Structural Control and Fault Detection of Wind Turbine Systems
With the rapid growth of wind energy worldwide, challenges in the operation and control of wind turbine systems are becoming increasingly important. These affect all parts of the system, and require an integrated approach to optimize safety, cost, integrity and survivability of the system, while retaining the desired performance quality. This book conveys up to date theoretical and practical techniques applicable to the control of wind turbine systems. Topics covered include wave loads on monopole-supported offshore wind turbines; numerical and experimental tools for small wind turbine load analysis; structural control concepts for load reduction of offshore wind turbines; towards farm-level health management of wind turbine systems; data-based approaches to the monitoring of wind turbines; fault diagnostics for electrically operated pitch systems in offshore wind turbines; an emulator prototype design for vibration control of magnetic bearings for wind turbine power generator shafts; condition monitoring and diagnostics of wind turbine power trains; and robust fuzzy fault tolerant control wind energy systems subject to actuator and sensor faults.
Inspec keywords: mechanical stability; offshore installations; mechanical variables control; condition monitoring; wind turbines; power generation control; fault diagnosis
Other keywords: electrically operated pitch systems; small wind turbine load analysis; monopile-supported offshore wind turbines; power train; fault diagnostics; condition monitoring; robust fuzzy fault tolerant control; load reduction; power generator shaft; emulator prototype design; actuator faults; health monitoring; structural control; vibration control; data-based approaches; farm-level health management; sensor faults; magnetic bearing; diagnostics; wave loads
Subjects: General and management topics; Buckling and instability (mechanical engineering); Power and plant engineering (mechanical engineering); Inspection and quality control; Control of electric power systems; Engineering mechanics; General electrical engineering topics; Control technology and theory (production); Wind power plants; Mechanical variables control
- Book DOI: 10.1049/PBPO117E
- Chapter DOI: 10.1049/PBPO117E
- ISBN: 9781785613944
- e-ISBN: 9781785613951
- Page count: 304
- Format: PDF
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Front Matter
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1 Introduction
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The wind turbine as a large-scale system is an aeroelastic mechanical system that converts kinetic wind energy into electrical power. Performance limitations of wind turbines in dealing with some problems such as vibration, corrosion and temperature changes, e.g. in the motors, sensors, blades and gearbox could affect the production capability and may cause remarkable downtime of the entire system. Therefore, considering the high cost of wind-turbine maintenance, increasing the reliability of wind-turbine operation becomes a key point for wind-farm operators. In other words, the maintenance strategy and reliability of the wind turbine are depending on each other, which leads us to the reliability-centred maintenance (RCM) and implementing an optimized maintenance program for wind turbines. Over the last few years, many researches were carried out by academicians or practitioners on implementation of RCM for wind turbines and the literature of this work is condensed by developing algorithms or methodologies in theory or practical aspects for dealing with structural load analysis or health monitoring of wind turbines for diagnostics or prognostics of various faults or possible failures in the system. This chapter gives an overview of the current book devoted to recent results in the field of structural control and fault detection of wind turbines. A review on the organization of the book and main contributions of each chapter is presented in detail.
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2 Wave loads on monopile-supported offshore wind turbines: current methods and future challenges
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This chapter provides an overview of the methods recently proposed for the prediction of the wave loads on fixed-bottom wind turbines, with particular emphasis on the role of nonlinear wave contributions in the assessment of the dynamic response of the support structure. After a brief presentation of the common numerical approaches to the simulation of OWTs, we review the fundamental equations governing the wave motions, briefly present a numerical method for the numerical solution of the fully nonlinear (FNL) problem and finally summarize the main commonly used analytical wave theories. The available hydrodynamic loading models are discussed, and an overview of the main literature findings and open issues in modelling the nonlinear resonant effects follows. Some key examples of the effects of highly nonlinear waves on the response of a 5-MW OWT are given and finally, a conclusion summarizes the current situation and future trends.
