bluuebunny/crossref_metadata_2025_split huggingface dataset:
The effect of wake position and yaw misalignment on power loss in wind turbines
Authors: Urbán Albert M. , Liew Jaime , Dellwik Ebba , Larsen Gunner Chr. 
Published: May 2019

Abstract
For a single wind turbine, the efficiency of extracting energy from the wind depends on the ability to align the wind turbine with the dominating wind direction. Considering average power production, yaw misalignment is relevant when the wind turbine operates with maximum power coefficient. On the other hand, the power production is less sensitive to yaw misalignment in high wind speeds, where the available energy in the wind field is higher than the maximum wind turbine capacity. In a wind farm, the interaction between nearby wind turbines alters the flow, and the power production is reduced. The present study investigates how yaw misalignment affects the power production in these wake situations compared to yaw misalignment effects for a wind turbine in the free-stream. Two generic cases are presented in this paper, offshore and forest, where the atmospheric conditions alter the morphology of the wake and, therefore, the power output of a yawed wind turbine operating in wake conditions. The results show that, for a conventional downstream spacing further than 3 rotor diameters, yaw misalignment results in larger power loss in wake situations than in free-stream. In wake situations, the presented results also show that the spatial distribution of the deficit influences the relative power loss when the wind turbine is operating in yawed conditions.
Improvements to the Eddy Viscosity Wind Turbine Wake Model
Authors: Gunn K 
Published: May 2019

Abstract
This paper presents improvements to the eddy viscosity wake model to significantly improve its fidelity without compromising its low computational cost. The eddy viscosity wind turbine wake model, proposed by Ainslie, has been a staple component of the wind yield toolchain for decades. Its low computational cost and excellent predictive power are likely to keep it as such for years to come. However, the standard implementations of the model rely heavily on several heuristics which, although well validated, may not scale well for large turbines or large windfarms.
In this paper, some non-physical heuristics are examined, and alternatives proposed which better reflect the underlying physics the model seeks to represent, which is shown to provide much better fidelity at no additional computational cost. The proposed model allows for better predictive capabilities of the performance of the next generation of offshore wind farms. The two key areas investigated are: first the impact of the ambient condition (TI, stability, …) on wake development; and second a re-examination of the wake combination method, leading to the inclusion of three additional processes in the model. It is shown that modifications to these areas provide a more verifiable wake model than the baseline implementations, and allow identification of the remaining physical processes to be further incorporated into future versions.
Unravelling the wind flow over highly complex regions through computational modeling and two-dimensional lidar scanning
Authors: Palma J.M.L.M. , Silva Lopes A. , Costa Gomes V.M. , Veiga Rodrigues C. , Menke R. , Vasiljević N. , Mann J. 
Published: May 2019

Abstract
Computational modeling and lidar scanning data of the atmospheric flow over a double-ridge (Perdigão) were used to study a 24-hour period on 14–15 May 2017 with a maximum wind speed of more than 6 ms−1. An influence of the stratification was observed throughout most of the time, in the form of a lee-wave triggered by the topography or flow separation further downstream of the ridge. The good agreement between the results obtained by lidar scanning and computational modeling increases our confidence in the use of either of these two techniques. See corresponding video at doi.org/10.11583/DTU.7863482.
Novel Aerodynamic Damping Identification Method for Operating Wind Turbines
Authors: Chen Chao , Duffour Philippe , Fromme Paul 
Published: May 2019

Abstract
This contribution introduces a novel method to determine the aerodynamic damping for operating wind turbines. Previous research typically estimated the modal damping ratios in the fore-aft and side-side directions as two decoupled degrees of freedom. This can result in misleading results, as the two directions are closely and unconventionally coupled through the wind-rotor interaction. This study proposes the identification of a novel type of aerodynamic damping matrix. This matrix arises from the linearization of the aerodynamic force resultant obtained from blade element momentum theory (blade modes not included). This linearized force is then applied to a beam finite element model of the tower with a lumped mass representing the rotor-nacelle assembly. This decoupled strategy efficiently describes the physics of the system including the coupling between the fore-aft and side-side motions. The identification of the damping matrix is shown to work for simulated wind time data.
Sub-seasonal to seasonal climate predictions for wind energy forecasting
Authors: Soret A , Torralba V , Cortesi N , Christel I , Palma Ll , Manrique-Suñén A , Lledó Ll , González-Reviriego N , Doblas-Reyes F J 
Published: May 2019

