A comprehensive review on brushless doubly-fed reluctance machine

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. The Brushless Doubly-Fed Reluctance Machine (BDFRM) has been widely investigated in numerous research studies since it is brushless and cageless and there is no winding on the rotor of this emerging machine. This feature leads to several advantages for this machine in comparison with its induction counterpart, i.e., Brushless Doubly-Fed Induction Machine (BDFIM). Less maintenance, less power losses, and also more reliability are the major advantages of BDFRM compared to BDFIM. The design complexity of its reluctance rotor, as well as flux patterns for indirect connection between the two windings mounted on the stator including power winding and control winding, have restricted the development of this machine technology. In the literature, there is not a comprehensive review of the research studies related to BDFRM. In this paper, the previous research studies are reviewed from different points of view, such as operation, design, control, transient model, dynamic model, power factor, Maximum Power Point Tracking (MPPT), and losses. It is revealed that the BDFRM is still evolving since the theoretical results have shown that this machine operates efficiently if it is well-designed

A comprehensive review on brushless doubly-fed reluctance machine

The Brushless Doubly-Fed Reluctance Machine (BDFRM) has been widely investigated in numerous research studies since it is brushless and cageless and there is no winding on the rotor of this emerging machine. This feature leads to several advantages for this machine in comparison with its induction counterpart, i.e., Brushless Doubly-Fed Induction Machine (BDFIM). Less maintenance, less power losses, and also more reliability are the major advantages of BDFRM compared to BDFIM. The design complexity of its reluctance rotor, as well as flux patterns for indirect connection between the two windings mounted on the stator including power winding and control winding, have restricted the development of this machine technology. In the literature, there is not a comprehensive review of the research studies related to BDFRM. In this paper, the previous research studies are reviewed from different points of view, such as operation, design, control, transient model, dynamic model, power factor, Maximum Power Point Tracking (MPPT), and losses. It is revealed that the BDFRM is still evolving since the theoretical results have shown that this machine operates efficiently if it is well-designed

Influence of pole-pair combinations on the characteristics of the brushless doubly fed induction generator

The brushless doubly fed induction generator (BDFIG) is an alternative to the doubly fed induction generator (DFIG), widely used in wind turbines which avoids the need for brush gear and slip rings. The choice of pole numbers for the two stator windings present in the BDFIG sets the operating speed, typically in the medium speed range to eliminate a gearbox stage. This paper focuses on how both the total number of poles and the assignment of poles between the windings affect machine performance. Analytical expressions have been developed for parameters including pull-out torque, magnetizing current and back-iron depth. The results show that the pole count can be increased without unduly compromising pull-out torque and that in cases where more than one combination of pole number is acceptable only the back iron depth is significantly affected. In addition an output factor has been introduced to enable a direct comparison to be made with conventional DFIGs. The torque density of a brushless DFIG is compromised to a degree relative to a comparable DFIG as a consequence of the presence of two magnetic fields and finite element analysis is needed to achieve an optimized design. Finally, predictions of the performance of multi-MW machines are made based on data from an existing 250 kW machine which show that suitable efficiencies can be obtained and excessive control winding excitation can be avoided

Small-Signal Modelling and Analysis of Doubly-Fed Induction Generators in Wind Power Applications

