Fault Diagnosis and Sustainable Control of Wind Turbines - 1st Edition - ISBN: 9780128129845

Fault Diagnosis and Sustainable Control of Wind Turbines

1st Edition

Robust Data-Driven and Model-Based Strategies

Authors: Silvio Simani Saverio Farsoni
Paperback ISBN: 9780128129845
Imprint: Butterworth-Heinemann
Published Date: 1st January 2018
Page Count: 228
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Description

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 are able to cope with unknown nonlinear systems and noisy measurements. The book also discusses simpler solutions relying on data-driven and model-based methodologies, which are key when on-line implementations are considered for the proposed schemes. The book targets both professional engineers working in industry and researchers in academic and scientific institutions.

In order to improve the safety, reliability and efficiency of wind turbine systems, thus avoiding expensive unplanned maintenance, the accommodation of faults in their early occurrence is fundamental. To highlight the potential of the proposed methods in real applications, hardware–in–the–loop test facilities (representing realistic wind turbine systems) are considered to analyze the digital implementation of the designed solutions. The achieved results show that the developed schemes are able to maintain the desired performances, thus validating their reliability and viability in real-time implementations.

Different groups of readers—ranging from industrial engineers wishing to gain insight into the applications' potential of new fault diagnosis and sustainable control methods, to the academic control community looking for new problems to tackle—will find much to learn from this work.

Key Features

  • Provides wind turbine models with varying complexity, as well as the solutions proposed and developed by the authors
  • Addresses in detail the design, development and realistic implementation of fault diagnosis and fault tolerant control strategies for wind turbine systems
  • Addresses the development of sustainable control solutions that, in general, do not require the introduction of further or redundant measurements
  • Proposes active fault tolerant ('sustainable') solutions that are able to maintain the wind turbine working conditions with gracefully degraded performance before required maintenance can occur
  • Presents full coverage of the diagnosis and fault tolerant control problem, starting from the modeling and identification and finishing with diagnosis and fault tolerant control approaches
  • Provides MATLAB and Simulink codes for the solutions proposed

Readership

Mechanical, Electrical and Power engineers working in industry and researchers in academic and scientific institutions wishing to gain insight into the applications potential of new fault diagnosis and sustainable control methods

Table of Contents

Chapter 1 Introduction
1.1 Motivations
1.2 Nomenclature
1.3 Fault Diagnosis Methods
1.4 Fault Tolerant Control Methods
1.5 Outline of the Monograph
Chapter 2 System and Fault Modelling
2.1 System Description
2.1.1 Wind Turbine Categories
2.1.2 Main Components of Wind Turbines
2.1.3 The Overall Wind Turbine Analytical Description
2.1.4 Wind Turbine Control Issues
2.2 The Wind Turbine Benchmark System
2.2.1 The Turbine Model
2.2.2 The Controller Model
2.2.3 The Measurement Model
2.2.4 The Fault Scenarios
2.2.5 Model Parameters
2.2.6 The Complete Model
2.3 The Wind Farm Benchmark System
2.3.1 The Wind and Wake Model
2.3.2 The Plant Model
2.3.3 The Fault Scenarios
2.3.4 Model Parameters
Chapter 3 Data–Driven Modelling and Identification
3.1 Fuzzy Modelling and Identification
3.1.1 Introduction to Fuzzy Logic
3.1.2 Takagi–Sugeno Fuzzy Rules
3.1.3 FIS Design from Data
3.2 Neural Network Modelling
3.2.1 Introduction to Neural Network
3.2.2 Neural Network Architectures
3.2.3 Training the Network
3.2.4 Other Training Algorithms
3.2.5 Problems with Neural Networks
Chapter 4 Fault Diagnosis and Fault Tolerant Control Schemes
4.1 Failure Mode & Effect Analysis
4.2 Fault Diagnosis
4.3 Fault Tolerant Control
Chapter 5 Nonlinear Geometric Approach for Fault Diagnosis
5.1 NLGA FDI Scheme Design
5.2 NLGA Robustness Improvements
5.2.1 Filter and Observer Residual Function Forms
5.2.2 NLGA Residual Optimisation
5.3 NLGA Adaptive Filter Fault Estimation
5.3.1 Adaptive Filtering Algorithm
5.3.2 Disturbance Distribution Estimation
Chapter 6 Simulations, Experiments and Results
6.1 Wind Turbine Simulations
6.1.1 Fault Diagnosis via Fuzzy Identified Models
6.1.2 Fault Diagnosis via Neural Networks
6.1.3 Validation and Comparative Analysis
6.1.4 Fault Tolerant Control
6.2 Wind Farm Simulations
6.2.1 Fault Diagnosis
6.2.2 Comparative Analysis
6.2.3 Fault Tolerant Control
6.3 Hardware in the Loop Tests
6.4 Wind Farm NLGA AFTC
Chapter 7 Conclusions
7.1 Concluding Remarks
7.2 Summary
7.3 Further Works
References

Details

No. of pages:
228
Language:
English
Copyright:
© Butterworth-Heinemann 2018
Published:
Imprint:
Butterworth-Heinemann
Paperback ISBN:
9780128129845

About the Author

Silvio Simani

Dr. Silvio Simani received his Laurea degree (cum laude) in Electronic Engineering from the Department of Engineering at the University of Ferrara, Italy, in 1996, and was awarded the Ph.D. in Information Science (Automatic Control) at the Department of Engineering of the University of Ferrara and Modena, Italy, in 2000. Since February 2002 he has been Assistant Professor at the Department of Engineering of the University of Ferrara. He has published about 240 refereed journal and conference papers, several book’s chapters, and 3 monographs. His research interests include fault diagnosis and fault tolerant control of linear and nonlinear dynamic processes, system modelling, identification and data analysis, linear and nonlinear filtering techniques, fuzzy logic and neural networks for modelling and control, as well as the interaction issues among identification, fault diagnosis, and fault tolerant control.

Affiliations and Expertise

Assistant Professor, Department of Engineering, University of Ferrara

Saverio Farsoni

Saverio Farsoni was born in Mirandola (MO, Italy) in 1987. In 2012 He graduated (cum laude) in Informatics and Automation Engineering at the University of Ferrara with a M. Sc. thesis on simulations in bio–medical environments. Since 2013 he has been PhD student in Engineering Science and, together with his supervisor, Dr. Simani, he works on control systems, fuzzy logic, modelling and identification problems. In particular, his researches deal with fault diagnosis and fault tolerant control for eolic plants, and he published some conference papers about these issues

Affiliations and Expertise

Visiting Assistant Professor, Department of Engineering, University of Ferrara