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Fault diagnosis and sustainable control of wind turbines : robust data-driven and model-based strategies /

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Fault Diagnosis and Sustainable Control of Wind Turbines: Robust Data-Driven and Model-Based Strategies discusses the development of reliable and robust fault diagnosis and fault-tolerant ('sustainable') control schemes by means of data-driven and model-based approaches. These strategies a...

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Bibliographic Details
Main Authors: Simani, Silvio, 1971- (Author), Farsoni, Saverio (Author)
Corporate Author: ScienceDirect (Online service)
Format: eBook
Language:English
Published: Oxford, United Kingdom : Butterworth-Heinemann, [2018]
Subjects:
Wind turbines.
Éoliennes.
wind turbines.
TECHNOLOGY & ENGINEERING > Mechanical.
Wind turbines
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Machine generated contents note: 1. Introduction
  • 1.1. Introduction
  • 1.2. Motivations
  • 1.3. Nomenclature
  • 1.4. Introduction to Wind Turbine Modeling
  • 1.5. Introduction to Fault Diagnosis Methods
  • 1.6. Introduction to Fault Tolerant Control Methods
  • 1.7. Modeling and Advanced Control Benchmarking
  • 1.8. Outline of the Monograph
  • 1.9. Summary
  • 2. System and Fault Modeling
  • 2.1. Introduction
  • 2.2. System Description
  • 2.2.1. Wind Turbine Categories
  • 2.3. Wind Turbine Main Components
  • 2.3.1. Aerodynamic System
  • 2.3.2. Drive-Train Model
  • 2.3.3. Load Carrying Structure and Blade Models
  • 2.3.4. Power System Model
  • 2.3.5. Pitch System Model
  • 2.3.6. Wind Model
  • 2.3.7. Model-Reality Mismatch
  • 2.3.8. Actuator and Sensor Models
  • 2.3.9. Overall Model Structure
  • 2.4. Wind Turbine Control Issues
  • 2.4.1. Advanced Control Solutions
  • 2.4.2. Wind Turbines Feedback Control
  • 2.4.3. Structural and Drive-Train Stress Damper
  • 2.4.4. Bumpless Transfer
  • 2.5. Wind Turbine Benchmark
  • 2.5.1. Wind Turbine Benchmark Model
  • 2.5.2. Wind Turbine Controller Model
  • 2.5.3. Measurement Model
  • 2.5.4. Wind Turbine Fault Scenario
  • 2.5.5. Model Parameters
  • 2.5.6. Wind Turbine Benchmark Overall Model
  • 2.6. Wind Farm Benchmark
  • 2.6.1. Wind and Wake Model
  • 2.6.2. Wind Farm Benchmark Overall Model
  • 2.6.3. Wind Farm Fault Scenario
  • 2.6.4. Model Parameters
  • 2.7. Fault Analysis
  • 2.7.1. Failure Mode and Effect Analysis
  • 2.7.2. Fault Specifications and Requirements
  • 2.8. Summary
  • 3. Fault Diagnosis for Wind Turbine Systems
  • 3.1. Introduction
  • 3.1.1. Plant and Fault Models
  • 3.1.2. Residual Generation General Scheme
  • 3.1.3. Residual Evaluation for Change Detection
  • 3.2. Residual Generation Model-Based Approaches
  • 3.2.1. Parity Space Methods
  • 3.2.2. Observer-Based Methods
  • 3.2.3. Filtering Methods
  • 3.2.4. Nonlinear Geometric Approach Method to FDI
  • 3.3. Residual Generation Data-Driven Approaches
  • 3.3.1. Recursive Identification Approaches
  • 3.3.2. Artificial Intelligence Methods
  • 3.3.3. Fault Diagnosis Technique Integration
  • 3.4. Robust Residual Generation Issues
  • 3.5. Summary
  • 4. Fault Tolerant Control for Wind Turbine Systems
  • 4.1. Introduction
  • 4.1.1. Integration of Fault Diagnosis and Control
  • 4.1.2. Nonlinear Adaptive Filters for Fault Estimation
  • 4.2. Wind Turbine Control Strategies
  • 4.2.1. Fuzzy Modeling for Control
  • 4.2.2. Recursive Identification for Adaptive Control
  • 4.2.3. Sustainable Control
  • 4.3. Fault Tolerant Control Architectures
  • 4.3.1. Controller Compensation and Active Fault Tolerance
  • 4.4. Fault Tolerant Control Oriented Fault Diagnosis
  • 4.4.1. Fault Tolerant Control for Wind Turbine Systems
  • 4.5. Summary
  • 5. Application Results
  • 5.1. Introduction
  • 5.2. Wind Turbine Model Application
  • 5.2.1. Data-Driven Fault Diagnosis Examples
  • 5.2.2. Model-Based Fault Diagnosis Examples
  • 5.2.3. Fault Diagnosis Comparative Results
  • 5.2.4. Performance and Robustness Analysis
  • 5.3. Advanced Control Designs for Wind Turbines
  • 5.3.1. Sustainable Control Design
  • 5.3.2. Data-Driven Fault Tolerant Control Examples
  • 5.3.3. Model-Based Fault Tolerant Control Examples
  • 5.3.4. Performance Evaluation and Robustness Analysis
  • 5.3.5. Comparative Results and Stability Analysis
  • 5.4. Wind Farm Model Application
  • 5.4.1. Control Design for Wind Farm
  • 5.4.2. Data-Driven Fault Diagnosis
  • 5.4.3. Model-Based Fault Diagnosis
  • 5.4.4. Comparative and Robustness Analysis
  • 5.4.5. Sustainable Control for the Wind Farm Simulator
  • 5.5. Summary
  • 6. Matlab and Simulink Implementations
  • 6.1. Introduction
  • 6.2. Wind Turbine System Benchmark
  • 6.2.1. Wind Turbine Simulator Main Components
  • 6.2.2. Aerodynamic Block
  • 6.2.3. Drive-Train Block
  • 6.2.4. Power System Block
  • 6.2.5. Pitch System Block
  • 6.2.6. Wind Model Block
  • 6.2.7. Actuator and Sensor Model Block
  • 6.2.8. Wind Turbine Controller Block
  • 6.2.9. Wind Turbine Fault Blocks
  • 6.2.10. Wind Turbine Model Parameter Initialization
  • 6.3. Wind Farm System Benchmark
  • 6.3.1. Wind and Wake Block
  • 6.3.2. Wind Farm Fault Block
  • 6.3.3. Wind Farm Model Parameter Initialization
  • 6.3.4. Fault Diagnosis Module Implementation
  • 6.3.5. Fault Tolerant Control Module Implementation
  • 6.3.6. Monte Carlo Simulation Tool
  • 6.3.7. Hardware-In-The-Loop Tests
  • 6.4. Summary
  • 7. Conclusions
  • 7.1. Introduction
  • 7.2. Closing Remarks
  • 7.3. Further Work and Open Problems
  • 7.3.1. Sustainable Control Design Objectives
  • 7.3.2. Sustainable Control Concepts and Approaches
  • 7.3.3. Sustainable Control Approaches and Working Methods
  • 7.3.4. Sustainable Control Design Ambition
  • 7.3.5. Sustainable Control Innovation Potentials
  • 7.3.6. Sustainable Control Expected Impacts
  • 7.4. Summary.