The worldwide demand for more diverse and greener energy supply has had a significant impact on the development of wind energy in the last decades. From 2 GW in 1990, the global installed capacity has now reached about 100 GW and is estimated to grow to 1000 GW by 2025. As wind power penetration increases, it is important to investigate its effect on the power system. Among the various technologies available for wind energy conversion, the doubly-fed induction generator (DFIG) is one of the preferred solutions because it offers the advantages of reduced mechanical stress and optimised power capture thanks to variable speed operation. This work presents the small-signal modelling and analysis of the DFIG for power system stability studies. This thesis starts by reviewing the mathematical models of wind turbines with DFIG convenient for power system studies. Different approaches proposed in the literature for the modelling of the turbine, drive-train, generator, rotor converter and external power system are discussed. It is shown that the flexibility of the drive train should be represented by a two-mass model in the presence of a gearbox. In the analysis part, the steady-state behaviour of the DFIG is examined. Comparison is made with the conventional synchronous generators (SG) and squirrel-cage induction generators to highlight the differences between the machines. The initialisation of the DFIG dynamic variables and other operating quantities is then discussed. Various methods are briefly reviewed and a step-by-step procedure is suggested to avoid the iterative computations in initial condition mentioned in the literature. The dynamical behaviour of the DFIG is studied with eigenvalue analysis. Modal analysis is performed for both open-loop and closed-loop situations. The effect of parameters and operating point variations on small signal stability is observed. For the open-loop DFIG, conditions on machine parameters are obtained to ensure stability of the system. For the closed-loop DFIG, it is shown that the generator electrical transients may be neglected once the converter controls are properly tuned. A tuning procedure is proposed and conditions on proportional gains are obtained for stable electrical dynamics. Finally, small-signal analysis of a multi-machine system with both SG and DFIG is performed. It is shown that there is no common mode to the two types of generators. The result confirms that the DFIG does not introduce negative damping to the system, however it is also shown that the overall effect of the DFIG on the power system stability depends on several structural factors and a general statement as to whether it improves or detriorates the oscillatory stability of a system can not be made

Effective algorithms for real-time wind turbine condition monitoring and fault-detection

Reliable condition monitoring (CM) can be an effective means to significantly reduce wind turbine (WT) downtime, operations and maintenance costs and plan preventative maintenance in advance. The WT generator voltage and current output, if sampled at a sufficiently high rate (kHz range), can provide a rich source of data for CM. However, the electrical output of the WT generator is frequently shown to be complex and noisy in nature due to the varying and turbulent nature of the wind. Thus, a fully satisfactory technique that is capable to provide accurate interpretation of the WT electrical output has not been achieved to date. The objective of the research described in this thesis is to develop reliable WT CM using advanced signal processing techniques so that fast analysis of non-stationary current measurements with high diagnostic accuracy is achieved. The diagnostic accuracy and reliability of the proposed techniques have been evaluated using data from a laboratory test rig where experiments are performed under two levels of rotor electrical asymmetry faults. The experimental test rig was run under fixed and variable speed driving conditions to investigate the kind of results expected under such conditions. An effective extended Kalman filter (EKF) based method is proposed to iteratively track the characteristic fault frequencies in WT CM signals as the WT speed varies. The EKF performance was compared with some of the leading WT CM techniques to establish its pros and cons. The reported experimental findings demonstrate clear and significant gains in both the computational efficiency and the diagnostic accuracy using the proposed technique. In addition, a novel frequency tracking technique is proposed in this thesis to analyse the non-stationary current signals by improving the capability of a continuous wavelet transform (CWT). Simulations and experiments have been performed to verify the proposed method for detecting early abnormalities in WT generators. The improved CWT is finally applied for developing a new real-time CM technique dedicated to detect early abnormalities in a commercial WT. The results presented highlight the advantages of the improved CWT over the conventional CWT to identify frequency components of interest and cope with the non-linear and non-stationary fault features in the current signal, and go on to indicate its potential and suitability for WT CM.</div

Studies in Electrical Machines & Wind Turbines associated with developing Reliable Power Generation

The publications listed in date order in this document are offered for the Degree of Doctor of Science in Durham University and have been selected from the author’s full publication list. The papers in this thesis constitute a continuum of original work in fundamental and applied electrical science, spanning 30 years, deployed on real industrial problems, making a significant contribution to conventional and renewable energy power generation. This is the basis of a claim of high distinction, constituting an original and substantial contribution to engineering science

