Narec, since 2014 known as the National Renewable Energy Centre, is a part of the Offshore Renewable Energy (ORE) Catapult, a British technology innovation and research centre for offshore wind power, wave energy, tidal energy and low carbon technologies. ORE Catapult's head office is in Glasgow, Scotland. The centre operates multi-purpose offshore renewable energy test and demonstration facilities. It is similar to other centres, such as NREL in the US and National Centre for Renewable Energies [es] (CENER) in Spain. The National Renewable Energy Centre is based in Blyth, Northumberland..
Global-to-local load transfer remains a critical – yet largely unstandardized – step in the structural assessment of floating structures. This paper presents the results of package WP2.2 from the OC7 project Phase II, which establishes a cross-industry benchmark for the workflows connecting global performance analysis (based on integrated loads analysis, ILA) and the local structural assessment (based on finite-element analysis, FEA). The study evaluates a spectrum of industry practices, including sequential approaches with the FEA following the ILA, fully integrated time-domain approaches with hydro-structural coupling, and simplified ILA-only approaches. Using the VolturnUS-S reference semi-submersible, the models were first harmonized through mass and inertia, static, and modal verifications. Structural responses were then compared across three primary scenarios: topside-only excitation, irregular waves, and combined wind and wave loading. The results establish a structured comparison framework, highlighting how specific modelling choices and load transfer techniques directly influence confidence in design processes. The findings offer practical guidance to reduce uncertainty in “global-to-local” design workflows.
Offshore wind turbines operate in a complex air-sea environment where surface waves can modulate the atmospheric boundary layer and alter turbine inflow conditions. Although previous studies have shown that the wind-wave interaction may influence power production and wake dynamics, its impact on blade-scale fatigue loading is not sufficiently understood, particularly under fully coupled flow conditions. This work investigates the effect of wind-wave interaction on the fatigue performance of offshore wind turbine blades using a two-phase numerical framework, explicitly resolving the wind-water interaction. A 10 MW reference offshore wind turbine is modelled using the Actuator Line Method, while the Volume of Fluid approach is employed to capture the free surface, allowing for the interaction between the wind, the waves, and the turbine. Numerical simulations are performed on rated wind conditions for a range of regular sea states with increasing severity. The resulting inflow characteristics, blade loads, and damage equivalent loads are analysed. The results show that the wind-wave interaction has a negligible effect on the mean inflow velocity and average power production. However, wave induced modulation introduces significant unsteadiness in the flow, leading to increased variability in blade root loads Spectral analysis reveals additional load components associated with the wave frequency and the bladepassing frequency. Fatigue analysis indicates that while mild sea states have a limited or slightly beneficial impact, severe sea states can increase equivalent blade damage loads by up to approximately 20%. These findings highlight the importance of accounting for the wind-wave interaction in offshore wind turbine fatigue assessments.
The ASTERIx-CAESar project investigates a novel hybrid CSP-CAES concept and implements a small-scale prototype at CIEMAT-PSA in the south of Spain. This document gives a complete overview of the prototype and its components, including the volumetric solar receiver, the compressed air storage system, the hot air turbine, as well as the connected Reverse Osmosis (RO) desalination unit. The prototype is currently under construction and is planned to be operational at the end of 2026.
To improve the sustainability and economic viability of concentrated solar thermal energy systems, this study proposes a cooling system that combines wet and dry cooling technologies. The effectiveness of this novel cooling solution relies on optimal operation strategies that balance water and electricity use under constrained water availability. To address this challenge, a two-stage optimization framework is proposed. In the first stage, a sequence of multi-step optimization problems is solved to generate Pareto fronts representing trade-offs between resource consumption. In the second stage, these fronts are traversed through a path-search algorithm that minimizes the cumulative cooling cost over the optimization horizon. This work focuses on the first stage by comparing two methodologies for obtaining Pareto fronts: (i) an exhaustive search across the entire operating range and (ii) a reinforcement learning agent. The results show that the latter significantly reduces computational time, which is particularly advantageous given the long operational lifetime of such plants, while maintaining a comparable solution quality.
Accurate knowledge of flux distribution in solar tower plants is essential for maximizing its efficiency, especially in high-flux applications such as solar fuel production. This work presents a simulation-based approach to efficiently generate flux maps by creating a pre-computed database with a minimal set of sun positions. This strategy significantly reduces computational costs while maintaining low error levels through interpolation paving the way for real-time aiming strategy calculations. Four interpolation methods are compared to identify the most accurate for optimizing aiming strategies and improving solar field performance. The result optimal method combines 220 precomputed flux maps with barycentric interpolation, achieving an error below 3% for elevation angles above 18°.
