Indirect load measurements for large floating horizontal-axis tidal current turbines
Introduction
Tidal current energy is an attractive renewable energy resource because of its high predictability and stability. Both the size and the generation power of tidal current turbines (TCTs) have been continuously increasing in recent years. The capacity of the world's largest TCT has reached 2 MW (Zhou et al., 2017). However, the further development of TCTs is facing some problems associated with their high energy cost and severe fatigue load.
In the current process of TCT design, the operational load performance of TCTs is investigated mainly based on theoretical analysis using blade element momentum (BEM) theory and CFD numerical simulation (ed-Dı̂n Fertahi et al., 2018, Li et al., 2016). However, the CFD method strongly relies on the computing ability and costs a substantial amount of time. Thus, it is difficult to calculate the load performance of turbines during the control process. In the BEM method, many parameters of blade hydrofoils are transferred from wind turbines, but the two systems have quite different Reynolds numbers, stall characteristics and potential for cavitation (Bahaj et al., 2007, Winter, 2011). In general, the load results predicted by the current theoretical analysis methods are not accurate or reliable enough for the precise designs of TCTs and their support structures. Hence, due to the complex marine conditions and the lack of accurate load estimation of operating TCTs, high reliability indices are often adopted in the design process with additional safety margins that increase the energy cost. This cost disadvantage has seriously impeded the industrialization process of the TCTs.
Additionally, another problem of software simulations and theoretical calculations is that they cannot provide real-time load data of an operating TCT for the load reduction control. With the increase in TCT size, the fatigue load arising from current shear becomes more severe (Li et al., 2019). The absence of effective load reduction control, such as individual pitch control (IPC), reduces the lifetime of TCTs and has led to some unexpected failures (Bahaj, 2011, Zhou et al., 2017). In addition to the pitch control actuators, a reliable real-time fatigue load monitor method is required for IPC. It is therefore important to establish an effective method to measure or monitor the operating load of TCTs.
Thus, developing a load measurement system for TCTs is an efficient approach to meet the requirements of the cost reduction design and lifetime extension. To measure or monitor the dynamic load of wind turbines, strain gauge sensors (Liu et al., 2015, Liu et al., 2016) and fiber Bragg grating sensors (Schroeder et al., 2006) have been proposed and demonstrated for wind turbine blade load measurement. However, because the TCTs operate in deep water, probably in a high-pressure environment, the seal problems and signal transmission problems of these direct load measurement methods affect their longtime and efficient operation and restrict their applications for TCTs. Moreover, some indirect methods have also been studied. Platform pitching motion (Wakui et al., 2017) and tower vibrations (Lio et al., 2018) were used as feedback for power control and load reduction. The effects of platform motion on turbine performance were also studied (Wen et al., 2018, Zhang et al., 2015). However, these studies cannot provide direct reference or feedback for turbine design. The 6-degree-of-freedom (DOF) motions of the Hywind Demo floating wind turbine were measured in a related study that focused on the wave loads and the comparative analysis of measurement and simulation (Lin et al., 2018, Skaare et al., 2015). However, the numerical relationship between the response of platform motions and the turbine loads remains to be studied and experimentally validated.
Although the load measurements were studied for wind turbines, little work has been devoted to the load measurements for TCTs. Until recently, load measuring for TCTs had been a largely under explored domain, and existing methods in wind energy research areas could not provide available direct reference for the load measurement method for TCTs. Thus, this paper presents a novel load measurement method for the large floating TCTs regarding the whole mooring system as a part of a load measurement sensor.
Floating platforms provide convenient maintenance for TCTs and thus are widely used to support TCTs and other equipment (Gu et al., 2018, Sheng et al., 2016, Xu et al., 2016). Compared with the towers of wind turbines, the mooring systems have smaller stiffness so that the motions of the platforms can be easily observed and measured. Hence, avoiding the complicated and difficult direct load measurement, the proposed method in this study is to investigate the loads of TCTs by measuring both the static and the dynamic responses of floating platform motion. It is the focus of this research to obtain the numerical relationship between the turbine loads and the mooring system motion responses as shown in Fig. 1. The main contributions of this method is presenting a new solution for the load measurements for TCTs to support the cost reduction design for both the TCTs and the floating platforms and to provide real-time load feedback for load reduction control.
In this study, a mooring system model was firstly established by analyzing all the loads acting on the platform to obtain the numerical relationship between the turbine loads and the mooring system motion responses. Then, a floating platform motion measurement method based on Euler's angles was proposed and introduced. To validate the feasibility of proposed method, a measurement experiment for a 300-kW floating TCT was subsequently carried out in real sea state. Good agreement was obtained between the measured results and the theoretically calculated results based on BEM theory.
Section snippets
Mooring system model
The mooring system model is crucial for the indirect load measurement. The floating mooring system is subjected to turbine loads, waves, tidal current and wind. Each of them needs to be analyzed to determine the accurate relationship between turbine loads and platform responses. Compared with other factors, the wind force is negligible. Fig. 2 shows the tidal current energy test field in Zhoushan consisting of three floating platforms for various sizes of TCTs. Although the sea surface is
Simulations
To obtain the numerical relationship between the TCT loads and platform responses, a theoretical model based on the analysis in Section.2 for this mooring system was established in MATLAB/Simulink. Additionally, to provide further evidence of the theoretical model results, a simulation for this mooring system was also conducted in ANSYS-Workbench, as shown in Fig. 13.
The mechanical structure of the platform was imported to the ANSYS-Workbench Hydrodynamic Response components. The mass
Experiments
To validate the feasibility of the proposed measurement method and the designed measurement system, a measurement experiment for a 300-kW twin-blade horizontal-axis TCT was carried out in a real sea state. This TCT with a 16 m rotor diameter was installed on a floating platform as shown in Fig. 17, with the turbine loads acting on the floating platform. The platform responses, including the tilt angles and accelerations, were monitored by the designed measurement system during the power
Conclusion
Reliable load measurements are crucial for the optimization design and load control of TCTs. In this study, a novel indirect load measurement method is proposed for large TCTs on floating platforms. A measurement system is designed, and its operating principle is introduced in detail based on the mooring system model. To validate the feasibility and measurement accuracy of the designed measurement system, an experimental measurement test for a 300-kW TCT was carried out in a real sea state.
Author contributions section
Yangjian Li; Conceptualization, Methodology, Writing - Original Draft, Software, Validation and Investigation. Wei Li: Conceptualization, Resources, Funding acquisition. Hongwei Liu: Resources, Supervision. Yonggang Lin: Resources, Funding acquisition, Project administration. Yajing Gu: Funding acquisition. Bingling Xie: Experimental assistant.
Declaration of competing interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgements
This work was supported by the Science Fund for Creative Research Groups of the National Natural Science Foundation of China (grant No. 51821093), the National Natural Science Foundation of China (grant No. 51775487, No. 51575477 and No. 51905472), the National Key Research and Development Program (grant No. 2018YFB1501900), the Special Funds of State Oceanic Renewable Energy (grant No. GHME2017SF02), the Fundamental Public Welfare project of Zhejiang Province (grant No. LGF19E050004) and the
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