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3 Numerical and experimental tools for small wind turbine load analysis
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The authors present a decision path which allowed them to design successfully a small diffuser augmented wind turbine (DAWT). Multiple methods were applied to design and verify the construction, ranging from an application of simple analytical methods through complex numerical simulations, to finish with the experimental tests of models in different scales. An influence of the turbine duct (diffuser) made it impossible to use standard methods of turbine design and forced one to combine analytical methods with CFD predictions of the flow. A set of different numerical models was used, ranging from the 2D CFDADM up to 3D FRM, which took the most important elements of the final construction into account. Those simulations provided data on aerodynamic loads, further used to verify the design with analytical methods. Some trials of the load analysis employing the FSI were carried out. They proved to be useful for the design load analysis. However, significant requirements of computer resources for simulations of the complex turbine model as well as high deformations of polyamide blades limited the practical application of that method within the project so far. Nevertheless, continuous progress in the computer performance and numerical methods, combining the fluid flow and structural solvers, should provide tools for detailed design analysis in the near future. At the same time, the Fourier transform analysis can be performed on the rotor power signal to provide the fault tolerance and to increase the turbine load factor. Combined with the high frequency measurement of wind velocity, a link between dangerous loading due to environmental conditions and the resulting rotor power fluctuations can be established early enough. In this case, a potential fault could be avoided, thus keeping the turbine uptime to its maximum.
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4 Structural control concept for load reduction of offshore wind turbines
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This chapter introduces the structural control concept for load reduction of OWTs. Theories for both passive and active structural control are introduced. Particularly, a spar-type FOWT is used as the study case to demonstrate the load mitigation effectiveness of the proposed structural control methods. For the passive case, design optimization process is performed on a TMD installed in the spar platform, and the obtained numerical simulation results have indicated the both their effectiveness and limits regarding different system parameters and installations. Regarding the active case, a gain scheduling H2/H∞ active structural full-state feedback controller is designed for an HMD installed at the tower top of a spar-type FOWT, aiming at both reducing tower bottom load and mitigating the aerodynamic disturbance. The results demonstrate that more load reduction could be achieved at the expense of more energy consumption. At the same time, this will bring the risk of instability. Moreover, the full-state feedback controller is not very practical from a technical point of view due to the lack of sensors and measurement inaccuracy.
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5 Advanced control of wind turbine system
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Wind turbines are complex and nonlinear dynamic systems driven by stochastic wind disturbances together with gravitational, centrifugal and gyroscopic forces. The aerodynamic of wind turbines is nonlinear, unsteady and complex. The rotor of a wind turbine is subjected to complicated turbulent wind inflow and periodic gravity loading that drives fatigue loads. The rotation of rotor adds even more complexity to the dynamic model. Hence, wind turbine modeling is challenging and complex. The design of control algorithms for wind turbines must account for these complexities. The models used for control design purposes must contain enough degrees of freedom (DOFs) to capture the most important turbine dynamics without being too complex.
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6 Toward farm-level health management of wind turbine systems: status and scope for improvements
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An outline of health management for OWFs has been detailed in this chapter with description of various important elements. The need for such farm level management is explained and benefits are discussed. Key gaps to be filled in order to realize such a system are identified. The proposed health management system is mainly based on the existing knowledge of fleet-level management in the aerospace sector. Health management is much broader than CM; there are a number of aspects beyond the prognostics capabilities that are to be designed in order to arrive at a comprehensive maintenance management scheme. A comprehensive maintenance program that is sensitive to the health of the assets and adapts maintenance schedule accordingly, depending upon resource availability, logistics and inventory, is key to cost optimization while ensuring reliability and availability. The advances in CM and diagnostics in wind energy are in the right direction, and many of them are building blocks for health management. Offshore wind faces a number of unique challenges that can be satisfactorily addressed by following a suitable systematic approach. RCM implementation appears to be the most suitable as it encompasses other maintenance strategies and is suitable for farm-level deployment.
