conclusion
- References
- Chapter 6
- Fuzzy Logic-Based Maximum Power for Grid Connected PV Systems
- Abstract
- Introduction
- A Variety of Renewable Energy Sources
- Wind Power
- Solar Power
- Small Hydropower
- Biomass
- Geothermal
- Trends of RES around the Globe
- Solar Cell
- Operating Principle
- The Need of Renewable Energy
- The Mathematical Equation for MPP
- Literature Review
- Simulation Models and Blocks
- PV Modelling
- Photovoltaic Cell Simulink Model in MATLAB
- Effect of Load Mismatching
- Boost Converter
- Procedure for Designing a Boost Converter
- Maximum Power Point Tracking Algorithms
- A Study on MPPT Techniques
- Algorithm for Fuzzy Logic
- Detailed Information of Perturb and Observe Algorithm
- Implementation Method
- Result and Discussion
- Results for PV System with Battery Integration by Using Fuzzy Logic Algorithm MPPT Techniques
- Conclusion
- Future Scope
- References
- Chapter 7
- Different Reconfiguration Approaches for Photovoltaic Systems
- Abstract
- Introduction
- Mathematical Modelling of Solar Cell
- Various Modelling Topologies for Observing PSC Effects
- Basic Connecting Topologies
- Series-Parallel (S-P)
- Bridge-Linked (B-L)
- Total Cross-Tied (TCT)
- Advanced Reconfiguration Topologies
- Ken-Ken Reconfiguration (K-K)
- Arithmetic Sequence Reconfiguration (AS)
- L-Shape Reconfiguration (L-S)
- Performance Indices under PSC
- Global Maximum Power Point (GMPP)
- Efficiency (?)
- Fill Factor (FF)
- % Power Loss (%PL)
- Mismatch Loss (ML)
- Execution Ratio (ER)
- Result and Discussion
- Global Maximum Power Point (GMPP)
- Efficiency (?)
- Fill Factor (FF)
- % Power Loss (%PL)
- Mismatch Loss (ML)
- Execution Ratio (ER)
- Comparison of TCT and L-S
- Conclusion
- References
- Chapter 8
- Implementation of Metaheuristic MPPT Approaches for a Large-Scale Wind Turbine System
- Abstract
- Introduction
- System Description and Modeling
- Wind Turbine Model
- Maximum Power Point Tracking
- WTS Maximum Power Point Tracking Algorithms
- Grey Wolf Optimization Based MPPT Algorithm
- Hybrid Particle Swarm Optimization with Grey Wolf Optimization Based MPPT
- Whale Search Optimization Algorithm Based MPPT
- Differential Squirrel Search Algorithm Based MPPT
- Grasshopper Optimization Based MPPT
- Experimental Assesment
- Result and Discussion
- Conclusion
- References
- Chapter 9
- Wind Power Prediction Using Hybrid Soft Computing Models
- Abstract
- Introduction
- Wind Power Prediction Techniques
- Wavelet Transform (WT)
- Adaptive Network-Based Fuzzy Inference System (ANFIS)
- Dynamic Recurrent Neural Networks (DNNs)
- NAR Neural Network
- NARX Neural Network
- Dynamic Particle Swarm Optimization (DPSO)
- Wind Power Forecasting Using the Proposed Hybrid Technique
- Wind Power Prediction Using Hybrid NAR/NARX Model
- Conclusion
- References
- Chapter 10
- Design Optimization of Inner Rotor Permanent Magnet Synchronous Machine Used in Wind Energy Conversion System Using Swarm Intelligence
- Abstract
- Introduction
- Problem Formulation
- Design Problem
- Optimizing Techniques
- Algorithm of GSA and GSA-PSO Technique
- Result and Discussion
- Conclusion
- References
- Chapter 11
- A Novel Voltage Stability Index and Application of Machine Learning Algorithm for Assessment of Voltage Stability
- Abstract
- Introduction
- The Existing Indices for Assessment of Voltage Stability
- Line Stability Index (Lmn)
- Fast Voltage Stability Index (FVSI)
- New Voltage Stability Index (NVSI)
- Proposed Modified Voltage Stability Index (MVSI)
- Results and Comparative Analysis of MVSI vs Other Indices
- IEEE 30 Bus System Results
- Base Load Operating Condition
- Heavy Active Loading Condition
- Heavy Reactive Loading Condition
- Heavy MVA Loading Condition
- IEEE 57 Bus System Results
- Base Load Operating Condition
- Active Power Loading Condition
- Reactive Power Loading Condition
- IEEE 118 Bus System Results
- Base Load Operating Condition
- Active Power Loading Condition
- Reactive Power Loading Condition
- The Machine Learning Approach for Voltage Stability Assessment
- The Exponential GPR Machine Learning Algorithm
- Methodology
- Results and Comparative Analysis of Exponential GPR vs NR Method MVSI Indices
- Comparative Analysis
- IEEE 30 Bus System
- IEEE 57 Bus System
- IEEE 118 Bus System
- Conclusion
- References
- Biographical Sketches
- Editors' Contact Information
- Index
- Blank Page
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