Extreme Wave Condition at Doggerbank

2016 ◽  
Vol 138 (4) ◽  
Author(s):  
Espen Engebretsen ◽  
Sverre K. Haver ◽  
Dag Myrhaug
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Wind ◽  
Extreme Condition ◽  
Exceedance Probability ◽  
Extreme Wave ◽  
Sea State ◽  
Wave Condition ◽  
The North ◽  
Wave Conditions

In design of offshore wind turbines, extreme wave conditions are of interest. Usually, the design wave condition is taken as the sea state corresponding to an annual exceedance probability of 2 × 10−2, i.e., a return period of 50 years. A possible location for a future wind farm, consisting of bottom fixed wind turbines, is the Doggerbank area. The water depth in this area varies from about 60 m in the north to about 20 m in the south. The hindcast database NORA10 provides sea state characteristics from 1957 to present over a domain covering Doggerbank. Regarding the deeper areas just north of Doggerbank, this hindcast model is found to be of good quality. Larger uncertainties are associated with the hindcast results as we approach shallower water further south. The purpose of the present study is to compare sea state evolution over Doggerbank as reflected by NORA10 with the results of the commonly used shallow water hindcast model SWAN. The adequacy of the default parameters of SWAN for reflecting changes in wave conditions over a sloping bottom is investigated by comparison with model test results. Extreme wave conditions for two locations 102.5 km apart in a north–south direction are established using NORA10. This is done using both, an all sea states approach and a peak over threshold (POT) approach. Assuming the extremes for the northern position to represent good estimates, the wave evolution southward is analyzed using SWAN. The extreme condition obtained from NORA10 in the northern position is used as input to SWAN and the results from the two hindcast models are compared in the southern position. SWAN seems to suggest a somewhat faster decay over Doggerbank compared to NORA10.

Extreme Wave Condition at Doggerbank

2014 ◽  
Author(s):  
Espen Engebretsen ◽  
Sverre K. Haver ◽  
Dag Myrhaug
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Wind ◽  
Extreme Condition ◽  
Exceedance Probability ◽  
Extreme Wave ◽  
Sea State ◽  
Wave Condition ◽  
The North ◽  
Wave Conditions

In design of offshore wind turbines, extreme wave conditions are of interest. Usually, the design wave condition is taken as the sea state corresponding to an annual exceedance probability of 2·10−2, i.e. a return period of 50 years. A possible location for a future wind farm, consisting of bottom fixed wind turbines, is the Doggerbank area, see Figure 1. The water depth in this area varies from about 60m in the north to about 20m in the south. The hindcast database NORA10 provides sea state characteristics from 1957 to present over a domain covering Doggerbank. Regarding the deeper areas just north of Doggerbank, this hindcast model is found to be of good quality. Larger uncertainties are associated with the hindcast results as we approach shallower water further south. The purpose of the present study is to compare sea state evolution over Doggerbank as reflected by NORA10 with the results of commonly used shallow water hindcast model SWAN. The adequacy of the default parameters of SWAN for reflecting changes in wave conditions over a sloping bottom is investigated by comparison with model test results. Extreme wave conditions for two locations 102.5km apart in a north–south direction are established using NORA10. This is done using both an all sea states approach and a peak over threshold approach. Assuming the extremes for the northern position to represent good estimates, the wave evolution southwards is analyzed using SWAN. The extreme condition obtained from NORA10 in the northern position is used as input to SWAN and the results from the two hindcast models are compared in the southern position. SWAN seems to suggest a somewhat faster decay over Doggerbank compared to NORA10.

scholarly journals Towards the North Sea wind power revolution

2018 ◽  
Author(s):  
Jens N. Sørensen ◽  
Gunner C. Larsen
Keyword(s):  
Wind Power ◽  
North Sea ◽  
Wind Turbines ◽  
Wind Farm ◽  
Cost Model ◽  
Offshore Wind ◽  
Meteorological Model ◽  
The North ◽  
The North Sea ◽  
The Cost