Abstract
Both renewable energy supply and electricity demand are strongly influenced by meteorological conditions and their evolution over time in terms of climate variability and climate change. However, knowledge of power output and demand forecasting beyond a few days remains poor. Current methodologies assume that long-term resource availability is constant, ignoring the fact that future wind resources could be significantly different from the past wind energy conditions. Such uncertainties create risks that affect investment in wind energy projects at the operational stage where energy yields affect cash flow and the balance of the grid. Here we assess whether sub-seasonal to seasonal climate predictions (S2S) can skilfully predict wind speed in Europe. To illustrate S2S potential applications, two periods with an unusual climate behaviour affecting the energy market will be presented. We find that wind speed forecasted using S2S exhibits predictability some weeks and months in advance in important regions for the energy sector such as the North Sea. If S2S are incorporated into planning activities for energy traders, energy producers, plant operators, plant investors, they could help improve management climate variability related risks.
Preliminary validation of ATOM: an aero-servo-elastic design tool for next generation wind turbines
Authors: Scott S , Macquart T , Rodriguez C , Greaves P , McKeever P , Weaver P , Pirrera A 
Published: May 2019

Abstract
Upscaling wind turbines has resulted in levelised cost of energy (LCoE) reductions. However, larger turbine diameters pose significant design challenges, often with conflicting requirements. For example, non-linear dynamics of aeroelastic tailored blades must be accurately predicted whilst, for the sake of efficient gradient-based design, it is also desirable to simplify the numerical definition of such blades—keeping design variables (DVs) to a minimum. This work presents and validates two features of the ATOM code (Aeroelastic Turbine Optimisation Methods), developed at the University of Bristol, that enable accurate and efficient modelling of large-scale wind turbine blades. Both an efficient parameterisation method and high-order beam elements illustrate the capacity for increasing the speed of gradient evaluations whilst accurately predicting blade dynamics—either by reducing DVs or simulation time. As a preliminary validation, aero-servo-elastic simulations from ATOM and an industry-standard software—DNV GL Bladed—are compared against field measurements gathered from an existing 7 MW turbine.
Wind tunnel setup for experimental validation of wind turbine control concepts under tailor-made reproducible wind conditions
Authors: Petrović V , Berger F , Neuhaus L , Hölling M , Kühn M 
Published: May 2019

Abstract
To speed up validation and prototyping of novel control and design concepts in wind energy, wind tunnel experiments should be used in synergy with numerical simulations and field experiments. The paper presents a wind tunnel setup consisting of a scaled wind turbine model MoWiTO and an active grid for generation of tailor-made and reproducible inflow conditions. To demonstrate that the presented experimental setup is suitable for fast validation of advanced control concepts, several control algorithms have been implemented and validated in various inflow conditions, such as turbulent and sheared inflows, and wind gusts. The tested control algorithms include the baseline collective pitch and torque control, individual pitch control for load reduction, and a control algorithms for compensation of static aerodynamic imbalances. All control algorithms resulted in an expected behaviour of the model wind turbine, thus emphasizing that the presented experimental setup can be used for fast and inexpensive testing of control concepts.
A Blade Load Feedback Control For Floating Offshore Wind Turbines
Authors: Olondriz Joannes , Jugo Josu , Elorza Iker , Alonso-Quesada Santiago , Pujana-Arrese Aron 
Published: May 2019

Abstract
The platform-pitch motions of Floating Offshore Wind Turbines are highly influenced by the blade-pitch controller. However, in rough sea state conditions, the platform-pitch motions are dominated by the incident wave dynamics. Then, the properties of the designed controller to reduce the platform-pitch motions can be changed due to the sea state conditions. In this study, the drawbacks of a previously designed Aerodynamic Platform Stabiliser controller performance in rough sea state conditions are analysed. Furthermore, an additional blade load feedback control loop has been designed to improve the performance of the controller in rough sea state conditions. The preliminary results presented here show the potential of the blade load feedback control loop effectiveness to improve the Aerodynamic Platform Stabiliser control loop performance in rough sea state conditions. The time-domain simulations were carried out with the NREL 5-MW wind turbine mounted on the ITI Energy’s barge in the fully coupled non-linear aero-hydro-elastic simulation tool FAST.
Pitch bearing lifetime prediction considering the effect of pitch control strategy
Authors: Lopez A , Zurutuza A , Olave M , Portugal I , Muñiz-Calvente M , Fernandez-Canteli A 
Published: May 2019

Abstract
Ambitious worldwide renewable energy targets are pushing for wind energy to become a mainstream power source. Pitch bearings are some of the most vulnerable components of wind turbines. Inside bearings, damage in the inner raceways is significant due to the rolling contact fatigue (RCF) caused by balls. It is well known that methodologies for RCF recommended by international standards are not suitable for fatigue cases where fatigue mechanism encompass multiaxiality, as well as the loading being non-proportional, leading to unnecessary design over-costs. The objective of this work is to develop a new accurate methodology to predict the lifetime of the raceway for a pitch bearing under RCF failure mode and analyse the effect of the pitch control strategy. This methodology will help both, the manufacturer of the bearing and the manufacturer of the turbine, to design a concept focused on the overall performance of the machine.
Optimised de-rated wind turbine response and loading through extended controller gain-scheduling
Authors: Galinos Christos , Urbán Albert M. , Lio Wai Hou 
Published: May 2019

