An approach to the characterisation of the performance of a tidal stream turbine

In order to better manage and maintain deployed Tidal Stream Turbine (TST) devices their response to complicated and severe loading mechanisms must be established. To aid this process the research presented details a methodology for mapping TST operational data, taken under a variety of operating conditions, to a set of model parameters. The parameter sets were developed based on a TST rotor torque model which, as well as providing means of characterising turbine behaviour, can be used to create TST simulations with minimal computation expense. The use of the model in facilitating parameter surface mapping is demonstrated via its application to a set of rotor torque measurements made of a 1/20th scale TST during flume testing. This model is then deployed to recreate the known rotor behaviour which is compared with the original flume based measurements. This is a flexible tool that can be applied to investigate turbine performance under conditions that cannot be readily replicated using tank-based experiments. Furthermore, Computational Fluid Dynamics simulations of such conditions could be time consuming and computationally expensive. To this end, the use of the model in creating drivetrain test bed based simulations is demonstrated. The model, which can be calculated in real-time, is used to develop representative turbine simulations at high turbulence intensity levels which were not achievable during flume experimentation. The intention is to provide a test-bed for future turbine performance monitoring under more realistic, site specific conditions. The work will also support the deployment of performance surfaces in real-life turbine applications

The specification and testing of a horizontal axis tidal turbine rotor monitoring approach.

The sustainable deployment of Horizontal Axis Tidal Turbines will require effective management and maintenance functions. In part, these can be supported by the engineering of suitable condition monitoring systems. The development of such a system is inevitably challenging, particularly given the present limited level of operational data associated with installed turbines during fault onset. To mitigate this limitation,a computational fluid dynamics model is used to simulate the operational response of a turbine under a known set of fault conditions. Turbine rotor imbalance faults were simulated by the introduction of increasing levels of pitch angle offset for a single turbine blade. The effects of these fault cases upon cyclic variations in the torque developed by the turbine rotor were then used to aid creation of a condition monitoring approach. A parametric tidal turbine rotor model was developed based on the outputs of the computational fluid dynamics models. The model was used to facilitate testing of the condition monitoring approach under a variety of more realistic conditions. The condition monitoring approach showed good performance in fault detection and diagnosis for simulations relating to turbulence intensities of up to 2 %. Finally,the condition monitoring approach was applied to simulations of 10 % turbulence intensity. Under the 10 % turbulence intensity case the rotor monitoring approach was successfully demonstrated in its use for fault detection. The paper closes with discussion of the effectiveness of using computational fluid dynamics simulations extended by parametric models to develop condition monitoring systems for horizontal axis tidal turbine applications

Condition monitoring and fault diagnosis of tidal stream turbines subjected to rotor imbalance faults

The main focus of the work presented within this thesis was the testing and development of condition monitoring procedures for detection and diagnosis of HATT rotor imbalance faults. The condition monitoring processes were developed via Matlab with the goal of exploiting generator measurements for rotor fault monitoring. Suitable methods of turbine simulation and testing were developed in order to test the proposed CM processes. The algorithms were applied to both simulation based and experimental data sets which related to both steady-state and non-steady-state turbine operation. The work showed that development of condition monitoring practices based on analysis of data sets generated via CFD modelling was feasible. This could serve as a useful process for turbine developers. The work specifically showed that consideration of the torsional spectra observed in CFD datasets was useful in developing a, ‘rotor imbalance criteria’ which was sensitive to rotor imbalance conditions. Furthermore, based on the CFD datasets acquired it was possible to develop a parametric rotor model which was used to develop rotor torque time series under more general flow conditions. To further test condition monitoring processes and to develop the parametric rotor model developed based on CFD data a scale model turbine was developed. All aspects of data capture and test rig control was developed by the researcher. The test rig utilised data capture within the turbine nose cone which was synchronised with the global data capture clock source. Within the nose cone thrust and moment about one of the turbine blades was measured as well as acceleration at the turbine nose cone. The results of the flume testing showed that rotor imbalance criteria was suitable for rotor imbalance faults as applied to 4 generator quadrature axis current measurements as an analogue for drive train torque measurements. It was further found that feature fusion of the rotor imbalance criterion calculated with power coefficient monitoring was successful for imbalance fault diagnosis. The final part of the work presented was to develop drive train simulation processes which could be calculated in real-time and could be utilised to generate representative datasets under non-steady-state conditions. The parametric rotor model was developed, based on the data captured during flume testing, to allow for non-steady state operation. A number of simulations were then undertaken with various rotor faults simulated. The condition monitoring processes were then applied to the data sets generated. Condition monitoring based on operational surfaces was successful and normalised calculation of the surfaces was outlined. The rotor imbalance criterion was found to be less sensitive to the fault cases under non-steady state condition but could well be suitable for imbalance fault detection rather than diagnosis