Abstract. The present work assesses the potential of a massive exploitation of offshore wind power in the North Sea by combining a meteorological model with a cost model that includes a bathymetric analysis of the water depth of the North Sea. The overall objective is to assess if the wind power in the North Sea can deliver the total consumption of electricity in Europe and to what prize as compared to conventional onshore wind energy. The meteorological model is based on the assumption that the exploited area is so large, that the wind field between the turbines is in equilibrium with the atmospheric boundary layer. This makes it possible to use momentum analysis to determine the mutual influence between the atmospheric boundary layer and the wind farm, with the wind farm represented by an average horizontal force component corresponding to the thrust. The cost model includes expressions for the most essential wind farm cost elements, such as costs of wind turbines, support structures, cables and electrical substations, as well as operation and maintenance as function of rotor size, interspatial distance between the turbines, and water depth. The numbers used in the cost model are based on previous experience from offshore wind farms, and is therefore somewhat conservative. The analysis shows that the lowest energy cost is obtained for a configuration of large wind turbines erected with an interspatial distance of about eight rotor diameters. A part of the analysis is devoted to assessing the relative costs of the various elements of the cost model in order to determine the components with the largest potential for reducing the cost price. As an overall finding, it is shown that the power demand of Europe, which is 0.4 TW or about 3500 TWh/year, can be fulfilled by exploiting an area of 190.000 km2, corresponding to about 1/3 of the North Sea, with 100.000 wind turbines of generator size 13 MW on water depths up to 45 m at a cost price of about 7.5 €cents/kWh.

scholarly journals Stable Ships for Smooth Servicing of Offshore Wind Farms

2014 ◽  
pp. 179-183
Author(s):  
Matthew Shanley
Keyword(s):  
Wind Turbines ◽  
Wind Farm ◽  
Wind Farms ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Irish Sea ◽  
Offshore Wind Farms ◽  
The North ◽  
The North Sea ◽  
The Irish Sea

There is a rapid increase in the number of offshore wind farms in European waters to help meet renewable energy targets. Wind turbines are being installed in progressively more exposed areas of the North Sea and the Irish Sea, with the eventual aim of placing them in the Atlantic Ocean. As offshore wind farms require regular maintenance, being able to access the wind turbines during rough sea conditions is a key issue for profitable operation. The operation involves transferring personnel from the service ship to the wind turbine. The current wave height limit for this is 1.5 m, slightly less than 5 feet, increasing this results in significant savings over the lifetime of the wind farm. Each wind farm service ship has 12 maintenance crew. Imagine you are one waiting on port for the sea and weather conditions to be right so that you can head out to the wind ...

scholarly journals Maintenance Planning of Offshore Wind Turbine Using Condition Monitoring Information

2009 ◽  
Author(s):  
Jose´ G. Rangel-Rami´rez ◽  
John D. So̸rensen
Keyword(s):  
Condition Monitoring ◽  
Wind Turbines ◽  
Wind Farm ◽  
Offshore Structures ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Maintenance Planning ◽  
Offshore Wind Turbines ◽  
Inspection And Maintenance ◽  
Monitoring Information

Deterioration processes such as fatigue and corrosion are typically affecting offshore structures. To “control” this deterioration, inspection and maintenance activities are developed. Probabilistic methodologies represent an important tool to identify the suitable strategy to inspect and control the deterioration in structures such as offshore wind turbines (OWT). Besides these methods, the integration of condition monitoring information (CMI) can optimize the mitigation activities as an updating tool. In this paper, a framework for risk-based inspection and maintenance planning (RBI) is applied for OWT incorporating CMI, addressing this analysis to fatigue prone details in welded steel joints at jacket or tripod steel support structures for offshore wind turbines. The increase of turbulence in wind farms is taken into account by using a code-based turbulence model. Further, additional modes t integrate CMI in the RBI approach for optimal planning of inspection and maintenance. As part of the results, the life cycle reliabilities and inspection times are calculated, showing that earlier inspections are needed at in-wind farm sites. This is expected due to the wake turbulence increasing the wind load. With the integration of CMI by means Bayesian inference, a slightly change of first inspection times are coming up, influenced by the reduction of the uncertainty and harsher or milder external agents.

