scholarly journals Assessment of Wind Turbine Aero-Hydro-Servo-Elastic Modelling on the Effects of Mooring Line Tension via Deep Learning

Energies ◽  
2020 ◽  
Vol 13 (9) ◽  
pp. 2264 ◽  
Author(s):  
Zi Lin ◽  
Xiaolei Liu
Keyword(s):  
Deep Learning ◽  
Wind Turbines ◽  
Environmental Conditions ◽  
Line Tension ◽  
Offshore Wind ◽  
Mooring Line ◽  
Offshore Wind Turbines ◽  
Wind Speeds ◽  
Study Results ◽  
Floating Offshore Wind Turbines

As offshore wind turbines are moving to deeper water depths, mooring systems are becoming more and more significant for floating offshore wind turbines (FOWTs). Mooring line failures could affect power generations of FOWTs and ultimately incur risk to nearby structures. Among different failure mechanics, an excessive mooring line tension is one of the most essential factors contributing to mooring failure. Even advanced sensing offers an effective way of failure detections, but it is still difficult to comprehend why failures happened. Unlike traditional parametric studies that are computational and time-intensive, this paper applies deep learning to investigate the major driven force on the mooring line tension. A number of environmental conditions are considered, ranging from cut in to cut out wind speeds. Before formatting input data into the deep learning model, a FOWT model of dynamics was simulated under pre-defined environmental conditions. Both taut and slack mooring configurations were considered in the current study. Results showed that the most loaded mooring line tension was mainly determined by the surge motion, regardless of mooring line configurations, while the blade and the tower elasticity were less significant in predicting mooring line tension.

Wind/Wave Misalignment Effects on Mooring Line Tensions for a Spar Buoy Wind Turbine

2018 ◽  
Author(s):  
Luigia Riefolo ◽  
Fernando del Jesus ◽  
Raúl Guanche García ◽  
Giuseppe Roberto Tomasicchio ◽  
Daniela Pantusa
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Wave ◽  
Offshore Wind ◽  
Mooring Line ◽  
Ultimate Limit State ◽  
International Electrotechnical Commission ◽  
Wave Loads ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines

The design methodology for mooring systems for a spar buoy wind turbine considers the influence of extreme events and wind/wave misalignments occurring in its lifetime. Therefore, the variety of wind and wave directions affects over the seakeeping and as a result the evaluation of the maxima loads acting on the spar-buoy wind turbine. In the present paper, the importance of wind/wave misalignments on the dynamic response of spar-type floating wind turbine [1] is investigated. Based on standards, International Electrotechnical Commission IEC and Det Norske Veritas DNV the design of position moorings should be carried out under extreme wind/wave loads, taking into account their misalignments with respect to the structure. In particular, DNV standard, in ‘Position mooring’ recommendations, specifies in the load cases definition, if site specific data is not available, to consider non-collinear environment to have wave towards the unit’s bow (0°) and wind 30° relative to the waves. In IEC standards, the misalignment of the wind and wave directions shall be considered to design offshore wind turbines and calculate the loads acting on the support structure. Ultimate Limit State (ULS) analyses of the OC3-Hywind spar buoy wind turbine are conducted through FAST code, a certified nonlinear aero-hydro-servo-elastic simulation tool by the National Renewable Energy Laboratory’s (NREL’s). This software was developed for use in the International Energy Agency (IEA) Offshore Code Comparison Collaborative (OC3) project, and supports NREL’s offshore 5-MW baseline turbine. In order to assess the effects of misaligned wind and wave, different wind directions are chosen, maintaining the wave loads perpendicular to the structure. Stochastic, full-fields, turbulence simulator Turbsim is used to simulate the 1-h turbulent wind field. The scope of the work is to investigate the effects of wind/wave misalignments on the station-keeping system of spar buoy wind turbine. Results are presented in terms of global maxima determined through mean up-crossing with moving average, which, then, are modelled by a Weibull distribution. Finally, extreme values are estimated depending on global maxima and fitted on Gumbel distribution. The Most Probable Maximum value of mooring line tensions is found to be influenced by the wind/wave misalignments. The present paper is organized as follows. Section ‘Introduction’, based on a literature study, gives useful information on the previous studies conducted on the wind/wave misalignments effects of floating offshore wind turbines. Section ‘Methodology’ describes the applied methodology and presents the spar buoy wind turbine, the used numerical model and the selected environmental conditions. Results and the corresponding discussion are given in Section ‘Results and discussion’ for each load case corresponding to the codirectional and misaligned wind and wave loads. Results are presented and discussed in time and frequency domains. Finally, in Section ‘Conclusion’ some conclusions are drawn.