Abstract
An increasing number of wind turbines are expected to be able to participate in the ancillary services that would normally be provided by conventional power plants, as the penetration of the wind energy in the electricity grid is increasing. Specifically, the turbines are needed to be able to control their active power based on the operator command. Constraining the possible output power, i.e. decreasing the power to less than the maximum or rated power, is therefore important for the wind turbine control system. When a turbine is operating under a de-rating strategy, the operating points of the turbine, i.e. the steady-state blade pitch and the tip speed ratio, change compared to the normal case and this needs to be considered within the controller design. Thus, this paper is to study the influence of the de-rating on the turbine controller gain-scheduling and its effect to power output and fatigue damage of the key turbine components. The results show that the wind turbine response is refined through tuning under the different down-regulation operation points, that translate into less fatigue damage of the key turbine components. For a typical multi-megawatt turbine, it is found that the main component lifetime damage can be reduced substantially. In numerical terms, there are up to 6.5% for the tower BM in fore-aft direction and 2.7% for the blade root flapwise direction, which can lead in a prolonged operational lifetime of the wind turbine.
Load analysis of special operation conditions and implementation of derived load states in Bearing Robustness Test (BRT)
Authors: Hirt A. , Jacobs G. , Neumann S. , Kock S. , Bosse D. 
Published: May 2019

Abstract
Premature bearing outages at the planetary and high speed shaft stage of gearboxes are responsible for long down time periods of wind turbines [1, 2]. In order to prevent premature bearing outages against certain failure mechanisms, a new robustness test procedure for original-sized WT gearbox bearings is developed within the project WT-Bearing Center.NRW. The BRT serves to qualify bearings for a damage-free operation over the entire service life [3]. It combines a fatigue load spectrum and also additional special load events [4]. This paper describes the analysis of wind turbine loads during different operation conditions and the definition of special load events, based on this analysis. The aim of including special loads to the BRT is to consider the complex real bearing loads within the test procedure as precisely as possible.
On wind turbine control for participation in grid frequency regulation
Authors: Elorza Iker , Calleja Carlos , Pujana-Arrese Aron 
Published: May 2019

Abstract
An energy mix with a large contribution from wind power requires wind farm participation in frequency regulation. To do this effectively, it is necessary for wind turbines to curtail their power production by a certain amount, or ‘delta’, which serves as a reserve. Although it is relatively straightforward to achieve this in certain conditions, doing so consistently normally requires wind speed observers to estimate available power. A delta control method is proposed here, which does not rely on said observers and naturally extends popular torque and pitch control algorithms.
Farm-wide assessment of wind turbine lifetime extension using detailed tower model and actual operational history
Authors: Kazemi Amiri A. , Kazacoks R. , McMillan D. , Feuchtwang J. , Leithead W. 
Published: May 2019

Abstract
Lifetime extension is receiving increasing attention because of ageing asset bases, the need for efficient use of capital budgets, and the optimistic lifetime assumptions used at the project design stage. Based on the industrial attention and the overall observable reduction in subsidies for new investments and repowering, especially in onshore wind energy, lifetime extension is expected to become essential in the future. This contribution presents a methodology for life extension assessment of individual onshore wind turbine towers, as the key structural components, using the joint aeroeastic-finite element analysis and taking account of wind directionality and stress magnification around the tower door. The results demonstrate that the spread in the wind rose provide the potential for tower lifetime extension, however, the stress concentration around the tower door and site-wide variations of wind characteristics have to be also taken into account. The outcomes of this paper indicates that the wind rose dispersion can also provide a lifetime extension potential in addition to a more benign weather and operational conditions.
Challenges of decommissioning offshore wind farms: Overview of the European experience
Authors: Topham Eva , Gonzalez Elena , McMillan David , João Elsa 
Published: May 2019

Abstract
In the coming years, an important number of offshore wind turbines will reach the end of their initially planned service life. In a wind turbine end-of-life scenario, owners can decide between extending the life of the asset, repowering the site or decommissioning. This decision-making process is affected by important sources of uncertainty, especially in offshore environments. The limited experience makes the decommissioning procedure challenging, as it is still largely unexplored. This work assesses the current state of knowledge about the challenges surrounding the decommissioning process of an offshore wind farm. The four main challenges encountered are identified and analysed in detail, namely the regulatory framework, the overall planning of the process, the logistics and vessels’ availability, and the environmental impacts confronted. Ultimately, this paper aims at stimulating the dialogue among stakeholders and raising the awareness of adequately regulating and preparing the upcoming decommissioning of offshore wind farms in Europe.
Increasing the Value of Offshore Wind by Integrating On-Board Energy Storage
Authors: Buhagiar D. , Sant T. , Farrugia R. N. , Farrugia D. 
Published: May 2019