scholarly journals Optimal Temperature-Based Condition Monitoring System for Wind Turbines

2021 ◽  
Vol 6 (4) ◽  
pp. 50
Author(s):  
Payam Teimourzadeh Baboli ◽  
Davood Babazadeh ◽  
Amin Raeiszadeh ◽  
Susanne Horodyvskyy ◽  
Isabel Koprek
Keyword(s):  
Monitoring System ◽  
Wind Turbines ◽  
Wind Farm ◽  
Measurement Data ◽  
Real Data ◽  
Offshore Wind ◽  
Risk Indicator ◽  
Real World Data ◽  
The Real ◽  
Data Driven Modeling

With the increasing demand for the efficiency of wind energy projects due to challenging market conditions, the challenges related to maintenance planning are increasing. In this paper, a condition-based monitoring system for wind turbines (WTs) based on data-driven modeling is proposed. First, the normal condition of the WTs key components is estimated using a tailor-made artificial neural network. Then, the deviation of the real-time measurement data from the estimated values is calculated, indicating abnormal conditions. One of the main contributions of the paper is to propose an optimization problem for calculating the safe band, to maximize the accuracy of abnormal condition identification. During abnormal conditions or hazardous conditions of the WTs, an alarm is triggered and a proposed risk indicator is updated. The effectiveness of the model is demonstrated using real data from an offshore wind farm in Germany. By experimenting with the proposed model on the real-world data, it is shown that the proposed risk indicator is fully consistent with upcoming wind turbine failures.

Fatigue Life Analysis of Offshore Wind Turbine Support Structures in an Offshore Wind Farm

2018 ◽  
Author(s):  
Bryan Nelson ◽  
Yann Quéméner
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Wind Farm ◽  
The Body ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Analysis Tool ◽  
Support Structures ◽  
Offshore Wind Farm ◽  
Actuator Disk

This study evaluated, by time-domain simulations, the fatigue lives of several jacket support structures for 4 MW wind turbines distributed throughout an offshore wind farm off Taiwan’s west coast. An in-house RANS-based wind farm analysis tool, WiFa3D, has been developed to determine the effects of the wind turbine wake behaviour on the flow fields through wind farm clusters. To reduce computational cost, WiFa3D employs actuator disk models to simulate the body forces imposed on the flow field by the target wind turbines, where the actuator disk is defined by the swept region of the rotor in space, and a body force distribution representing the aerodynamic characteristics of the rotor is assigned within this virtual disk. Simulations were performed for a range of environmental conditions, which were then combined with preliminary site survey metocean data to produce a long-term statistical environment. The short-term environmental loads on the wind turbine rotors were calculated by an unsteady blade element momentum (BEM) model of the target 4 MW wind turbines. The fatigue assessment of the jacket support structure was then conducted by applying the Rainflow Counting scheme on the hot spot stresses variations, as read-out from Finite Element results, and by employing appropriate SN curves. The fatigue lives of several wind turbine support structures taken at various locations in the wind farm showed significant variations with the preliminary design condition that assumed a single wind turbine without wake disturbance from other units.

scholarly journals Correlations of power output fluctuations in an offshore wind farm using high-resolution SCADA data

2021 ◽  
Vol 6 (4) ◽  
pp. 997-1014
Author(s):  
Janna Kristina Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Power Output ◽  
Wind Farm ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Flow Conditions ◽  
Output Fluctuations ◽  
Power Difference ◽  
Time Correlations