An initial characterisation of a tidal stream turbine on a drive train test rig

The potential of tidal stream turbines simulations on steady-state conditions by the use of a drive train test rig is considered. An initial assessment of two case scenarios is developed to furtherly assess the availability of replicating a theoretical model to the experimental model. It has been demonstrated that a drive train test rig is able to represent power curves of a 0.5 m diameter turbine with velocities from 0.5 to 1.8 ms-1 given its torque value and its rotational frequency. IndraWorks Engineering is being used to obtain the rotor and generator signals and review the losses through a horizontal axis tidal turbine drivetrain. This provides a first order approximation for the use of the test rig with non-steady state conditions and develop condition monitoring techniques

Detection of tidal stream turbine rotor imbalance faults for turbulent flow conditions and optimal tip speed ratio control

The paper presents a methodology for the Condition Monitoring (CM) of tidal stream turbines. The process is based on the use of, so-called, Transient Monitoring Surfaces (TMS)developed by the authors. In this paper the TMSs have been used to detect rotor imbalance faults. To test the use of TMS for CM drive train simulations were undertaken. The simulations undertaken relate to a lab-scale turbine subjected to turbulent flows and an optimal � control scheme based on Vector Oriented Control (VOC). The simulations are parametrised based on experimental data relating to testing undertaken with varying degrees of rotor imbalance. Use of the TMS gave promising results for the detection of various rotor imbalance conditions. Differing levels of discrepancies between the ’normal operating’or ’baseline’ surface were found for differing fault severities. It was also found that a minimum amount of data is required to gain convergence in the surface structure - in this case data sets relating to 5 rotations of the turbine were required to make a suitable fault detection

The specification and testing of a Horizontal Axis Tidal Turbine Rotor Monitoring approach

The sustainable deployment of Horizontal Axis Tidal Turbines will require effective management and maintenance functions. In part, these can be supported by the engineering of suitable condition monitoring systems. The development of such a system is inevitably challenging, particularly given the present limited level of operational data associated with installed turbines during fault onset. To mitigate this limitation, a computational fluid dynamics model is used to simulate the operational response of a turbine under a known set of fault conditions. Turbine rotor imbalance faults were simulated by the introduction of increasing levels of pitch angle offset for a single turbine blade. The effects of these fault cases upon cyclic variations in the torque developed by the turbine rotor were then used to aid creation of a condition monitoring approach. A parametric tidal turbine rotor model was developed based on the outputs of the computational fluid dynamics models. The model was used to facilitate testing of the condition monitoring approach under a variety of more realistic conditions. The condition monitoring approach showed good performance in fault detection and diagnosis for simulations relating to turbulence intensities of up to 2 %. Finally, the condition monitoring approach was applied to simulations of 10 % turbulence intensity. Under the 10 % turbulence intensity case the rotor monitoring approach was successfully demonstrated in its use for fault detection. The paper closes with discussion of the effectiveness of using computational fluid dynamics simulations extended by parametric models to develop condition monitoring systems for horizontal axis tidal turbine applications

An initial characterisation of a tidal stream turbine on a drive train test rig

The potential of tidal stream turbines simulations on steady-state conditions by the use of a drive train test rig is considered. An initial assessment of two case scenarios is developed to furtherly assess the availability of replicating a theoretical model to the experimental model. It has been demonstrated that a drive train test rig is able to represent power curves of a 0.5 m diameter turbine with velocities from 0.5 to 1.8 ms-1 given its torque value and its rotational frequency. IndraWorks Engineering is being used to obtain the rotor and generator signals and review the losses through a horizontal axis tidal turbine drivetrain. This provides a first order approximation for the use of the test rig with non-steady state conditions and develop condition monitoring techniques