The pod propulsion systems are extensively used in polar ice-class ships to enhance manoeuvrability and propulsion efficiency. This study investigates the thermal-fluid-solid coupled dynamic performance of non-contact end-face seals under polar low-temperature conditions. Steady and dynamic fluid film models considering temperature-dependent seawater viscosity and density were developed based on the compressible Reynolds equation, and thermal-mechanical deformation of the seal structure was analyzed using the finite element method. Results show that low-temperature-induced thermal deformation reduces the fluid film thickness by approximately 13%, significantly affecting stiffness and damping. With decreasing temperature, the increasing seawater viscosity leads to enhanced principal stiffness coefficients but slightly reduces the damping coefficient, improving seal rigidity while weakening energy dissipation. Higher rotational speeds markedly improve both stiffness and damping, while greater pressure difference enhance damping—especially axial damping—thereby stabilizing the fluid film. Overall, the seal demonstrates superior dynamic stiffness and stability under low temperatures, high speeds, and moderate-to-high pressure differences. This work provides theoretical insights into optimizing structure and enhancing operational adaptability of end-face seals in polar pod propulsion systems.

Underwater vehicles navigating through water generate accompanying nonlinear hydrodynamic phenomena around their structures, such as vortices and form distinct wake characteristics behind them which can be detected and exploited. Therefore, modifying the connecting surfaces between the main body and the tail appendages of underwater vehicles is significant for enhancing their performance. This study innovatively proposes a fillet-shaped control surface between the tail appendage and the hull body. A series of discussions were conducted to examine the changes in the turbulent kinetic energy of the wake behind the vehicle as the fill ratio of the fillet-shaped control surface, the navigation speed and the submersion depth vary. Thereby, the influence of the fillet-shaped control surface on the hydrodynamic performance of the underwater vehicle is revealed. The results indicate that adding a fillet-shaped control surface between the main body and the tail appendage alters the pressure distribution around the underwater vehicle, consequently affecting the turbulence intensity of the wake flow. Further research shows that the turbulent kinetic energy in the wake flow of the underwater vehicle decreases significantly by approximately 57% when the height of the fillet-shaped control surface is full of the original value. Additionally, the addition of the fillet-shaped control surface reduces vortex generation and the turbulence intensity of the wake. This study provides a novel approach for improving the flow field of underwater vehicles.

Wind and solar energy curtailment is seen as one of the most important power system issues in multiple countries, and it will grow in importance for electricity systems that are targeting high shares of renewable energy. International cooperation, under the scheme of the International Energy Agency's (IEA) TCP (Technical Cooperation Programme) Wind Task 25 (Design and operation of energy systems with large amounts of variable generation) and its continuation task, Task 63 (Twenty Fifty Integration of Variable Energy), as well as Tasks 14 (Solar PV in the 100% RES Power System) and 19 (Photovoltaic Integration in Electricity Networks and Markets) of the Photovoltaic Power Systems (PVPS) Programme, have been investigating the global situation of wind and solar curtailment for more than a decade. This joint paper includes four topics: (1) proposing unified curtailment statistics, (2) rethinking and redefining curtailment, (3) updating statistics in various areas / countries, and (4) surveying and summarising future curtailment estimates in various country/areas. Specifically, the paper reviews previous publications and discussions on curtailment and rethinks the definition of curtailment. The paper also makes recommendations to governments, regulators and system operators around the world for uniform statistics on curtailment.

Short-term electricity price forecasting (STEP) plays a pivotal role in ensuring the stability and economic efficiency of modern power markets, especially under conditions of high volatility and increasing renewable penetration. However, existing models fail to adequately capture extreme price spikes, hierarchical periodic structures, and the dynamic impact of exogenous variables. To overcome these challenges, we propose Fourier-EPNet, a novel deep learning framework that integrates frequency-domain attention with multimodal variable fusion. Specifically, it features: (i) a Fourier Softmax attention mechanism, which extracts dominant periodic signals while suppressing high-frequency noise; and (ii) an exogenous-endogenous cross-attention module, which dynamically aligns historical price trends with forward-looking external drivers such as load and wind forecasts. Extensive experiments on five benchmark datasets (NP, PJM, BE, FR, DE) from the EPF corpus show that Fourier-EPNet consistently surpasses state-of-the-art baselines, achieving 49.5% lower MSE and 40.4% lower MAE on average. Ablation studies and theoretical visualization further validate the contribution and interpretability of each component. Overall, Fourier-EPNet offers a robust, interpretable, and generalizable solution for real-world electricity price forecasting, setting a strong foundation for intelligent energy market decision-making.

This paper presents a system-wide approach for contingency severity screening intended as a practical and scalable precursor to full dynamic security assessment (DSA). DSA is the standard practice used by Transmission System Operators (TSOs) to ensure that power systems remain stable following disturbances, with key variables—such as voltage, frequency, and thermal loading—kept within defined dynamic performance limits. However, applying DSA comprehensively across all credible contingencies and operating points is prohibitive, making a pre-screening stage indispensable. Commonly used static-security filters offer limited insight to transient dynamics, motivating the development of alternative screening strategies. To support early-stage analysis and prioritization, three static indicators are devised as proxies for dynamic behaviour, grounded in the power–angle characteristics determining transient stability. For eachn−1 contingency, these indicators provide a severity estimate and serve as inputs to a supervised learning model trained on labels derived from time-domain simulation. This approach aims to reflect how each disturbance might impact system stability, consistent with the objectives of DSA. Contingency rankings derived from these estimates serve to guide further analysis, enabling TSOs to focus dynamic simulations on the most critical scenarios.