ABSTRACT Proton electrolyte membrane (PEM) water electrolyzers (WE) represent a pivotal technology for the electrochemical production of hydrogen. However, a persistent challenge is the loss of efficiency and performance, along with a shortened lifetime caused by degradation of the materials in PEMWE. This review examines the degradation mechanisms of PEMWE components, including the electrolyte membrane, catalyst layers, porous transport layers, bipolar plates, and gaskets. Furthermore, it places particular emphasis on measurement techniques used to examine and differentiate the degradation mechanisms, including a discussion of less‐studied mechanisms and measurement methods. A survey was conducted among PEMWE experts to analyse prevailing opinions on the severity and frequency of different degradation mechanisms. It supplements the literature review and allows for a comprehensive understanding of the impacts of degradation.
Abstract The development and design of renewable energy systems relies on system simulations to evaluate constantly changing environments and new requirements. This can require the extension or development of new simulation models, which is a time consuming effort, making reusing models desirable. However, this flexibility is not always given in existing tools. Co-Simulation provides a technique to overcome these issues, but it has not been applied yet for aero-elastic simulation of wind farms. This study investigates how co-simulation techniques can be applied to create modular simulations of wind farms. We utilize functional mock-up units as a model base to wrap existing models as components for a wind farm simulation framework, which we call farmQSim. Additionally, a continuously generating wind model is used to remove the necessity of a precursor wind generating model. The wind farm co-simulation approach shows a good match with results from FAST.farm and allows for flexible setup of simulation. Models of different complexity can be combined into a single simulation case to decrease simulation time while achieving comparable results. Overall, co-simulation has been proven to be suitable for wind farm simulations and therefore enables reusability of simulation models and provides extensibility of the simulation cases.
Abstract Accurate, manufacturer-independent assessment of wind turbine performance remains a key challenge with direct implications for energy yield, as conventional power-curve analyses are often biased by uncertainties in nacelle-mounted wind measurements. This paper presents an anomaly detection framework developed within the WindKI research initiative, which aims to improve wind turbine performance diagnostics using data-driven methods. The proposed framework combines multiple unsupervised anomaly detection models with a rank-based ensemble strategy to identify statistically unusual operating behavior without requiring labeled training data or turbine-specific tuning. The approach is evaluated using the CARE dataset, comprising predefined normal and anomalous events from three wind farms. Results show consistent prioritization of anomalous events across sites, with ROC–AUC values of approximately 0.8, indicating robust performance despite the unsupervised setting. The framework provides a scalable foundation for diagnosing underperformance and investigating potential failure modes in wind energy assets.
Abstract As wind turbine drivetrains grow in scale and complexity, the practice of full-scale testing has become expensive and logistically demanding. These challenges are inducing a significant shift in the wind energy industry, potentially propelling scaled testing from a specialized academic pursuit into a widely adopted method. While scaled testing has a well-established history in the analysis of the structural integrity of wind turbine components and the aerodynamic performance, its application to drivetrain systems is a recent but expanding field. This paper reviews state-of-the-art scaled testing methods for wind turbine drivetrain components. It addresses recent developments, and the ongoing efforts of standardized scaled testing methods for wind turbine drivetrains. Considering the research and case studies presented in this paper, it is projected that scaled testing will become an integral and essential part of the design, validation, and optimization processes for future wind turbine drivetrain systems.
Abstract A large comparison exercise has been performed featuring aerodynamic and aero-elastic simulation cases on the IEA 15MW reference wind turbine in various conditions, containing results of 30 codes ranging from BEM to CFD. More than 10 different variable types ranging from lifting line variables to pressures, loads and velocities have been compared for the different conditions, resulting in many comparison plots. The result is a unique insight in the current status and accuracy of rotor aerodynamic modeling. Although there are no measurements on this turbine, mutual comparison of model results provided useful insights into the performance of rotor aerodynamic models. Preparatory simulations on the 15MW RWT at constant uniform conditions generally showed reasonable agreement in the aerodynamic response between engineering and higher-fidelity models, provided the turbine was considered rigid. However, including flexibility effects led to more discrepancies, largely due to differences in blade torsion, which in turn impacts the aerodynamics. Even at very moderate wind speeds the blade tip torsion angle could be in the order of 2 degrees where large differences were found between the partners results. Following the preparatory cases, simulations under turbulent conditions were performed. Several turbulent boxes were generated using high-fidelity CFD models and the results were compared mutually. Some differences appeared in the turbulent boxes, which could be expected from convection differences. At first sight the differences seemed small. However, when the boxes were fed into an aero-elastic code, the differences became significant enough to affect load response. When supplying the sampled wind speeds from the turbulent box as input to engineering-fidelity models, it was interesting to find that these models showed a much higher standard deviation in loads compared to higher-fidelity models. This confirms the finding from previous numerical studies that engineering models tend to overpredict fatigue loads, also for a large sized rotor.
