Energies

In the context of the zero-carbon transition, this article provides a comprehensive review of Organic Rankine Cycle (ORC) technologies for low-grade heat recovery and conversion to power. It surveys a wide range of renewable and waste heat sources—including geothermal, solar thermal, biomass, internal combustion engine exhaust, and industrial process heat—and discusses the integration of ORC systems to enhance energy recovery and thermal efficiency. The analysis examines various configurations, from basic and regenerative cycles to advanced transcritical and supercritical designs, cascaded systems, and multi-source integration, evaluating their thermodynamic performance for different heat source profiles. A critical focus is placed on working fluid selection, where the landscape is being reshaped by stringent regulatory frameworks such as the EU F-Gas regulation, driving a shift towards low-GWP hydrofluoroolefins, natural refrigerants, and tailored zeotropic mixtures. The review benchmarks ORC against competing technologies such as the Kalina cycle, Stirling engines, and thermoelectric generators, highlighting relative performance characteristics. Furthermore, it identifies key trends, including the move beyond single-source applications toward integrated hybrid systems and the use of multi-objective optimization to balance thermodynamic, economic, and environmental criteria, despite persistent challenges related to computational cost and real-time control. Key findings confirm that ORC systems significantly improve low-grade heat utilization and overall thermal efficiency, positioning them as vital components for integrated zero-carbon power plants. The study concludes that synergistically optimizing ORC design, refrigerant choice in line with regulations, and system integration strategies is crucial for maximizing energy recovery and supporting the broader zero-carbon energy transition.

Large-scale vertical-axis wind turbines (VAWTs) have potential applications in the oceanic environment due to their ease of installation and maintenance. Most research has focused on the aerodynamic enhancement of VAWTs; however, controlling the structural vibration of a VAWT supported by a floating platform has seldom been addressed in previous work. In this paper, four optimized structures are proposed to passively mitigate the dynamic response of a 5 MW floating VAWT subjected to high wind speeds (25 m/s) and combined platform motions (pitch and surge). Computational fluid dynamics (CFD) was used to calculate the wind loads, while the wave loads were represented by accelerations applied to the bottom of the turbine. The dynamic responses of the original and optimized models were comprehensively compared. The results show that the optimized models effectively reduce vibration by shifting the blade swing and flapping modes to higher frequencies. Specifically, the model incorporating brace struts, cables, and spring-damping units demonstrates the highest damping efficiency, reaching 96.83% for the y-direction displacement at the blade tip.

An efficient and reliable heat dissipation system is essential for the safe and stable operation of high-power water-cooled couplers. However, thermal analysis methods accounting for the centrifugal effects on coolant flow remain limited. This paper presents a high-accuracy equivalent thermal network model (ETNM) for analyzing the temperature distribution in water-cooled permanent magnet couplers (WPMCs), based on fluid–structure interaction and rotational centrifugal flow-field inversion. First, the ETNM is established based on key assumptions. Subsequently, an eddy current loss calculation method based on permanent magnet mapping is proposed to accurately determine the heat source distribution. The convective heat transfer coefficient of the coolant is then precisely derived by inverting the flow field obtained from fluid–structure coupling simulations under rotational centrifugal conditions. Finally, the model is applied for temperature analysis, and its accuracy is verified through both finite element simulations and experimental tests. The calculated results show errors of only 3.2% compared to numerical simulation and 5.6% compared to experimental data, indicating strong agreement of the proposed thermal analysis method. The accuracy of copper conductor (CC) temperature prediction is improved by 32.73%, and that of permanent magnet (PM) prediction by 33.33%. Furthermore, this method enables accurate estimation of individual component temperatures, effectively preventing operational failures such as PM demagnetization, CC softening, and severe vibrations caused by overheating.