Gamesa (Spain)

The rapid growth of large-scale wind power plants (WPPs) and other inverter-based resources (IBRs) is significantly transforming and impacting power system design and operation, introducing new complexities and challenges. In this context, high-fidelity models that replicate the electrical behaviour of the actual plant are critical to ensuring secure and stable grid operation, increasing the demand for validation of electrical models against the actual component. Although validation techniques for grid-following (GFL) wind turbines (WTs) are well established, grid-forming (GFM) technology introduces functionalities that current validation practices may not fully address. Therefore, it is necessary to assess to what extent GFL validation techniques are suitable to validate GFM technology. This paper reviews the requirements of grid codes, standards, and expert groups on validating WT and WPP simulation models, outlines the WT test setups used in practice, and presents the validation methodologies currently used to assess the accuracy of models. The paper finally discusses the few recent proposals on the validation of GFM WT models and aims to bridge the methodological gap between existing validation practices and the validation of emerging GFM capabilities, offering a foundational perspective for original equipment manufacturers (OEMs), transmission system operators (TSOs) and industry working groups to shape future validation frameworks for GFM controls in WTs.

<strong class="journal-contentHeaderColor">Abstract.</strong> Non-destructive inspection (NDI) is useful in the industrial sector to ensure that manufacturing follows defined specifications, reducing the quantity of waste and thereby the cost of production. Optical Coherence Tomography (OCT), a well-known diagnostic technique in medical and biological research, is increasingly being used for industrial NDI. In the mid-infrared (MIR) wavelength range, OCT can be used to characterise parts and defects not possible by other industry-ready scanners, and enables better penetration than conventional near-infrared OCT. In this article, we demonstrate NDI of wind turbine blade (WTB) coatings using an MIR OCT scanner employing light around 4 <em>&micro;</em>m from a supercontinuum laser source. We inspected the top two layers of the coating (topcoat and primer) in two different samples. The first is to determine the maximum penetration depth, and the second one is to imitate defect identification. The results of our study confirm that MIR OCT scanners are promising for coating inspection and quality control in the production of WTBs, with performance parameters not achievable by other technologies.

Accurate knowledge of the mechanical loads of wind turbine gearboxes has become essential in modern, highly loaded gearbox designs, as maintaining or even improving gearbox reliability with increasing torque density demands is proving to be challenging. Unfortunately, the traditional method of measuring dynamic mechanical torque using strain gauges placed on the outer surface of a rotating shaft and transmitting the resulting signal is unsuitable for serial deployment due to technical and economic constraints. An alternative method based on fiber-optic strain sensors placed on the stationary outer surface of the gearbox ring gear has been proposed. Like shaft torsion, the radial deformation of the ring gear is proportionate to the rotor torque. Placing the sensors on a stationary component is a cost-effective alternative for serial implementation because the need for complex and expensive data transfer via wireless transmission or a slip ring is eliminated. In this paper, we present the results of an extensive field experiment conducted to evaluate the torque measurement accuracy of this novel sensing solution installed on the gearbox of a Gamesa G97 2-MW wind turbine at the National Renewable Energy Laboratory's Flatirons Campus. Torque measurements derived from fiber-optic strain sensors placed on the ring gear of the planetary stage are compared to conventional torque measurements from strain gauges placed on the main shaft. Two different torque estimation data processing methods were evaluated, with the method based on operational deflection shapes providing the most accurate results with an average normalized root mean square error below 0.7% for a load revolution distribution analysis. The effect of operating conditions on the torque estimate was also investigated, and the third planet-passing operational deflection shape was found to be the least sensitive to nontorque load-related effects. The fiber-optic strain sensors' successful operation during the complete test campaign has demonstrated a robust and accurate solution for fleet-wide enhanced gearbox remaining useful life estimation.

Abstract Background Infective endocarditis (IE) is a life-threatening condition with high in-hospital mortality rates. In recent decades, the implementation of endocarditis teams has been proposed as a multidisciplinary approach to improve patient outcomes. Our aim was to evaluate prognosis over a fifteen-year period in a national cohort. Methods Our data come from the Spanish endocarditis registry. We included 6525 patients diagnosed with IE between 2008 and 2022. Clinical characteristics, complications, and mortality rates were compared in four periods (2008-2011, 2009-2014, 2015-2017, 2018-2022). Results We found a worsening of the clinical profile during the four periods, with an increase of median age (68-69-69-70 years, p=0.007), age-adjusted Charlson comorbidity index (4-5-5-5, p &amp;lt;0.001), prosthetic valve IE rate (29-31-32-33%, P=0.029) and intracardiac complications rate (27-30-37-38%, p&amp;lt;0.001), and a decrease in the rate of cardiac implantable electronic devices infections (11-11-9-8%, p=0.012). However, the rate of surgical interventions increased (45-45-49-51%, p&amp;lt;0.001) and the median number of days from diagnosis to surgery decreased (12-10-9-9. P=0.001). Inhospital death decreased in the overall population (27-25-25-23%, p=0.037) and in high risk patients as those aged 70-77 years (31-32-28-23, p=0.04), ≥78 years (36-33-34-30, p=0.07), Charlson index ≥7 (38-39-38-31, p=0.02), treated with surgery (22-21-18-18, p=0.02), and prosthetic valve IE (32-27-30-25, p=0.001). One-year mortality also decreased (36-35-33-28%, p=0.008). Year period was an independent risk factor for inhospital mortality (odds ratio 0.97, 95% confidence interval 0.95-0.98, p &amp;lt;0.001) and one-year mortality (hazard ratio 0.93, 95% confidence interval 0.88-0.99, p=0.016) Conclusions Despite a worsening clinical profile, IE inhospital and one-year mortality seem to be decreasing. The introduction of endocarditis teams and an increase in surgical interventions might contribute to this better prognosis. Our findings suggest that adopting a multidisciplinary team approach could be a critical strategy in improving outcomes for patients with IE.

