Heat Dissipation Efficiency Optimization Method for ONAF External Cooling System Taking into Account Airflow Losses
Wang Lujia1, Cai Zhenlu1, Qiu Yabo1, Zhang Lebin1, Yang Haitao2, Zhang Jianwen1
1. School of Electrical Engineering China University of Mining and Technology Xuzhou 221116 China; 2. Electric Power Research Institute of State Grid Anhui Electric Power Company Hefei 230601 China
Abstract To help improve the energy efficiency of transformer cooling systems, “lightweight and miniaturization” is a development trend. The precise configuration of the fan diameter ensures efficient heat dissipation and reasonable air volume distribution while avoiding the problems of high cost, heavy mass, and large air loss, which is in line with the “light” and “small” concepts. The main means to study the cooling performance of transformers is often based on computational fluid dynamic (CFD) tentative modeling and improvement, to explore the cooling effect of the configuration structure, but CFD numerical simulation can obtain the required high precision results, but the pre-processing such as equal scale 3D modeling, mesh drawing and multi-physics field simulation consumes a lot of computational resources and time, and the process is complicated and the optimization objective is single. Thus, a fast iterative optimization model is constructed for a radiator with natural oil circulation forced air cooling (ONAF). Firstly, the analytical model includes the momentum analysis of the overall oil circulation, the cooling air intensity analysis based on the local air loss coefficient, and the heat transfer analysis of the internal oil flow and external air of the radiator. Among them, the momentum analysis of oil circulation is the core of radiator temperature rise calculation, and the local loss coefficient of air volume is closely related to wind speed, fan diameter, cooling air distance, and duct perimeter, and directly affects the Nusselt number (Nu), which is the most important dimensionless number reflecting convective heat transfer strength. Matlab is then used to iteratively calculate the flow-heat characteristic parameters of the analytical model to obtain the radiator import and export oil temperature difference, the relationship between air loss and heat dissipation efficiency is finally integrated and controlled to achieve efficient heat dissipation in the cooling system. Secondly, to verify the accuracy of the analytical model, a combined flow-thermal simulation and test platform was also established based on the PC2600-22/520 radiator with an equal scale. The k-ε model was selected for the simulation, and the physical parameters of mineral oil, air, and heat sink were defined. In the test, three types of fans with diameters of 455 mm, 655 mm, and 855 mm were used to record the temperature difference between the inlet and outlet of the radiator, and a hot-wire anemometer was used to measure the air velocity and the temperature between the radiator fin. Finally, the research shows that the fan diameter has a non-linear effect on the oil temperature difference, and the wind loss is positively correlated with the diameter. With the PC2600-22/520 radiator as the verification object, the temperature difference can reach the desired value when the wind speed is 3.5 m/s and the fan diameter is 1.2~1.5 times the width of the radiator fin, at which time the heat dissipation efficiency and the wind loss collaborate to enter the optimal interval. In addition, the average relative error between the model calculated cooling air flow rate of the adjacent air duct at the center of the radiator fin and the test and simulation results is less than 6%, and the average relative error of the outlet oil temperature is less than 2%, which saves more than 98.56% of time cost. The work of this paper provides a new idea for the lightweight design of radiator structure under forced air cooling, cooling efficiency improvement and cooling air intensity distribution calculation.
Wang Lujia,Cai Zhenlu,Qiu Yabo等. Heat Dissipation Efficiency Optimization Method for ONAF External Cooling System Taking into Account Airflow Losses[J]. Transactions of China Electrotechnical Society, 2023, 38(17): 4767-4778.
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2023, Vol. 38 