scholarly journals Deep learning and fuzzy logic to implement a hybrid wind turbine pitch control

2021 ◽  
Author(s):  
J. Enrique Sierra-Garcia ◽  
Matilde Santos
Keyword(s):  
Fuzzy Logic ◽  
Deep Learning ◽  
Wind Turbines ◽  
Fuzzy Controller ◽  
Complex Dynamics ◽  
Hybrid Control ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Wind Speeds ◽  
Floating Offshore Wind Turbines

AbstractThis work focuses on the control of the pitch angle of wind turbines. This is not an easy task due to the nonlinearity, the complex dynamics, and the coupling between the variables of these renewable energy systems. This control is even harder for floating offshore wind turbines, as they are subjected to extreme weather conditions and the disturbances of the waves. To solve it, we propose a hybrid system that combines fuzzy logic and deep learning. Deep learning techniques are used to estimate the current wind and to forecast the future wind. Estimation and forecasting are combined to obtain the effective wind which feeds the fuzzy controller. Simulation results show how including the effective wind improves the performance of the intelligent controller for different disturbances. For low and medium wind speeds, an improvement of 21% is obtained respect to the PID controller, and 7% respect to the standard fuzzy controller. In addition, an intensive analysis has been carried out on the influence of the deep learning configuration parameters in the training of the hybrid control system. It is shown how increasing the number of hidden units improves the training. However, increasing the number of cells while keeping the total number of hidden units decelerates the training.

Jump bifurcation phenomenon during varying wind speeds in floating offshore wind turbines

2022 ◽  
pp. 1-15
Author(s):  
Alwin Jose ◽  
Jeffrey M. Falzarano
Keyword(s):  
Transition Region ◽  
Wind Turbines ◽  
Large Amplitude ◽  
Offshore Wind ◽  
Nonlinear Phenomenon ◽  
Motion Response ◽  
Offshore Wind Turbines ◽  
Future Design ◽  
Wind Speeds ◽  
Floating Offshore Wind Turbines

Abstract Floating Offshore Wind Turbines (FOWTs) are susceptible to an instability which has come to be called negative damping. Conventional land based wind turbine controllers when used with FOWTs may cause large amplitude platform pitch oscillations. Most controllers have since been improved to reduce motions due to this phenomenon. In this paper, the motions induced using one of the original controllers is studied. The current study is performed using the coupled time domain program FAST-SIMDYN that was developed in Marine Dynamics Laboratory (MDL) at Texas A&M University. It is capable of studying large amplitude motions of Floating Offshore Wind Turbines. FOWTs use various controller algorithms of operation based on the available wind speed depending on various power output objectives i.e., to either maximize or level out power absorption. It is observed that the transition region for controllers is often chaotic. So most studies focus on operations away from the transition region below and above the transition wind speeds. Here we study the transition region using the theoretical insight of non-linear motion response of structures. This study reveals the presence of a very interesting and potentially hazardous nonlinear phenomenon, bifurcation. This finding could help explain the chaotic motion response that is observed in the transition region of controllers. Understanding the nature and cause of bifurcation could prove very useful for future design of FOWT controllers.

scholarly journals Application of a Monte Carlo Procedure for Probabilistic Fatigue Design of Floating Offshore Wind Turbines

2017 ◽  
Author(s):  
Kolja Müller ◽  
Po Wen Cheng
Keyword(s):  
Monte Carlo ◽  
Wind Turbines ◽  
Environmental Conditions ◽  
Measurement Data ◽  
Monte Carlo Integration ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Sampling Procedures ◽  
The Impact