Abstract. Space–time correlations of power output fluctuations of wind turbine pairs provide information on the flow conditions within a wind farm and the interactions of wind turbines. Such information can play an essential role in controlling wind turbines and short-term load or power forecasting. However, the challenges of analysing correlations of power output fluctuations in a wind farm are the highly varying flow conditions. Here, we present an approach to investigate space–time correlations of power output fluctuations of streamwise-aligned wind turbine pairs based on high-resolution supervisory control and data acquisition (SCADA) data. The proposed approach overcomes the challenge of spatially variable and temporally variable flow conditions within the wind farm. We analyse the influences of the different statistics of the power output of wind turbines on the correlations of power output fluctuations based on 8 months of measurements from an offshore wind farm with 80 wind turbines. First, we assess the effect of the wind direction on the correlations of power output fluctuations of wind turbine pairs. We show that the correlations are highest for the streamwise-aligned wind turbine pairs and decrease when the mean wind direction changes its angle to be more perpendicular to the pair. Further, we show that the correlations for streamwise-aligned wind turbine pairs depend on the location of the wind turbines within the wind farm and on their inflow conditions (free stream or wake). Our primary result is that the standard deviations of the power output fluctuations and the normalised power difference of the wind turbines in a pair can characterise the correlations of power output fluctuations of streamwise-aligned wind turbine pairs. Further, we show that clustering can be used to identify different correlation curves. For this, we employ the data-driven k-means clustering algorithm to cluster the standard deviations of the power output fluctuations of the wind turbines and the normalised power difference of the wind turbines in a pair. Thereby, wind turbine pairs with similar power output fluctuation correlations are clustered independently from their location. With this, we account for the highly variable flow conditions inside a wind farm, which unpredictably influence the correlations.

scholarly journals Adaptation of VSC-HVDC Connected DFIG Based Offshore Wind Farm to Grid Codes: A Comparative Analysis

2019 ◽  
Vol 8 (1) ◽  
pp. 91
Author(s):  
Seyed Saed Heidary Yazdi ◽  
Jafar Milimonfared ◽  
Seyed Hamid Fathi
Keyword(s):  
Comparative Analysis ◽  
Frequency Response ◽  
Wind Turbines ◽  
Wind Farm ◽  
Control Structure ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Grid Codes ◽  
Primary Frequency ◽  
Primary Frequency Response

Lack of synchronism between VSC-HVDC (Voltage Source Converter - High Voltage Direct Current) connected offshore wind farm and onshore grid leads to immunity of wind turbines to grid contingencies. Focusing on DFIG (Doubly Fed Induction Generator) based wind farms; this paper has presented a univalent control structure based on inertial and primary frequency response in which DC link voltage is utilized as synchronization interface. Based on the presented structure, four approaches based on the communication system, frequency, voltage and combined frequency and voltage modulation are utilized and compared to inform the onshore grid status to individual wind turbines. Considering Kondurs two area power system, results have revealed that all four approaches have similar ability (with negligible error) in offering inertial and primary frequency response to improve slow network oscillations. On the other hand, voltage and combined frequency and voltage modulation approaches have the ability to satisfy Fault Ride Through (FRT) requirements thanks to superior dynamics. However, communication and frequency modulation approaches lose that ability as communication and frequency measurement delays increase respectively. It has been concluded that combined frequency and voltage modulation, as the superior approach, has advantages like minimum FRT DC voltage profile increase and deviation from operating point after the fault, the minimum imposition of electrical and mechanical stress on DFIG and preservation of prevalent control structure thanks to appropriate dissociation between slow and fast dynamics.©2019. CBIORE-IJRED. All rights reservedArticle History: Received Dec 8th 2017; Received in revised form July 16th 2018; Accepted December 15th 2018; Available onlineHow to Cite This Article: Yazdi, S.S.H., Milimonfared, J. and Fathi, S.H. (2019). Adaptation of VSC-HVDC Connected DFIG Based Offshore Wind Farm to Grid Codes: A Comparative Analysis. Int. Journal of Renewable Energy Development, 8(1), 91-101.https://doi.org/10.14710/ijred.8.1.91-101

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