Extreme Load Predictions for Floating Offshore Wind Turbines

2009 ◽  
Author(s):  
Jo̸rgen Juncher Jensen
Keyword(s):  
Wind Turbines ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
First Order ◽  
Floating Offshore Wind Turbines ◽  
Extreme Load ◽  
Reliability Method ◽  
Short Time ◽  
Wave Induced ◽  
Stochastic Loads

An effective stochastic procedure for extreme value predictions related to wave and wind induced stochastic loads is applied to a tension-leg concept for floating offshore wind turbines. The method is based on the First Order Reliability Method (FORM) and as the procedure makes use of only short time-domain simulations all kinds of non-linearities can be included. The procedure has been used previously for wave induced loads and is in this note extended to combined wave and wind loads.

scholarly journals Digital twins of the mooring line tension for floating offshore wind turbines to improve monitoring, lifespan, and safety

2021 ◽  
Author(s):  
Jake Walker ◽  
Andrea Coraddu ◽  
Maurizio Collu ◽  
Luca Oneto
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Mechanical Response ◽  
Offshore Wind ◽  
Mooring Line ◽  
Offshore Wind Turbines ◽  
Axial Tension ◽  
Floating Offshore Wind Turbines ◽  
Extreme Load ◽  
Operational Data

AbstractThe number of installed floating offshore wind turbines (FOWTs) has doubled since 2017, quadrupling the total installed capacity, and is expected to increase significantly over the next decade. Consequently, there is a growing consideration towards the main challenges for FOWT projects: monitoring the system’s integrity, extending the lifespan of the components, and maintaining FOWTs safely at scale. Effectively and efficiently addressing these challenges would unlock the wide-scale deployment of FOWTs. In this work, we focus on one of the most critical components of the FOWTs, the Mooring Lines (MoLs), which are responsible for fixing the structure to the seabed. The primary mechanical failure mechanisms in MoLs are extreme load and fatigue, both of which are functions of the axial tension. An effective solution to detect long-term drifts in the mechanical response of the MoLs is to develop a Digital Twin (DT) able to accurately predict the behaviour of the healthy system to compare with the actual one. Moreover, we will develop another DT able to accurately predict the near future axial tension as an effective tool to improve the lifespan of the MoLs and the safety of FOWT maintenance operations. In fact, by changing the FOWT operational settings, according to the DT prediction, operators can increase the lifespan of the MoLs by reducing the stress and, additionally, in the case where FOWT operational maintenance is in progress, the prediction from the DT can serve as early safety warning to operators. Authors will leverage operational data collected from the world’s first commercial floating-wind farm [the Hywind Pilot Park (https://www.equinor.com/en/what-we-do/floating-wind/hywind-scotland.html.)] in 2018, to investigate the effectiveness of DTs for the prediction of the MoL axial tension for the two scenarios depicted above. The DTs will be developed using state-of-the-art data-driven methods, and results based on real operational data will support our proposal.

Pitch Angle Control of Floating Offshore Wind Turbines by H∞ Control

2014 ◽  
Vol 134 (8) ◽  
pp. 1096-1103 ◽  
Author(s):  
Sho Tsujimoto ◽  
Ségolène Dessort ◽  
Naoyuki Hara ◽  
Keiji Konishi
Keyword(s):  
Wind Turbines ◽  
Pitch Angle ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines

scholarly journals Impact of Typhoons on Floating Offshore Wind Turbines: A Case Study of Typhoon Mangkhut

2021 ◽  
Vol 9 (5) ◽  
pp. 543
Author(s):  
Jiawen Li ◽  
Jingyu Bian ◽  
Yuxiang Ma ◽  
Yichen Jiang
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Safety Evaluation ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Motion Response ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Coupling Motion

A typhoon is a restrictive factor in the development of floating wind power in China. However, the influences of multistage typhoon wind and waves on offshore wind turbines have not yet been studied. Based on Typhoon Mangkhut, in this study, the characteristics of the motion response and structural loads of an offshore wind turbine are investigated during the travel process. For this purpose, a framework is established and verified for investigating the typhoon-induced effects of offshore wind turbines, including a multistage typhoon wave field and a coupled dynamic model of offshore wind turbines. On this basis, the motion response and structural loads of different stages are calculated and analyzed systematically. The results show that the maximum response does not exactly correspond to the maximum wave or wind stage. Considering only the maximum wave height or wind speed may underestimate the motion response during the traveling process of the typhoon, which has problems in guiding the anti-typhoon design of offshore wind turbines. In addition, the coupling motion between the floating foundation and turbine should be considered in the safety evaluation of the floating offshore wind turbine under typhoon conditions.

scholarly journals Performance Analysis on the Use of Oscillating Water Column in Barge-Based Floating Offshore Wind Turbines