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7 Health monitoring of wind turbine: data-based approaches
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This chapter presented a robust data-driven fault detection scheme with the application to a wind turbine benchmark. The proposed scheme is based on robust residual generators constructed directly from available process measurements. For this purpose, a parity space is first identified from the measured data, and optimal parity vectors are selected from the parity space according to a given performance index and an optimization criterion to generate a robust residual vector. A proper evaluation approach as well as a suitable decision logic is further given to make a correct final decision. The effectiveness of the proposed scheme is finally demonstrated by the results obtained from the simulation of a wind turbine benchmark model.
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8 Fault diagnostics for electrically operated pitch systems in offshore wind turbines
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In this chapter, the main objective is to determine the feasibility and applicability of current signature analysis for pitch motors in typical operating profiles. In order to determine pitch system operation profiles, the 5 MW reference wind turbine is simulated in FAST analysis tools developed by National Renewable Energy Laboratory [10]. The pitch systems however pose significant challenge in terms of intermittent, start-stop operating profiles and low speed operations. The main contribution of this chapter is therefore twofold: (1) to develop a detailed physical modelling of various motor faults and study their effect on motor currents in pitch system operating profiles and (2) to determine the feasibility of current signature analysis in such operating profiles. The rest of this chapter is organised as follows: In Section 8.2, determination of the typical pitch profiles from FAST analysis tool is described. Further, a detailed modelling of induction motor with implementation of various fault conditions is described in Section 8.3. In Section 8.4, the motor current signature analysis (MCSA) is tested for pitch motor diagnostics in various wind turbine operating profiles. Finally, accuracy of the fault detection algorithms and steps towards implementation in wind farms are discussed.
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9 Magnetic bearing for wind turbine power generator shaft: an emulator prototype design for vibration control
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In this chapter, the relevance and potential of micro-sized wind turbines (μSWTs) have been discussed and the following facts have been stated In wide areas of developing countries with a poor grid power supply, μSWTs can be an important factor of social, economic and technological development. From an educational point of view, μSWTs can be a valuable source of motivation, helping to provide a practical presentation of basic and advanced mechatronical principles. Moreover, μSWTs can also be an excellent field for cooperative and project-based learning, allowing to define a wide variety of experimental projects with a direct real-life application. From a research perspective, μSWTs constitute a unique opportunity to perform full-scale physical experimentation on advanced research topics at a very low cost and with very limited resources. To provide a practical demonstration of the μSWTs potential in academic and research experimentation, a low-cost platform for active magnetic bearing vibration control has been presented.
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10 Condition monitoring and diagnostics of wind turbine power train
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The average size of offshore wind turbines is 4.2 MW. Higher costs and installation complexity compared to onshore are the two main drawbacks that can be mainly reduced by developing larger turbines. A special case is represented by the small wind turbine world market given by turbine size less than 100 kW. At the end of 2014, the cumulative total of less than 1 million small wind turbines was installed all over the world, for a total installed capacity of about 830 MW. In terms of installed capacity, China accounts for 41 per cent of the global capacity, USA for 30 per cent and United Kingdom for 15 per cent [3]. According to the 2016s GWEC report, the growth of the whole wind energy sector will continue. At the end of the year 2020, the expected installed power will reach 800 GW globally, with an average annual installed capacity growth rate of about 6 per cent. The increase of installed capacity is also achieved by building larger and larger wind turbines up to 10 MW, able to achieve the highest wind energy harvest. Large turbines have higher failure rates and require more maintenance than small turbines. The popularity of wind energy increased the interest of companies and research centres about the technical problems related to wind turbines.
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11 Robust fuzzy fault tolerant control wind energy system subject to actuator and sensor faults
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An augmented TS fuzzy plant model has been proposed to model the nonlinear plant subject to large parameter uncertainties, sensor faults and actuator faults. Based on this augmented TS fuzzy plant model, three different methods to design the fuzzy FTC have been proposed to tackle this nonlinear system. A design procedure of fuzzy fault tolerant controllers has been developed. The stability and robustness of the fuzzy FTC systems have been investigated based on the results of Chapters 11.2 and 11.3. An application example on stabilizing a WES with sensor faults, actuator faults and parameter uncertainties has been given to illustrate the design procedure and merits of the proposed fuzzy fault tolerant controller.
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Back Matter
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