KEYWORDS: Data modeling, Temperature distribution, Electric fields, Transformers, Dielectrics, Visualization, Visual process modeling, Design, Physics, Modeling
This article is based on the physical field model with multiple physical field mechanisms, which enables the digital twin model to accurately simulate the behavior of physical objects. The driving model based on the reduced order algorithm enables the digital twin model to have good interaction and exploration of physical object mechanisms while ensuring computational accuracy. The visualization model enables the digital twin model to display the internal structure and state of physical objects in a detailed and intuitive manner. Grid data is the finite element mesh parameters obtained by finite element meshing of the bushing geometric model. Each node in the grid data not only participates in the calculation of the multi physical field of the valve side bushing, but also interfaces with the visualization model as the rendering basis for the visualization of valve side bushing. Therefore, constructing grid data requires grid node data and grid rendering data. The grid node data is stored in NAS (BDF) file format, and the grid rendering data is stored in STL file format.
KEYWORDS: Photovoltaics, Solar energy, Transformers, Neural networks, Resistance, Mathematical optimization, Capacitors, Solar cells, Power grids, Temperature metrology
User side energy storage system is generally discrete distributed energy storage system, which can effectively play a role in the power storage in the traditional power systems. The distributed energy storage system can be analyzed theoretically through the classical single capacitor analysis theory, and the complete solution of constant power discharge of single capacitor can be obtained through system derivation. After calculation and simulation, the charging and discharging characteristic curve of group user side energy storage photovoltaic system can be obtained. For photovoltaic characteristic curves, this article collected typical power system characteristic load curves and found that the photovoltaic output curve presents an inverted "U" shaped distribution, but the electricity consumption curve presents an irregular distribution feature. And based on Hop-field Lagrange neural network, a single photovoltaic cell capacitor is used as a neural network node, and the daily distribution curves of photovoltaic cell are obtained through continuous iterative optimization. The optimization result is to optimize the power load curve from the traditional "M" type characteristic curve to a stable horizontal curve. At the same time, the spontaneous self use ratio of photovoltaic power generation was optimized, and the thermal diagram after installing photovoltaic energy showed the full day self use ratio of photovoltaic energy storage. The research results of this article can provide theoretical and practical basis for the economic scheduling of energy storage on the user side. At the same time, for the first time, the Hop-field Lagrange neural network is matched and optimized with the photovoltaic output power generation curve, and the photovoltaic power generation convergence load curve is effectively obtained through hundreds of iterative calculations.
The optical structure suitable for the on-line detection of high-voltage equipment is designed, the on-line analysis of trace decomposition gas composition of insulating gas SF6 of the high-voltage equipment is realized, and the prototype is developed. The optical noise suppression technology suitable for the field is studied, the optical path system is designed to withstand the gas pressure of high-pressure equipment, and the influence of field vibration and temperature change of the high-pressure equipment on the optical path structure is solved. The judgment threshold of expert diagnosis system is formed to predict the operation state and fault type of GIS equipment according to the changes of types and contents of typical decomposition products of the sulfur hexafluoride. The above achievements lay the theoretical foundation for realizing the on-line monitoring of the insulation status of SF6 Electrical equipment, greatly promoted the development and application of ultraviolet spectrum and non dispersive infrared optical live sensing detection technology, provided effective guarantee for the safe and stable operation of the sulfur hexafluoride electrical equipment, further improved the reliability of equipment, and ensured the ability of power grid to safely and continuously provide clean energy, ensure reliable power supply and good social benefits.
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