This paper deals with a review of the state-of-the-art performance investigations of green gas for grid (g3) gas, which is an emerging eco-friendly alternative insulation gas for sulfur hexafluoride (SF₆) that will be used in gas-insulated power facilities for reducing environmental concerns. The required physical and chemical properties of insulation gas for high-voltage applications are discussed, including dielectric strength, arc-quenching capability, heat dissipation, boiling point, vapor pressure, compatibility, and environmental and safety requirements. Current studies and results on AC, DC, and lightning impulse breakdown voltage, as well as the partial discharge of g3 gas, are provided, which indicate an equivalent dielectric strength of g3 gas with SF₆ after a proper design change or an increase in gas pressure. The switching bus-transfer current test, temperature rise test, and liquefaction temperature calculation also verify the possibility of replacing SF₆ with g3 gas. In addition, the use of g3 gas significantly reduces theabovementioned environmental concerns in terms of global warming potential and atmosphere lifetime. In recent years, g3 gas-insulated power facilities, including switchgear, transmission line, circuit breaker, and transformer, have been commercially available in the electric power industry.

This paper addresses the issue of course keeping control (CKC) for unmanned surface vehicles (USVs) under network environments, where various challenges, such as network resource constraints and discontinuities of course and yaw caused by data transmission, are taken into account. To tackle the issue of network resource constraints, an event-sampled scheme is developed to obtain the course data, and a novel event-sampled adaptive neural-network-based state observer (NN–SO) is developed to achieve the state reconstruction of discontinuous yaw. Using a backstepping design method, an event-sampled mechanism, and an adaptive NN–SO, an adaptive neural output feedback (ANOF) control law is designed, where the dynamic surface control technique is introduced to solve the design issue caused by the intermission course data. Moreover, an event-triggered mechanism (ETM) is established in a controller–actuator (C–A) channel and a dual-channel event-triggered adaptive neural output feedback control (ETANOFC) solution is proposed. The theoretical results show that all signals in the closed-loop control system (CLCS) are bounded. The effectiveness is verified through numerical simulations.

In order to realize the green, low-carbon and sustainable development of shipping, liquefied natural gas (LNG) fuel powered ships as an effective measure of energy saving and emission reduction in shipping, have been paid attention to by the shipping industry. Based on the statistical data of Det Norske Veritas, this paper studies the proportion of global LNG fuel powered ships in clean energy ships and the types of ships which used LNG as fuel through data comparison and analysis. At the same time, the paper further makes a comparative analysis of the bunkering mode of LNG fuel powered ships and the supply and demand status of LNG bunker vessels and puts forward constructive suggestions, with a view to providing reference for the development of bunkering of LNG fuel powered ships in China.