Ambitious offshore wind energy targets in the North Sea necessitate innovative solutions for efficiently delivering energy to onshore demand locations. Wind-to-hydrogen systems offer a promising pathway, with three archetypes of system configurations: centralized onshore electrolysis (C-ON), centralized offshore electrolysis (C-OFF), and decentralized offshore electrolysis at each wind turbine (D-OFF). This study introduces a high-resolution, time-dependent simulation framework capable of analyzing offshore wind-to-hydrogen systems with a focus on operational dynamics and comprehensive cost estimation. The framework enables detailed analysis of D-OFF, capturing its unique dynamics driven by direct connections to individual wind turbines, including the impacts of dynamic operation. A comprehensive system analysis, spanning from the wind farm to the hydrogen offtaker, reveals a wide cost range, with Levelized Cost of Hydrogen (LCOHs) ranging from 3.0 to 10.5€/kgH₂ post 2030. Among the different scenarios analyzed, C-OFF with proton exchange membrane electrolysis achieves the lowest LCOHs due to a reduced need for offshore electrical infrastructure, economies of scale, and efficient dynamic operating characteristics. D-OFF with alkaline electrolysis incurs the highest costs and faces operational challenges, such as electrolyzers shutting down when they occasionally fail to reach the minimum load thresholds, lowering hydrogen production. We illustrate the trade-offs between system configurations’ cost, production rate, and electrolyzer stack lifetime across configurations. Insights from this study can be utilized as a starting point for informed decision-making for large-scale wind-to-hydrogen deployment in the Dutch North Sea region.

While modern wind turbines have become by far the largest rotating machines on Earth with further upscaling planned for the future, a renewed interest in small wind turbines (SWTs) is fostering energy transition and smart grid development. Small machines have traditionally not received the same level of aerodynamic refinement as their larger counterparts, resulting in lower efficiency, lower capacity factors, and therefore a higher cost of energy. In an effort to reduce this gap, research programs are developing worldwide. With this background, the scope of the present study is 2-fold. In the first part of this paper, an overview of the current status of the technology is presented in terms of technical maturity, diffusion, and cost. The second part of the study proposes five grand challenges that are thought to be key to fostering the development of small wind turbine technology in the near future, i.e. (1) improving energy conversion of modern SWTs through better design and control, especially in the case of turbulent wind; (2) better predicting long-term turbine performance with limited resource measurements and proving reliability; (3) improving the economic viability of small wind energy; (4) facilitating the contribution of SWTs to the energy demand and electrical system integration; (5) fostering engagement, social acceptance, and deployment for global distributed wind markets. To tackle these challenges, a series of unknowns and gaps are first identified and discussed. Based on them, improvement areas are suggested, for which 10 key enabling actions are finally proposed.

Simulation methods ensuring a level of fidelity higher than that of the ubiquitous Blade Element Momentum theory are increasingly applied to VAWTs, ranging from Lifting-Line methods, to Actuator Line or Computational Fluid Dynamics (CFD). The inherent complexity of these machines, characterised by a continuous variation of the angle of attack during the cycloidal motion of the airfoils and the onset of many related unsteady phenomena, makes nonetheless a correct estimation of the actual aerodynamics extremely difficult. In particular, a better understanding of the actual angle of attack during the motion of a VAWT is pivotal to select the correct airfoil and functioning design conditions. Moving from this background, a high-fidelity unsteady CFD model of a 2-blade H-Darrieus rotor was developed and validated against unique experimental data collected using Particle Image Velocimetry (PIV). In order to reconstruct the AoA variation during one rotor revolution, three different methods-detailed in the study-were then applied to the computed CFD flow fields. The resulting AoA trends were combined with available blade forces data to assess the corresponding lift and drag coefficients over one rotor revolution and correlate them with the most evident flow macro-structures and with the onset of dynamic stall.