Optimization Design of Oil-Immersed Iron Core Reactor Based on the Particle Swarm Algorithm and Thermal Network Model

In this paper, according to the design parameters of oil-immersed iron core reactor, the thermal network model of windings is established by the thermo-electric analogy method, and the temperature distribution of the windings can be obtained. Meanwhile, a fluid-thermal coupled finite element model is established, the temperature and fluid velocity distribution are extracted, and the simulation results show that the error coefficient of temperature is less than 3% compared with the thermal network model, so the correctness of thermal network model has been verified. Taking the metal conductor usage and loss of windings as the optimization objects, the optimization method based on the particle swarm algorithm and thermal network model is proposed, and the Pareto optimal solutions between the metal conductor usage and loss of windings are given. The optimization results show that the metal conductor usage is reduced by 23.05%, and the loss is reduced by 20.25% compared with the initial design parameters, and the maximum temperature of winding does not exceed the expected value. Thus, the objects of low metal conductor usage and loss of windings are conflicted and cannot be optimized simultaneously; the optimization method has an important guiding significance for the design of oil-immersed iron core.