Machine Learning Proxies Integrating Wake Effects in Offshore Wind Generation for Adequacy Studies

Author(s):  
Thuy-hai Nguyen ◽  
Jean-Francois Toubeau ◽  
Emmanuel De Jaeger ◽  
Francois Vallee
2021 ◽  
Author(s):  
Peng Chen ◽  
Changhong Hu ◽  
Zhiqiang Hu

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.


2020 ◽  
Vol 54 (6) ◽  
pp. 108-113
Author(s):  
Sarah Freeman ◽  
Jake Gentle ◽  
Tim Conway

AbstractAs wind generation becomes more prevalent, it is critical that these resources remain secure and, perhaps more significantly, resilient in the face of cyberattacks. Additionally, the remote locations of offshore wind assets increase the cost associated with responding to cyber incidents. Existing risk assessment techniques, such as consequence prioritization and MITRE ATT&CK, can be used by the wind industry to identify potential impacts from cyberattacks. This perspective can then inform cybersecurity investment strategies for greatest impact.


2019 ◽  
Vol 122 ◽  
pp. 04005
Author(s):  
Ilayda Ulku ◽  
Cigdem Alabas-Uslu

A wind farm, mainly, is composed of a set of turbines, one or more transmitters and a set of electrical cable connections between turbines and transmitters. Determination of turbine locations within the farm to maximize total power generation is called turbine location (TL) problem. Relative turbine positions affect the amount of overall energy because of wake effects. Determination of cable connections among turbines and transmitters to collect produced energy by turbines at transmitters is called cable layout (CL) problem. While TL problem is directly effective on the total energy production in the farm, CL problem indirectly affects the total energy due to the power losses. In the literature, TL and CL problems are solved sequentially where the layout found by solving of TL is used as an input of CL problem. To minimize wake effects in TL problem, distances between turbine pairs should be increased, however, as the distances are increased the cable cost increases in CL problem. A new mathematical model is developed to deal with simultaneously solving of TL and CL problems. A set of test instances are used to show the performance of the proposed model. The experiments show the practical use of the proposed holistic model.


Author(s):  
Sarah McElman ◽  
Arjen Koop ◽  
Erik-Jan de Ridder ◽  
Andrew Goupee

The development of a new wind-wave facility for offshore floating wind turbine testing can be complex; outfitting existing basins with wind generation capacity can be even more of a challenge. We present the simulation, design, and construction of a wind generation system for use in a modified existing basin at MARIN for the purpose of new concept testing for floating offshore wind turbines. Computational fluid dynamics simulations using MARIN’s ReFRESCO software are carried out for wind generator design and flow characterization within the basin. Modifications to improve the wind flow quality from the designed configuration, with the aid of CFD simulations, are discussed for the constructed system. Measurements on the completed wind generation system show reasonable spatial uniformity of the flow and turbulence intensities similar to atmospheric wind flows. Finally, suggestions for the construction of similar testing facilities are provided based on lessons learned from this retrofit project.


2016 ◽  
Vol 33 (3) ◽  
pp. 481-501 ◽  
Author(s):  
Niranjan S. Ghaisas ◽  
Cristina L. Archer

AbstractLayout studies are critical in designing large wind farms, since wake effects can lead to significant reductions in power generation. Optimizing wind farm layout using computational fluid dynamics is practically unfeasible today because of their enormous computational requirements. Simple statistical models, based on geometric quantities associated with the wind farm layout, are therefore attractive because they are less demanding computationally. Results of large-eddy simulations of the Lillgrund (Sweden) offshore wind farm are used here to calibrate such geometry-based models. Several geometric quantities (e.g., blockage ratio, defined as the fraction of the swept area of a wind turbine that is blocked by upstream turbines) and their linear combinations are found to correlate very well (correlation coefficient of ~0.95) with the power generated by the turbines. Linear models based on these geometric quantities are accurate at predicting the farm-averaged power and are therefore used here to study layout effects in large wind farms. The layout parameters that are considered include angle between rows and columns, angle between incoming wind and columns (orientation), turbine spacings, and staggering of alternate rows. Each can impact wind power production positively or negatively, and their interplay is complex. The orientation angle is the most critical parameter influencing wake losses, as small changes in it can cause sharp variations in power. In general, for a prevailing wind direction, the orientation angle should be small (7.5°–20°) but not zero; staggering and spacing are beneficial; and nonorthogonal layouts may outperform orthogonal ones. This study demonstrates the utility of simple, inexpensive, and reasonably accurate geometry-based models to identify general principles governing optimal wind farm layout.


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