This paper presents a physics-informed hybrid analytical-empirical model for gallium nitride high electron mobility transistors (GaN-HEMTs), implemented in MATLAB for transient and frequency-domain simulations. The model unifies three dominant physical mechanisms: (i) dynamic drift velocity based on the momentum balance (MB) equation, (ii) nonlinear parasitic effects via gate/drain RC trap subcircuits, and (iii) thermal feedback using temperature-dependent mobility and threshold voltage. Unlike compact or black-box models, this framework requires no proprietary measurements. Simulation results demonstrate critical phenomena such as gate-lag, current collapse, and dynamic Ron degradation. The model predicts up to 18% drain current reduction under thermal stress and 22% increase in on-state resistance during switching due to parasitic and thermal effects. A frequency-dependent phase lag of the drift velocity caused by carrier inertia is also observed. The proposed MATLAB-based model supports device/circuit co-simulation and is suitable for high-frequency GaN converter applications.

Abstract. With the number of commissioned and planned wind farms increasing rapidly, analysing wind farm cluster wakes becomes essential for resource assessment and lifetime considerations. Cluster wakes influence wind turbine power in downstream wind farms in certain meteorological situations. Our objective is to ascertain whether far-reaching cluster wakes (15 to 21 km) impact individual turbine loading in a downstream wind farm, considering the influence of atmospheric stratification. We utilized supervisory control and data acquisition (SCADA) data from an offshore wind farm and accelerometer measurements as the load proxy in the absence of load measurements to check short-term fatigue loading effects. We compared the absolute values of relevant SCADA variables of turbines in and out of the cluster wake. We found that while cluster wakes increase fluctuations of rotor speed and power, the load effects were lower than from turbines in the free wind, primarily due to lower wind speeds. We developed a new methodology to quantify loads of turbines affected by the cluster wake while separating the dependency of loads on the inflow wind speed. The turbines within the cluster wake showed a small increase in the load effects (≈2.5 %) when compared to turbines in free wind, but lower than loads of turbines within the wind farm affected by inner-farm wakes (both at the same local inflow wind speeds). We also found atmospheric stratification and the inflow wind speed to have no impact on the magnitude of loads within the cluster wake. Additionally, we found no additional blade mode excitations due to the presence of the cluster wake from the analysis of load spectra. We conclude that wind turbines affected by cluster wakes have a marginal increase in loads when compared to reference conditions in undisturbed inflow. The absolute load effects in the cluster wake are lower due to the lower wind speeds. We propose the use of additional data from load sensors to further determine possible lifetime fatigue effects of cluster wakes on offshore wind turbines. These new insights can potentially add to the design standards of future wind farm clusters.

As the European countries strive to meet their ambitious climate goals, renewable hydrogen has emerged to aid in decarbonizing energy-intensive sectors and support the overall energy transition. To ensure that hydrogen production aligns with these goals, the European Commission has introduced criteria for additionality, temporal correlation, and geographical correlation. These criteria are designed to ensure that hydrogen production from renewable sources supports the growth of renewable energy. This study assesses the impact of these criteria on green hydrogen production, focusing on production costs and technology impacts. The European energy market is simulated up to 2048 using stochastic programming, applying these requirements exclusively to green hydrogen production without the phased-in compliance period outlined in the EU regulations. The findings show that meeting the criteria will increase expected system costs by €82 billion from 2024 to 2048, largely due to the rapid shift from fossil fuels to renewable energy. The additionality requirement, which mandates the use of new renewable energy installations for electrolysis, proves to be the most expensive, but also the most effective in accelerating renewable energy adoption. • Analyzes new EU green hydrogen regulations using the EMPIRE optimization model. • Green hydrogen regulations could increase system costs by €82 billion from 2024 to 2048. • Most of the cost increases due to new renewable investments in the coming decade. • Using existing renewable capacities for green hydrogen can cut costs. • More electrolyzers are needed to adapt to renewable availability for green hydrogen.

In a collaborative project between Siemens Gamesa Renewable Energy and the National Renewable Energy Laboratory (NREL), a cost-effective method to measure dynamic main shaft torque and the influence of non-torque loads was applied to the gearbox of the Gamesa G97 2-megawatt (MW) wind turbine at the NREL Flatirons Campus and verified through a field test campaign that took place in 2023. The method involved the installation of fiber-optic sensors on the ring gear of the gearbox. Additionally, traditional strain gauges and a rotary encoder were installed on the main shaft to measure mechanical torque and orthogonal bending moments. We compare the measured total main shaft bending moments from the field test campaign to those predicted by an updated OpenFAST model of the G97 wind turbine for similar environmental conditions. We also assessed the sensitivity of the predicted bending moment to varying levels of turbulence intensity, shear exponent, and yaw error.