Abstract
Energy storage technologies are considered a promising solution for overcoming one of the most pertinent hurdles to high renewable energy penetration: the mismatch between energy supply and consumer demand. The intermittent nature of variable renewable energy technologies at high penetration rates leads to a loss of value for each unit of energy produced. Generation-side energy storage can allow wind turbines to alter their generation strategies and derive additional value through improved market participation. On-board storage leads to more efficient use of space and a potential for cost reductions. In the present work, a brief review of existing work on these aspects was undertaken, followed by a time-series analysis of an offshore 6 MW wind turbine coupled to an energy storage system. The performance of the wind+storage system was simulated using one year of data from the Egmond aan Zee offshore wind farm site. A statistical analysis was undertaken to estimate the required charge/discharge cycles and establish the required storage capacity under different operating conditions. A lithium-ion battery was then considered as the competing energy storage technology, and a cumulative damage model was applied based on the depth-of-discharge characteristics. Findings indicate that despite their competitive capital costs, battery technologies would have a limited lifetime resulting from high charging/discharging cycles. A more viable approach in the long-term could be to opt for technologies that are less dependent on charge/discharge cycles and which have a lifetime that can match that of the wind turbine itself.
Optimized Energy Management Strategy for Wind Plants with Storage in Energy and Reserve Markets
Authors: González-Garrido Amaia , Villarreal Igor , Gaztañaga Haizea , Saez-de-Ibarra Andoni , Eguia Pablo 
Published: May 2019

Abstract
This paper addresses the joint operation of wind plants with energy storage systems in multiple markets to increase the value of wind energy from an economic and technical point of view. The development of an optimized energy management allows scheduling the wind generation in energy markets, as well as contributing to the system stability through the joint participation in frequency ancillary services. The market optimization maximizes market revenues considering overall storage costs, while avoiding energy imbalances and market penalties. Moreover, wind power fluctuations, forecast errors and real-time reserve requirements are controlled by the energy storage system and managed afterward through the participation in continuous intraday market. Furthermore, model predictive control approach enables a high compliance of reserve requirements and a huge reduction of energy imbalances in real-time operation. Different energy storage capacities are selected in order to evaluate their cost-effectiveness enhancing the wind plant operation under the considered study case.
Analysing Current Signature Data to Diagnose an In-Service Wind Turbine Generator
Authors: Artigao Estefania , Gonzalez Elena , Honrubia-Escribano Andres , Gomez-Lazaro Emilio 
Published: May 2019

AbstractCondition-based maintenance (CBM) is currently seen as the preferred approach to optimise operation and maintenance (O&M) strategies by the early detection and diagnosis of critical failures for wind turbines (WT). WT reliability is highly affected by failures of the mechanical components from the drive train, although doubly-fed induction generators (DFIG) also contribute to high failure rates and downtime. As DFIG is the dominant technology employed for variable speed WTs, dedicated failure detection and diagnosis techniques are required. Current signature analysis (CSA) has emerged as a powerful tool for this purpose, despite some limitations. In this work, the variability of CSA through time by means of spectra waterfall and the wavelet transform are investigated to overcome these limitations. The analysis of a faulty in-service WT DFIG presented in this work raises the usefulness of the suggested approaches to identify patterns related to failure development through time.
A Novel Probabilistic Long-Term Fault Prediction Framework Beyond SCADA Data - With Applications in Main Bearing Failure
Authors: Herp Jürgen , Pedersen Niels L. , Nadimi Esmaeil S. 
Published: May 2019

Abstract
Prognostic and health monitoring addresses the issue of detecting faults and monitoring the current state of a wind turbine. Details about the fault’s progression, and from there, the remaining useful lifetime, are key features in monitoring and industrial operation and maintenance planning. In order to avoid increase in operation and maintenance cost, as well as subjective human involvement, we present an online and automated monitoring framework for prediction of the remaining useful lifetime based on deep learning models. This framework includes training and re-training of predictive models with minimal oversight by the operators.
Further, we explore the dependency of various models’ predictive abilities based on the input variables available, such as SCADA and secondary measurements. Especially deep learning approaches, such as neural networks, benefit greatly from the volume of data that can be extracted from modern-day turbines. This work utilizes upon the volume of data to present a case study on main bearing failures for 108 turbines. In the presented setting, predictions of the remaining useful lifetime of more than 90 days can be expected on average, outperforming the closest state-of-the-art estimate by almost a factor of two on average.