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The off-state leakage (I off ) properties of the AlGaN/GaN high electron mobility field-effect transistors (HEMTs) was analyzed by fabricating metal-semiconductor (MES)-HEMTs and metal-insulator-semiconductor (MIS)-HEMTs. The experimental results show that off-state gate leakage (I g-off ) for MES-HEMTs is larger than the corresponding off-state drain leakage (I d-off ), which suggests that I d-off is a branch of I g-off . I off by the ion implantation isolation is nearly an order of magnitude lower than that by the ICP-etching isolation, which suggests the side wall under the gate electrode caused by the etching isolation can increase the I g-off and planar structure formed by ion implantation isolation can suppress gate leakage efficiently. A linear relationship of I d-off and I g-off for MES-HEMTs with the gate length implies that the gate area is proportional to the I g-off . This indicates that the edge effect on the I g-off can be negligible. At the same time, the estimated current with L g of 0 μm is not zero, indicating the gate metal covered isolation region participates in conduction. MIS-HEMTs can suppress I off significantly, indicating that the existence of the insulation layer can not only reduce the leakage current from effective gate electrode, but also suppress the leakage current from gate metal-covered isolation area.

The equipment which has not been operated, maintain, and switched beyond a specified interval is called three-no equipment. As the three-no equipment will cause some danger power network operation, a quick survey technology is proposed in this paper. The technique simulates artificial retrieval in the third subarea of the secondary security protection system. The technique works in a self-adaptive, divided-period, no-repeat way. Meanwhile, new equipment doesn't need to access and original network settings don't need to change. After the last action time of equipment is obtained by the computer in a short time, the difference between the last active time of equipment and the current time is used to take advice for check operation. An artificial equipment survey can be taken by computer automatically. The results of the actual case also show that the proposed technique is effective.

The causes and processes of personal accidents in the distribution network have extremely complicated factors. Due to the lack of scientific understanding of the basic laws of safety risks, personal accidents are repeatedly happened, leading to vicious electric shock accidents. In addition, if faults cannot be handled quickly and in a timely manner, ground faults can easily cause device overvoltage, causing equipment burnout and even causing fire accidents. Single phase grounding fault and power failure will reduce the reliability of power supply and directly affect industrial production and people’s living standards. This article is mainly based on the international advanced safety management concept. By identifying the influencing factors of single-phase grounding in distribution networks and closely integrated with power grid enterprises actual field operations, using the “5M safety risk factor” theory to analyze the personal safety and equipment safety influencing factors in power supply operations, extract six major influence factors that have a greater impact on the distribution network operation and personal safety. Based on the above points, a quantitative assessment model, index, and method system for single-phase fault processing based on security protection are proposed to effectively improve the person and device safety in power grid companies. Pre-control ability has very important practical value and promotion significance. It can provide a strong reference for the primary and secondary equipment and structure design of the new distribution network and the adjustment of the operating mode of the distribution network in operation, and effectively guide the operation and maintenance of the distribution network.

Electric vehicle charging station is the infrastructure to provide electric energy for electric vehicles (EV). Reasonable location of charging station is of great significance to promote the popularization of EVs. Firstly, the ownership of EVs in the selected area is forecasted. According to the ownership and driving characteristics of various types of EVs, the total charging demand of EVs and the charging demand of each network node are obtained. Secondly, the location model of charging station is established to minimize the sum of operation and maintenance costs of charging station and user loss costs. Finally, weighted Voronoi diagram and adaptive particle swarm optimization are used. The results show that this method can optimize the annual average comprehensive cost of charging station. Graphic user interface (GUI) is designed to display the result of location, which makes the location scheme more intuitive.