Devices In Power Grid Research Articles

Power Transformer Fault Diagnosis Using Random Forest and Optimized Kernel Extreme Learning Machine

Power transformer is one of the most crucial devices in power grid. It is significant to determine incipient faults of power transformers fast and accurately. Input features play critical roles in fault diagnosis accuracy. In order to further improve the fault diagnosis performance of power transformers, a random forest feature selection method coupled with optimized kernel extreme learning machine is presented in this study. Firstly, the random forest feature selection approach is adopted to rank 42 related input features derived from gas concentration, gas ratio and energy-weighted dissolved gas analysis. Afterwards, a kernel extreme learning machine tuned by the Aquila optimization algorithm is implemented to adjust crucial parameters and select the optimal feature subsets. The diagnosis accuracy is used to assess the fault diagnosis capability of concerned feature subsets. Finally, the optimal feature subsets are applied to establish fault diagnosis model. According to the experimental results based on two public datasets and comparison with 5 conventional approaches, it can be seen that the average accuracy of the proposed method is up to 94.5%, which is superior to that of other conventional approaches. Fault diagnosis performances verify that the optimum feature subset obtained by the presented method can dramatically improve power transformers fault diagnosis accuracy.

Research and Performance Optimization of Visualization of Panoramic Monitoring in Responsive Distribution Network

As the scale of the power grid continues to expand, the number of power grid devices in the national power system is increasing, the structure of the power grid is becoming more and more complex, and the information construction of the distribution network is improving, but the visualization is relatively low in real time. In terms of informationization, the current information presentation and interaction mode cannot adapt to the rapid expansion of power supply scale and daily distribution network operation and maintenance management. In this paper, we study GIS-based grid panoramic visualization display technology and responsive visualization solutions for multiple terminals. These solutions not only improve the monitoring efficiency of the distribution network, but also reduce the time of finding and overhauling when problems occur. It also enables visualization of topological data and timely access to the required information. The experiments in this paper use clustering methods to optimize the visualization elements as well as to optimize the GIS rendering, which effectively improves the visualization efficiency.

Aspects Regarding the Use of Electronic Power Devices in Power Grid

Abstract Custom power devices are generally used to power sensitive consumers who need higher energy quality. This paper will exemplify some of the custom power devices used in distribution networks. The case study will highlight the solid-state current limiter effects on an electrical network by simulating a medium voltage network. By installing a solid-state current limiter, the value of the short-circuit current decreases; thus, the electrodynamic forces and thermal stresses supported by the components of the electrical network are reduced.

The overhauls technical innovation project optimization method of power grid device based on Life Cycle Asset Management

In order to realize the precise management of investment in equipment overhauls technical innovation project, this paper fully analyzed the cost characteristics of equipment in every section of the life cycle and established the actual available Life Cycle Cost (LCC) model and provided a combination forecasting method to forecast the future costs. Then this paper obtained the full life cycle cost of the equipment for overhauls technical innovation project. By comparison of the two average annual LCC costs of overhaul and technical innovation project, the final optimization project with the best economic benefit could be determined. Case analysis verified the economics of the method, which could provide decision support for precise investment in the power grid.

Knowledge Graph Construction and Application of Power Grid Equipment

Recent development of artificial intelligence (AI) technology enquires the traditional power grid system involving additional information and connectivity of all devices for the smooth transit to the next generation of smart grid system. In an AI-enhanced power grid system, each device has its unique name, function, property, location, and many more. A large number of power grid devices can form a complex power grid knowledge graph through serial and parallel connection relationships. The scale of power grid equipment is usually extremely large, with thousands and millions of power devices. Finding the proper way of understanding and operating these devices is difficult. Furthermore, the collection, analysis, and management of power grid equipment become major problems in power grid management. With the development of AI technology, the combination of labeling technology and knowledge graph technology provides a new solution understanding the internal structure of a power grid. As a result, this study focuses on knowledge graph construction techniques for large scale power grid located in China. A semiautomatic knowledge graph construction technology is proposed and applied to the power grid equipment system. Through a series of experimental simulations, we show that the efficiency of daily operations, maintenance, and management of the power grid can be largely improved.

Design, Fabrication, and Operation of the Cryogenic System for a 220 kV/300 MVA Saturated Iron-Core Superconducting Fault Current Limiter

High reliability is one of the key requirements for a power grid device. The reliability of a superconducting fault current limiter (SFCL) largely depends on the reliability of its cryogenic system. An open cryogenic system was designed and fabricated for a 220 kV/300 MVA saturated iron-core SFCL, which was composed of a Dewar, heat insulation pipelines, a liquid nitrogen tank, a control circuit, and a vacuum pump. In its configuration, a high-temperature superconducting (HTS) dc bias coil is immersed with liquid nitrogen inside the Dewar. The control circuit constantly monitors the liquid nitrogen level and controls the supply of liquid nitrogen in accordance with the liquid nitrogen level. Nitrogen vapor is directly released into the environment. The SFCL including the cryogenic system was installed in the Shigezhuang substation of Tianjin, China. There are three operation modes for the cryogenic system. The first is the ac coil and the HTS coil being loaded with current. The second is the HTS coil being loaded with current, while no current in the ac coil. The last mode is no current loading in both the coils. Operation data of the cryogenic system are analyzed to compare thermal load, pressure, and supply cycle of liquid nitrogen in the three operation modes.