Considering the difficulty of power supply for automatic observation equipment in the polar regions, this paper introduced a small standalone renewable energy system with wind–solar co-generation as the energy supply scheme. Mathematical models were given, including solar photovoltaic panels, wind turbines, solar irradiance, wind energy density, and renewable energy assessment. ERA-Interim atmospheric reanalysis data were used to evaluate solar energy resources, and the synergistic effect of wind–solar resources on renewable energy was also analyzed and discussed. The system composition of the small standalone renewable energy system was proposed in this study. This system deployed near Zhongshan Station was taken as the object of investigation to analyze the operation performance of each component of the system in different months, and the technical feasibility of the system has also been verified. The results showed that the wind–solar resources in the polar regions had a synergistic effect, which can provide an effective and feasible scheme for the power supply of automatic observation equipment. Through research and analysis, it was found that each component of the renewable energy system, including photovoltaic panels, wind turbines, and batteries, could meet the long-term power supply requirements of automatic observation regardless of the polar periods, polar day or polar night. This paper can not only provide theoretical and data support for the application of small independent renewable energy systems in the polar regions but also provide feasible solutions for clean energy supply of the systems and equipment for independent observation stations deployed in uninhabited islands and alpine regions.

A large number of research stations have been established to provide members of Antarctic expeditions with logistical support. A previous study confirmed that the wind and solar energy resources of the Chinese Zhongshan Station, a coastal station located in an area of Lassmann Hills in East Antarctica, are highly synergetic and complementary. Considering the demand for a renewable energy power supply in Zhongshan Station, this paper introduces a hybrid energy system with wind–solar–diesel–battery co-generation used as a power supply scheme. Based on the 2015 climate data for Zhongshan Station, the wind–solar resources, conventional energy system, and annual diesel consumption of the station area were analyzed. The annual electrical load demand of each building in the station area was quantitatively expounded. Compared with the original power supply system, and combined with the analysis results of the thermal load and electrical load demands of the station, an objective function based on the requirements of economy, reliability, and environmental protection was presented. According to the constraint conditions of the heat energy and electrical energy load balance in the station area, a multi-objective scheduling strategy for the system was designed. Finally, the effects of this scheduling strategy were analyzed under three different application scenarios. The results indicated that the annual load demand was significantly lower than before the scheduling, and that a 50% reduction in diesel consumption could be achieved, demonstrating that the multi-objective scheduling strategy proposed in this paper could achieve optimal energy scheduling and management of the renewable hybrid energy system.

Sea ice affects the Earth’s energy balance and ocean circulation and is crucial to the global climate system. However, research on the decadal variations in the mean sea-level pressure patterns in recent winters (2001–2020) and the characteristics of sea ice motion (SIM) in the Western Arctic region is very limited. In this study, we utilized the Empirical Orthogonal Function (EOF) analysis method to investigate the potential impacts of Arctic Oscillation (AO) and Arctic Dipole (AD) on the Beaufort High (BH) during the period 2001–2020 and discuss the changes in SIM intensity in the Western Arctic. The results indicate that the negative phases of AO and AD are connected with (tend to bring about) a higher BH, strengthening anticyclonic circulation in the Arctic region. Conversely, the positive phases of AO and AD led to the collapse of the BH, resulting in a reversal of sea ice movement. Additionally, during the period 2001–2020, the BH consistently explained 67% of the sea ice motion (had the highest explanatory degree for sea ice advection within the region (weighted average 61.71%)). Meanwhile, the sea ice advection has become more sensitive to change in various atmospheric circulations. This study contributes to an in-depth understanding of the response of sea ice motion to atmospheric circulation in the Western Arctic in recent years, offering more explanations for the anomalous movement of sea ice in the Western Arctic.

Hydrogen energy generation plays a crucial role in enhancing the utilization of clean energy at coastal stations with abundant wind and solar resources in Antarctica. In response to the reliable demand for the application of hydrogen fuel cells in standalone observation systems in Antarctica, in this research, a power supply scheme based on a proton exchange membrane fuel cell (PEMFC) is introduced. Transient models of the PEMFC are developed, and the optimum operational and environmental conditions are determined through experimental investigations conducted at low temperatures. Based on the findings, a PEMFC-based power supply system is designed, encompassing a fuel cell stack, a measurement and control system, and an operation cabin. A temperature-coordinated control system leveraging a BP neural network, fuzzy logic rules, and the fuzzy-based active disturbance rejection control (Fuzzy-ADRC) strategy are proposed to ensure that the temperature of the PEMFC and cabin can reach the optimal state rapidly and that the output voltage is stable. The results indicate that the stack temperature reaches the specified value more rapidly than with PID and ADRC control methods when the current loading and changes in the ambient temperature are considered, and the output voltage oscillation amplitude can be more effectively minimized. This research provides preliminary guidance for a reliable energy supply scheme for PEMFCs, especially in standalone observation systems in coastal locales.

In view of the problems that mean that existing detection networks are not effective in detecting dynamic targets such as wildfire smoke, a lightweight dynamically enhanced transmission line channel wildfire smoke detection network LDENet is proposed. Firstly, a Dynamic Lightweight Conv Module (DLCM) is devised within the backbone network of YOLOv8 to enhance the perception of flames and smoke through dynamic convolution. Then, the Ghost Module is used to lightweight the model. DLCM reduces the number of model parameters and improves the accuracy of wildfire smoke detection. Then, the DySample upsampling operator is used in the upsampling part to make the image generation more accurate with very few parameters. Finally, in the course of the training process, the loss function is improved. EMASlideLoss is used to improve detection ability for small targets, and the Shape-IoU loss function is used to optimize the shape of wildfires and smoke. Experiments are conducted on wildfire and smoke datasets, and the final mAP50 is 86.6%, which is 1.5% higher than YOLOv8, and the number of parameters is decreased by 29.7%. The experimental findings demonstrate that LDENet is capable of effectively detecting wildfire smoke and ensuring the safety of transmission line corridors.