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

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.

2021 ◽  
Author(s):  
Rieska Mawarni Putri ◽  
Etienne Cheynet ◽  
Charlotte Obhrai ◽  
Jasna Bogunovic Jakobsen

Abstract. Turbulence spectral characteristics for various atmospheric stratifications are studied using the observations from an offshore mast at Vindeby wind farm. Measurement data at 6 m, 18 m and 45 m above the mean sea level are considered. At the lowest height, the normalized power spectral densities of the velocity components show deviations from Monin-Obukhov similarity theory (MOST). A significant co-coherence at the wave spectral peak frequency between the vertical velocity component and the velocity of the sea surface is observed, but only when the significant wave heights exceed 0.9 m. The turbulence spectra at 18 m generally follow MOST and are consistent with the empirical spectra established on the FINO1 offshore platform from an earlier study. The data at 45 m is associated with a high-frequency measurement noise which limits its analysis to strong wind conditions only. The estimated co-coherence of the along-wind component under near-neutral atmosphere matches remarkably well with those at FINO1. The turbulence characteristics estimated from the present dataset are valuable to better understand the structure of turbulence in the marine atmospheric boundary layer and are relevant for load estimations of offshore wind turbines. Yet, a direct application of the results to other offshore or coastal sites should be exercised with caution, since the dataset is collected in shallow waters and at heights lower than the hub height of the current and the future state-of-the-art offshore wind turbines.


Energies ◽  
2021 ◽  
Vol 14 (22) ◽  
pp. 7576
Author(s):  
Maximilian Henkel ◽  
Wout Weijtjens ◽  
Christof Devriendt

The design of monopile foundations for offshore wind turbines is most often driven by fatigue. With the foundation price contributing to the total price of a turbine structure by more than 30%, wind farm operators seek to gain knowledge about the amount of consumed fatigue. Monitoring concepts are developed to uncover structural reserves coming from conservative designs in order to prolong the lifetime of a turbine. Amongst promising concepts is a wide array of methods using in-situ measurement data and extrapolating these results to desired locations below water surface and even seabed using models. The modal decomposition algorithm is used for this purpose. The algorithm obtains modal amplitudes from acceleration and strain measurements. In the subsequent expansion step these amplitudes are expanded to virtual measurements at arbitrary locations. The algorithm uses a reduced order model that can be obtained from either a FE model or measurements. In this work, operational modal analysis is applied to obtain the required stress and deflection shapes for optimal validation of the method. Furthermore, the measurements that are used as input for the algorithms are constrained to measurements from the dry part of the substructure. However, with subsoil measurement data available from a dedicated campaign, even validation for locations below mud-line is possible. After reconstructing strain history in arbitrary locations on the substructure, fatigue assessment over various environmental and operational conditions is carried out. The technique is found capable of estimating fatigue with high precision for locations above and below seabed.


2020 ◽  
Author(s):  
Janna K. Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen

Abstract. The correlation of power output fluctuations of wind turbines in free field are investigated, taking into account the challenge of varying correlation states due to variable flow and wind turbine conditions within the wind farm. Based on eight months of 1 Hz SCADA data, measured at an offshore wind farm with 80 wind turbines, the influence of different parameters on the correlation of power output fluctuations is analysed. It is found that the correlation of power output fluctuations of wind turbines depends on the location of the wind turbines within the wind farm as well as the inflow conditions (free-stream or wake). Wind direction investigations show that the correlation is highest for streamwise aligned pairs and decreases towards spanwise pairs. Most importantly, the highly variable measurement data in a free-field wind farm has considerable influence on the identification of different correlation states. To account for that, the clustering algorithm k-means is used to group wind turbine pairs with similar correlations. The main outcome is that next to the location of a wind turbine pair in the wind farm the standard deviation in their power output and their power differences are suitable parameters to describe the correlation of power output fluctuations.


Author(s):  
Jose´ G. Rangel-Rami´rez ◽  
John D. So̸rensen

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.


Author(s):  
Bryan Nelson ◽  
Yann Quéméner

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.


2016 ◽  
Vol 138 (4) ◽  
Author(s):  
Espen Engebretsen ◽  
Sverre K. Haver ◽  
Dag Myrhaug

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.


2021 ◽  
Vol 6 (4) ◽  
pp. 997-1014
Author(s):  
Janna Kristina Seifert ◽  
Martin Kraft ◽  
Martin Kühn ◽  
Laura J. Lukassen

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.


2019 ◽  
Vol 8 (1) ◽  
pp. 91
Author(s):  
Seyed Saed Heidary Yazdi ◽  
Jafar Milimonfared ◽  
Seyed Hamid Fathi

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


Energies ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 882 ◽  
Author(s):  
Hongyan Ding ◽  
Zuntao Feng ◽  
Puyang Zhang ◽  
Conghuan Le ◽  
Yaohua Guo

The composite bucket foundation (CBF) for offshore wind turbines is the basis for a one-step integrated transportation and installation technique, which can be adapted to the construction and development needs of offshore wind farms due to its special structural form. To transport and install bucket foundations together with the upper portion of offshore wind turbines, a non-self-propelled integrated transportation and installation vessel was designed. In this paper, as the first stage of applying the proposed one-step integrated construction technique, the floating behavior during the transportation of CBF with a wind turbine tower for the Xiangshui wind farm in the Jiangsu province was monitored. The influences of speed, wave height, and wind on the floating behavior of the structure were studied. The results show that the roll and pitch angles remain close to level during the process of lifting and towing the wind turbine structure. In addition, the safety of the aircushion structure of the CBF was verified by analyzing the measurement results for the interaction force and the depth of the liquid within the bucket. The results of the three-DOF (degree of freedom) acceleration monitoring on the top of the test tower indicate that the wind turbine could meet the specified acceleration value limits during towing.


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