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.

Dynamic Responses of a Spar Type Floating Offshore Wind Turbine With Failed Moorings

2020 ◽  
Author(s):  
Yajun Ren ◽  
Vengatesan Venugopal
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Mooring System ◽  
Floating Offshore Wind Turbine ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines ◽  
Platform Motions

Abstract The complex dynamic characteristics of Floating Offshore Wind Turbines (FOWTs) have raised wider consideration, as they are likely to experience harsher environments and higher instabilities than the bottom fixed offshore wind turbines. Safer design of a mooring system is critical for floating offshore wind turbine structures for station keeping. Failure of mooring lines may lead to further destruction, such as significant changes to the platform’s location and possible collisions with a neighbouring platform and eventually complete loss of the turbine structure may occur. The present study focuses on the dynamic responses of the National Renewable Energy Laboratory (NREL)’s OC3-Hywind spar type floating platform with a NREL offshore 5-MW baseline wind turbine under failed mooring conditions using the fully coupled numerical simulation tool FAST. The platform motions in surge, heave and pitch under multiple scenarios are calculated in time-domain. The results describing the FOWT motions in the form of response amplitude operators (RAOs) and spectral densities are presented and discussed in detail. The results indicate that the loss of the mooring system firstly leads to longdistance drift and changes in platform motions. The natural frequencies and the energy contents of the platform motion, the RAOs of the floating structures are affected by the mooring failure to different degrees.

scholarly journals Software-in-the-Loop Combined Reinforcement Learning Method for Dynamic Response Analysis of FOWTs

2021 ◽  
Vol 7 ◽  
Author(s):  
Peng Chen ◽  
Jiahao Chen ◽  
Zhiqiang Hu
Keyword(s):  
Machine Learning ◽  
Policy Decision ◽  
Maximum Error ◽  
Machine Learning Algorithms ◽  
Dynamic Responses ◽  
Offshore Wind ◽  
Response Analysis ◽  
Learning Method ◽  
Mean Values ◽  
Floating Offshore Wind Turbines

Floating offshore wind turbines (FOWTs) still face many challenges on how to better predict the dynamic responses. Artificial intelligence (AI) brings a new solution to overcome these challenges with intelligent strategies. A new AI technology-based method, named SADA, is proposed in this paper for the prediction of dynamic responses of FOWTs. Firstly, the methodology of SADA is introduced with the selection of Key Disciplinary Parameters (KDPs). The AI module in SADA was built in a coupled aero-hydro-servo-elastic in-house program DARwind and the policy decision is provided by the machine learning algorithms deep deterministic policy gradient (DDPG). Secondly, a set of basin experimental results of a Hywind Spar-type FOWT were employed to train the AI module. SADA weights KDPs by DDPG algorithms' actor network and changes their values according to the training feedback of 6DOF motions of Hywind platform through comparing the DARwind simulation results and that of experimental data. Many other dynamic responses that cannot be measured in basin experiment could be predicted in higher accuracy with this intelligent DARwind. 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 by AI-based DARwind with higher accuracy, for example the maximum error of surge motion is reduced by 21%. This proposed SADA method takes advantage of numerical-experimental method and the machine learning method, which brings a new and promising solution for overcoming the handicap impeding direct use of traditional basin experimental technology in FOWTs design.

Scale Tests of the GICON®-TLP for Wind Turbines

2014 ◽  
Author(s):  
F. Adam ◽  
T. Myland ◽  
F. Dahlhaus ◽  
J. Großmann
Keyword(s):  
Experimental Data ◽  
Wind Turbines ◽  
Offshore Wind ◽  
Scale Model ◽  
Offshore Wind Turbine ◽  
Preliminary Design ◽  
Wave Loads ◽  
Ongoing Research ◽  
Offshore Wind Turbines ◽  
Floating Offshore Wind Turbines

The paper will present the preliminary design of the so called GICON® - Tension Leg Platform (TLP) as an innovative foundation concept for floating offshore wind turbines. Preliminary results from model basin tests are also shared. This includes the currently ongoing research of comparing calculated and experimental data obtained through extensive wind and wave tank experiments with a scale model of an offshore wind turbine at the Maritime Research Institute Netherlands (MARIN) in June 2013. These tests have provided insights regarding the dynamic characteristics of the GICON®-TLP by analyzing the system’s response to different load cases. The experiments included wind and wave loads, which represent three different sea states, each with three different directions of inflow. The chosen load cases correspond to the proposed location in the German Baltic Sea where the full scale prototype will be erected.

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.

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