Wind Turbine Generator Condition Monitoring via the Generator Control Loop

This thesis focuses on the development of condition monitoring techniques for application in wind turbines, particularly for offshore wind turbine driven doubly fed induction generators. The work describes the significant development of a physical condition monitoring Test Rig and its MATLAB Simulink model to represent modern variable speed wind turbine and the innovation and application of the rotor side control signals for the generator fault detection. Work has been carried out to develop a physical condition monitoring Test Rig from open loop control, with a wound rotor induction generator, into closed loop control with a doubly fed induction generator. This included designing and building the rotor side converter, installing the back-to-back converter and other new instrumentation. Moreover, the MATLAB Simulink model of the Test Rig has been developed to represent the closed loop control, with more detailed information on the Rig components and instrumentation and has been validated against the physical system in the time and frequency domains. A fault detection technique has been proposed by the author based on frequency analysis of the rotor-side control signals, namely; d-rotor current error, q-rotor current error and q-rotor current, for wind turbine generator fault detection. This technique has been investigated for rotor electrical asymmetry on the physical Test Rig and its MATLAB Simulink model at different fixed and variable speed conditions. The sensitivity of the each proposed signal has been studied under different operating conditions. Measured and simulated results are presented, a comparison with the results from using stator current and total power has been addressed and the improvement in condition monitoring detection performance has been demonstrated in comparison with previous methods, looking at current, power and vibration analysis

Advanced Algorithms for Automatic Wind Turbine Condition Monitoring

Reliable and efficient condition monitoring (CM) techniques play a crucial role in minimising wind turbine (WT) operations and maintenance (O&M) costs for a competitive development of wind energy, especially offshore. Although all new turbines are now fitted with some form of condition monitoring system (CMS), very few operators make use of the available monitoring information for maintenance purposes because of the volume and the complexity of the data. This Thesis is concerned with the development of advanced automatic fault detection techniques so that high on-line diagnostic accuracy for important WT drive train mechanical and electrical CM signals is achieved. Experimental work on small scale WT test rigs is described. Seeded fault tests were performed to investigate gear tooth damage, rotor electrical asymmetry and generator bearing failures. Test rig data were processed by using commercial WT CMSs. Based on the experimental evidence, three algorithms were proposed to aid in the automatic damage detection and diagnosis during WT non-stationary load and speed operating conditions. Uncertainty involved in analysing CM signals with field fitted equipment was reduced, and enhanced detection sensitivity was achieved, by identifying and collating characteristic fault frequencies in CM signals which could be tracked as the WT speed varies. The performance of the gearbox algorithm was validated against datasets of a full-size WT gearbox, that had sustained gear damage, from the National Renewable Energy Laboratory (NREL) WT Gearbox Condition Monitoring Round Robin project. The fault detection sensitivity of the proposed algorithms was assessed and quantified leading to conclusions about their applicability to operating WTs

The application of advanced signal processing techniques to the condition monitoring of electrical machine drive systems

Includes bibliographical references (leaves 128-129).The thesis examines the use of two time-frequency domain signal processing tools in its application to condition monitoring of electrical machine drive systems. The mathematical and signal processing tools which are explored are wavelet analysis and a non-stationary adaptive signal processing algorithm. Four specific applications are identified for the research. These applications were specifically chosen to encapsulate important issues in condition monitoring of variable speed drive systems. The main aim of the project is to highlight the need for fault detection during machine transients and to illustrate the effectiveness of incorporating and adapting these new class of algorithms to detect faults in electrical machine drive systems during non-stationary conditions

Emerging Multiport Electrical Machines and Systems: Past Developments, Current Challenges, and Future Prospects

Distinct from the conventional machines with only one electrical and one mechanical port, electrical machines featuring multiple electrical/mechanical ports (the so-called multiport electrical machines) provide a compact, flexible, and highly efficient manner to convert and/or transfer energies among different ports. This paper attempts to make a comprehensive overview of the existing multiport topologies, from fundamental characteristics to advanced modeling, analysis, and control, with particular emphasis on the extensively investigated brushless doubly fed machines for highly reliable wind turbines and power split devices for hybrid electric vehicles. A qualitative review approach is mainly adopted, but strong efforts are also made to quantitatively highlight the electromagnetic and control performance. Research challenges are identified, and future trends are discussed