The dielectric behavior of insulations is a key factor affecting the development of anti-corona materials for generators. Epoxy resin (EP), as the matrix, is blended with inorganic fillers of micron SiC and nano SiO2 to investigate the effect of micro and nano doping on the conductivity and breakdown mechanism of the composites. Using experimental and simulation analysis, it is found that the effect of nano-SiO2 doping concentration on the conductivity is related to the dispersion of SiC particles. The lower concentration of SiO2 could decrease the conductivity of the composites. The conductivity increases with raising the nano-SiO2 doping concentration to a critical value. Meanwhile, the breakdown field strength of the composites decreases with the rising content of SiC in constant SiO2 and increases with more SiO2 when mixed with invariable SiC. When an equivalent electric field is applied to the samples, the electric field at the interface of micron particles is much stronger than the average field of the dielectric, close to the critical electric field of the tunneling effect. The density of the homopolar space charge bound to the surface of the stator bar elevates as the concentration of filled nanoparticles increases, by which a more effective Coulomb potential shield can be built to inhibit the further injection of carriers from the electrode to the interior of the anti-corona layer, thus reducing the space charge accumulation in the anti-corona layer as well as increasing the breakdown field strength of the dielectric.
The failure of electrical equipment directly or indirectly caused by overheating has become one of the main reasons for equipment accidents. The real-time condition monitoring method of electrical equipment based on digital twin (DT) has received extensive attention and is considered as a technology with great engineering values and excellent application prospects. However, the current calculation of DT mostly relies on the traditional finite element method (CFEM). This method becomes less computationally efficient as the size of the DT increases, especially for electrical equipment with high complexity. It is difficult to meet the requirements real-time calculation in DT. Therefore, starting from the algorithm optimization and parallel architecture, based on the weighted residual method and stabilised conforming nodal integration, a novel discrete method of electrothermal coupling equation is proposed and the data storage structure of the algorithm from the bottom layer is redesigned, and the corresponding GPU and multi-core CPU parallel framework are proposed. Finally, taking the high voltage bushing as an example, the correctness of the method in this paper is verified by the CFEM code and commercial software ABAQUS. Under the same grid and accuracy requirement, the calculation time is shortened by at least five times than ABAQUS. And the method is easy to extend to other types of multi-physics calculations.
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