Torque Control of a Laboratory Scale Variable Speed Hydrokinetic Tidal Turbine: CFD Simulation and Validation

Author(s):  
Arturo Ortega ◽  
Anup Nambiar ◽  
David Ingram ◽  
Danny Sale

Abstract Hydrokinetic tidal turbines are a promising alternative for the generation of clean electrical energy. They are still far behind, with respect to their technological development, in comparison to offshore wind turbines, which are currently in the stage of commercial energy production. Thus, more studies and analyses of the behaviour of tidal devices and their interaction with the surrounding ocean space are required. How this interaction is interrelated to the power production system is also necessary to be further examined. In this paper, the development of a whole system, fully-coupled model of a laboratory-scale hydrokinetic tidal turbine, along with its interactions with the ocean environment and its electrical control system is described. The model was developed in fastFlume (SOWFA, NREL) coupled with an external torque control system. The control system is developed from the optimal torque speed curve based Maximum Power Point Tracking (MPPT) algorithm. The optimal torque speed curve of the turbine used in the model was obtained from experimental work in a test tank. The hydrokinetic tidal turbine and the control system models were implemented independently. They were coupled in order to reach an energy balance between the surrounding flow, the tidal turbine, and the control system. Three flow stream velocities were imposed in the inlet of the model domain, starting the rotor from zero rotational speed. After the optimal rotational speed is attained, the electrical power generated and the loads experienced by the turbine rotor were studied. In the simulations, the tidal device is controlled to keep the optimal power production for any flow stream velocity. The results of the modelling work were compared with experimental measurements taken from 1:15th scaled testing of a fully-instrumented and controllable tidal device at the Flowave Ocean Energy Research Facility, The University of Edinburgh, a combined wave and current test facility. The results show time series of turbine and generator variables like mechanical and electrical torque and power, as well as thrust and the optimal rotational speed for each of the tested cases. The validation shows good agreement between the numerical and experimental results which encourages futures studies using the coupled model, including the turbine working in more complex flow conditions and controlled by more complex control schemes.

Energies ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 2154 ◽  
Author(s):  
Dazhi Wang ◽  
Tianqing Yuan ◽  
Xingyu Wang ◽  
Xinghua Wang ◽  
Yongliang Ni

In order to improve the performance of the servo control system driven by a permanent magnet synchronous motor (PMSM) under novel direct torque control (NDTC), which, utilizing composite active vectors, fixed sector division criterion, is proposed in this paper. The precondition of the accurate compensations of torque and flux errors is that the sector where the stator flux linkage is located can be determined accurately. Consequently, the adaptive sector division criterion is adopted in NDTC. However, the computation burden is inevitably increased with the using of the adaptive part. On the other hand, the main errors can be compensated through SV-DTC (DTC-utilizing single active vector), while another active vector applied in NDTC can only supply the auxiliary error compensation. The relationships of the two active vectors’ characteristics in NDTC are analyzed in this paper based on the active factor. Furthermore, the fixed sector division criterion is proposed for NDTC (FS-NDTC), which can classify the complexity of the control system. Additionally, the switching table for the selections of the two active vectors is designed. The effectiveness of the proposed FS-NDTC is verified through the experimental results on a 100-W PMSM drive system.


2021 ◽  
Vol 45 (7) ◽  
pp. 605-613
Author(s):  
Jimin Park ◽  
Youngjin Kim ◽  
Hyeongrae Kim ◽  
Juyeon Kim ◽  
Dongho Oh

Author(s):  
Suranga C. H. Geekiyanage ◽  
Dan Sui ◽  
Bernt S. Aadnoy

Drilling industry operations heavily depend on digital information. Data analysis is a process of acquiring, transforming, interpreting, modelling, displaying and storing data with an aim of extracting useful information, so that the decision-making, actions executing, events detecting and incident managing of a system can be handled in an efficient and certain manner. This paper aims to provide an approach to understand, cleanse, improve and interpret the post-well or realtime data to preserve or enhance data features, like accuracy, consistency, reliability and validity. Data quality management is a process with three major phases. Phase I is an evaluation of pre-data quality to identify data issues such as missing or incomplete data, non-standard or invalid data and redundant data etc. Phase II is an implementation of different data quality managing practices such as filtering, data assimilation, and data reconciliation to improve data accuracy and discover useful information. The third and final phase is a post-data quality evaluation, which is conducted to assure data quality and enhance the system performance. In this study, a laboratory-scale drilling rig with a control system capable of drilling is utilized for data acquisition and quality improvement. Safe and efficient performance of such control system heavily relies on quality of the data obtained while drilling and its sufficient availability. Pump pressure, top-drive rotational speed, weight on bit, drill string torque and bit depth are available measurements. The data analysis is challenged by issues such as corruption of data due to noises, time delays, missing or incomplete data and external disturbances. In order to solve such issues, different data quality improvement practices are applied for the testing. These techniques help the intelligent system to achieve better decision-making and quicker fault detection. The study from the laboratory-scale drilling rig clearly demonstrates the need for a proper data quality management process and clear understanding of signal processing methods to carry out an intelligent digitalization in oil and gas industry.


Author(s):  
Xiaoxin Hou ◽  
Mingqian Wang ◽  
Guodong You ◽  
Jinming Pan ◽  
Xiating Xu ◽  
...  

The traditional direct torque control system of permanent magnet synchronous motor has many problems, such as large torque ripple and variable switching frequency. In order to improve the dynamic and static performance of the control system, a new torque control idea and speed sensorless control scheme are proposed in this paper. First, by deriving the equation of torque change rate, an improved torque controller is designed to replace the torque hysteresis controller of the traditional direct torque control. The improved direct torque control strategy can significantly reduce the torque ripple and keep the switching frequency constant. Then, based on the improved direct torque control and considering the sensitivity of the stator resistance to temperature change, a speed estimator based on the model reference adaptive method is designed. This method realizes the stator resistance on-line identification and further improves the control precision of the system. The performance of the traditional direct torque control and the improved direct torque control are compared by simulation and experiment under different operating conditions. The simulation and experimental results are presented to support the validity and effectiveness of the proposed method.


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