Abstract：The dynamic transformer rating (DTR) and thermal life loss of oil-immersed transformers under on-site variable load operation conditions are closely related to the transient temperature rise of the equipment. However, as an implicit solution method, the traditional finite element analysis and finite volume method need to be iteratively solved in each sub-step of transient thermal analysis, which has many computational resources and is time consuming. It is challenging to meet the requirements of fast calculation. The rapid and accurate solution of the temperature field (especially the hot spot temperature rise) of the oil-immersed transformer in field operation is the premise to realize the digital operation and maintenance of the transformer and the DTR evaluation. Therefore, this paper proposes a lattice Boltzmann (LBM) physical in the loop simulation model for coupled electrical networks. The real time evaluation of DTR under electrical network constraints is realized through the rapid solution of the transformer temperature field. Firstly, the D2Q9 model is used to solve the fluid flow and thermal lattice Boltzmann equations (LBEs) to capture the transient oil flow and temperature rise process inside the transformer. In the Simulink environment, the equivalent current source model is used to construct the electrical network constraints of multi-level load scenarios, and the established transformer LBM model is used as a component for numerical encapsulation to complete the construction of the physical-in-the-loop simulation model. Secondly, to verify the effectiveness of the proposed method, the finite volume method (FVM) is used to simulate the same oil-immersed transformer model. The grid independence test determines the optimal number of grids. The number of grids is 1 250×420 for LBM modeling and simulation, and the number of units is 43 654 for FVM meshing. Compared with the constructed LBM-Simulink model with the FVM model, LBM still has the advantages of speed and memory occupation when the number of lattices is higher than the number of FVM units. If commercial software is used, this advantage will be further expanded. Thirdly, the steady state solution results of the hot spot temperature rise of the established LBM model are compared with the FVM solution, and the error is 2.60%. According to the load curve given in the transformer guidelines, it is used as input to solve the transient temperature rise of the established LBM and FVM simulation models. Finally, the results show that the LBM and FVM calculations are better than the transformer guide calculation. The maximum error between the hot spot temperature calculated by LBM and FVM is 6.44%. Moreover, the hot spot temperature rise trend of LBM is consistent with the transformer load guidelines, which verifies the effectiveness of the proposed method. Based on the constructed LBM model, the load capacity of oil-immersed transformers under constant 25℃ and typical ambient temperature changes in summer and winter are evaluated at 6~18 hours during the day. The results show that under the premise that the relative insulation life loss of oil-immersed transformers is less than 1. The maximum load capacity coefficients are 1.20, 1.10, and 1.60 under the constant ambient temperature of 25℃, typical temperature changes in summer, and typical temperature changes in winter. The simulation model based on the proposed LBM provides an effective method for real-time monitoring of temperature rise, load capacity evaluation, and dynamic capacity increase of oil-immersed transformers.
于文旭, 关向雨, 赵俊义, 涂嘉毅, 赖泽楷. 基于格子玻耳兹曼的油浸式变压器瞬态温升模拟与负载能力评估[J]. 电工技术学报, 2025, 40(10): 3315-3325.
Yu Wenxu, Guan Xiangyu, Zhao Junyi, Tu Jiayi, Lai Zekai. Transient Temperature Rise Simulation and Load Capacity Evaluation of Oil-Immersed Transformer Based on Lattice Boltzmann Method. Transactions of China Electrotechnical Society, 2025, 40(10): 3315-3325.
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