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 475
Author(s):  
Payam Aboutalebi ◽  
Fares M’zoughi ◽  
Izaskun Garrido ◽  
Aitor J. Garrido
Keyword(s):  
Wind Turbines ◽  
Positive Impact ◽  
Offshore Wind ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Water Columns ◽  
Numerical Tools ◽  
Oscillating Water Columns ◽  
The Given ◽  
The Waves

Undesired motions in Floating Offshore Wind Turbines (FOWT) lead to reduction of system efficiency, the system’s lifespan, wind and wave energy mitigation and increment of stress on the system and maintenance costs. In this article, a new barge platform structure for a FOWT has been proposed with the objective of reducing these undesired platform motions. The newly proposed barge structure aims to reduce the tower displacements and platform’s oscillations, particularly in rotational movements. This is achieved by installing Oscillating Water Columns (OWC) within the barge to oppose the oscillatory motion of the waves. Response Amplitude Operator (RAO) is used to predict the motions of the system exposed to different wave frequencies. From the RAOs analysis, the system’s performance has been evaluated for representative regular wave periods. Simulations using numerical tools show the positive impact of the added OWCs on the system’s stability. The results prove that the proposed platform presents better performance by decreasing the oscillations for the given range of wave frequencies, compared to the traditional barge platform.

Open-Loop Control Co-Design of Floating Offshore Wind Turbines Using Linear Parameter-Varying Models

2021 ◽  
Author(s):  
Athul K. Sundarrajan ◽  
Yong Hoon Lee ◽  
James T. Allison ◽  
Daniel R. Herber
Keyword(s):  
Wind Turbines ◽  
Open Loop ◽  
Offshore Wind ◽  
Linear Parameter ◽  
Design Decisions ◽  
Linear Parameter Varying ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Parameter Varying ◽  
And Control

Abstract This paper discusses a framework to design elements of the plant and control systems for floating offshore wind turbines (FOWTs) in an integrated manner using linear parameter-varying models. Multiple linearized models derived from high-fidelity software are used to model the system in different operating regions characterized by the incoming wind speed. The combined model is then used to generate open-loop optimal control trajectories as part of a nested control co-design strategy that explores the system’s stability and power production in the context of crucial plant and control design decisions. A cost model is developed for the FOWT system, and the effect of plant decisions and subsequent power and stability response of the FOWT is quantified in terms of the levelized cost of energy (LCOE) for that system. The results show that the stability constraints and the plant design decisions affect the turbine’s power and, subsequently, LCOE of the system. The results indicate that a lighter plant in terms of mass can produce the same power for a lower LCOE while still satisfying the constraints.

Software-in-the-Loop Combined Machine Learning for Dynamic Responses Analysis of Floating Offshore Wind Turbines

2021 ◽  
Author(s):  
Peng Chen ◽  
Changhong Hu ◽  
Zhiqiang Hu
Keyword(s):  
Machine Learning ◽  
Experimental Data ◽  
Wind Turbines ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Learning Technology ◽  
Mean Values ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Brute Force Method

Abstract Artificial intelligence (AI) brings a new solution to overcome the challenges of Floating offshore wind turbines (FOWTs) to better predict the dynamic responses with intelligent strategies. A new AI-based software-in-the-loop method, named SADA is introduced in this paper for the prediction of dynamic responses of FOWTs, which is proposed based on an in-house programme DARwind. DARwind is a coupled aero-hydro-servo-elastic in-house program for FOWTs, and a reinforcement learning method with exhaust algorithm and deep deterministic policy gradient (DDPG) are embedded in DARwind as an AI module. Firstly, the methodology is introduced with the selection of Key Disciplinary Parameters (KDPs). Secondly, Brute-force Method and DDPG algorithms are adopted to changes the KDPs’ values according to the feedback of 6DOF motions of Hywind Spar-type platform through comparing the DARwind simulation results and those of basin experimental data. Therefore, many other dynamic responses that cannot be measured in basin experiment can be predicted in good accuracy with SADA method. Finally, the case study of SADA method was conducted and the results demonstrated that the mean values of the platform’s motions can be predicted with higher accuracy. This proposed SADA method takes advantage of numerical-experimental method, basin experimental data and the machine learning technology, which brings a new and promising solution for overcoming the handicap impeding direct use of conventional basin experimental way to analyze FOWT’s dynamic responses during the design phase.

Fault Tree Analysis of floating offshore wind turbines

2019 ◽  
Vol 133 ◽  
pp. 1455-1467 ◽  
Author(s):  
Jichuan Kang ◽  
Liping Sun ◽  
C. Guedes Soares
Keyword(s):  
Wind Turbines ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Offshore Wind ◽  
Tree Analysis ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines
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