renewable energy developers

Abstract: A piezoelectric transducer embedded in a pitch-plunge aerofoil with a finite-mass trailingedge flap converts the limit-cycle oscillation that follows flutter into electrical power. The design findings for such a harvester have so far been obtained with incompressible strip theory, whose aerodynamic state is a handful of lag variables. Here the same section, the same transducer and the same test cases are coupled instead to the two-dimensional compressible Euler equations, giving a full-order model of twelve thousand states, and the two aerodynamic models are placed side by side on the flutter boundary, on the limit cycle and on the harvested power, with the strip-theory results compared against higher fidelity aerodynamic modelling provided by CFD. The degree of freedom carrying the transducer remains the first-order design variable, and the ranking of the mountings is unchanged and wider, while strip theory is found to under-predict the harvested power of the compressible section and to overstate the effect of the transducer on stability where the electrical time constant meets the flutter frequency. A nonlinear reduced model of four states, built on eigenvectors of the coupled Jacobian at the velocity of interest, reproduces the frequency of the cycle, its pitch amplitude, the transducer voltage and the mean power, and misstates the proportion of plunge to pitch in the orbit and its phase. That error is shown to be independent of the amplitude of the cycle and to survive enlargement of the basis, which places it in the retained subspace rather than in the order of the expansion, and suggests that such models should be judged on the shape of the orbit rather than on a single amplitude.

Abstract: The rapid expansion of artificial intelligence is transforming data centres into one of the world's fastest-growing sources of electricity demand. As AI systems scale in size and capability, the physical infrastructure supporting computation is approaching critical limits in energy availability, cooling capacity, land use, freshwater consumption, and carbon management. Conventional land-based data centres are increasingly constrained by urban land competition, grid congestion, environmental pressures, and lengthy permitting processes, raising fundamental questions about where future computing infrastructure can sustainably exist. This article examines floating and offshore data centres as an emerging alternative model for digital infrastructure. By relocating computation to marine environments, offshore systems can exploit the ocean's natural cooling capacity, reduce freshwater dependence, and enable direct integration with offshore renewable energy resources such as wind, wave, and tidal power. Early deployments have demonstrated the potential for significantly improved energy efficiency and operational reliability compared with conventional facilities, while also opening new possibilities for distributed and resilient computing architectures. The article explores how offshore computing may reshape the future relationship between electrification, renewable energy, and large-scale AI infrastructure. It analyses the opportunities and trade-offs associated with marine deployment, including environmental impacts, engineering design challenges, economic feasibility, and regulatory governance. Rather than treating offshore data centres as experimental novelties, the article presents them as part of a broader systems-level transition in how society may power, cool, and sustain the next generation of computational growth.