Abstract. Fatigue load assessment of floating offshore wind turbines poses new challenges on the feasibility of numerical procedures. Due to the increased sensitivity of the considered system with respect to the environmental conditions from wind and ocean, the application of common procedures used for fixed-bottom structures results in either inaccurate simulation results or hard-to-quantify conservatism in the system design. Monte Carlo based sampling procedures provide a more realistic approach to deal with the large variation of the environmental conditions, although basic randomization has shown slow convergence. Specialized sampling methods allow efficient coverage of the complete design space, resulting in faster convergence and hence a reduced number of required simulations. In this study, a quasi-random sampling approach based on Sobol’ sequences is applied to select representative events for the determination of the lifetime damage. This is calculated applying Monte-Carlo integration, using subsets of a resulting total of 16 200 coupled time-domain simulations performed with the simulation code FAST. The considered system is the DTU 10 MW reference turbine installed on the LIFES50+ OO-Star Wind Floater Semi 10 MW floating platform. Statistical properties of the considered environmental parameters (i.e. wind speed, wave height and wave period) are determined based on the measurement data from Gulf of Maine, USA. Convergence analyses show that it is sufficient to perform around 200 simulations in order to reach less than 10 % uncertainty of lifetime fatigue damage equivalent loading. Complementary in-depth investigation is performed focusing on the load sensitivity and the impact of outliers. Recommendations for the implementation of the proposed methodology in the design process are also provided.

scholarly journals Application of a Monte Carlo procedure for probabilistic fatigue design of floating offshore wind turbines

2018 ◽  
Vol 3 (1) ◽  
pp. 149-162 ◽  
Author(s):  
Kolja Müller ◽  
Po Wen Cheng
Keyword(s):  
Monte Carlo ◽  
Wind Turbines ◽  
Environmental Conditions ◽  
Measurement Data ◽  
Monte Carlo Integration ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Sampling Procedures ◽  
The Impact

Abstract. Fatigue load assessment of floating offshore wind turbines poses new challenges on the feasibility of numerical procedures. Due to the increased sensitivity of the considered system with respect to the environmental conditions from wind and ocean, the application of common procedures used for fixed-bottom structures results in either inaccurate simulation results or hard-to-quantify conservatism in the system design. Monte Carlo-based sampling procedures provide a more realistic approach to deal with the large variation in the environmental conditions, although basic randomization has shown slow convergence. Specialized sampling methods allow efficient coverage of the complete design space, resulting in faster convergence and hence a reduced number of required simulations. In this study, a quasi-random sampling approach based on Sobol sequences is applied to select representative events for the determination of the lifetime damage. This is calculated applying Monte Carlo integration, using subsets of a resulting total of 16 200 coupled time–domain simulations performed with the simulation code FAST. The considered system is the Danmarks Tekniske Universitet (DTU) 10 MW reference turbine installed on the LIFES50+ OO-Star Wind Floater Semi 10 MW floating platform. Statistical properties of the considered environmental parameters (i.e., wind speed, wave height and wave period) are determined based on the measurement data from the Gulf of Maine, USA. Convergence analyses show that it is sufficient to perform around 200 simulations in order to reach less than 10 % uncertainty of lifetime fatigue damage-equivalent loading. Complementary in-depth investigation is performed, focusing on the load sensitivity and the impact of outliers (i.e., values far away from the mean). Recommendations for the implementation of the proposed methodology in the design process are also provided.

Jump Bifurcation Phenomenon During Varying Wind Speeds in Floating Offshore Wind Turbines

2020 ◽  
Author(s):  
Alwin Jose ◽  
Jeffrey Falzarano
Keyword(s):  
Transition Region ◽  
Wind Turbines ◽  
Large Amplitude ◽  
Offshore Wind ◽  
Nonlinear Phenomenon ◽  
Motion Response ◽  
Offshore Wind Turbines ◽  
Future Design ◽  
Wind Speeds ◽  
Floating Offshore Wind Turbines

Abstract Floating Offshore Wind Turbines (FOWTs) are susceptible to an instability which has come to be called “negative damping”. Conventional land based wind turbine controllers when used with FOWTs may cause large amplitude platform pitch oscillations. Most controllers have since been improved to reduce motions due to this phenomenon. In this paper, the motions induced using one of the original controllers is studied. The current study is performed using the coupled time domain program FAST-SIMDYN that was developed in Marine Dynamics Laboratory (MDL) at Texas A&M University. It is capable of studying large amplitude motions of Floating Offshore Wind Turbines. FOWTs use various controller algorithms of operation based on the available wind speed depending on various power output objectives i.e., to either maximize or level out power absorption. It is observed that the transition region for controllers is often chaotic. So most studies focus on operations away from the transition region i.e., both below and above the transition wind speeds. Here we study the transition region using the theoretical insight of non-linear motion response of structures. This study reveals the presence of a very interesting and potentially hazardous nonlinear phenomenon, bifurcation. This finding could help explain the chaotic motion response that is observed in the transition region of controllers. Understanding the nature and cause of bifurcation could prove very useful for future design of FOWT controllers.

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