Parameter Identification of Oil-paper Insulation Extended Debye Model Based on Improved Snow Ablation Optimizer
Solving the extended Debye model equivalent circuit parameters of transformer oil-paper insulation based on the recovery voltage method is a typical nonlinear multi-objective optimization problem.In order to improve the efficiency and accuracy of extended Debye model parameter identification,a novel improved snow ablation optimization algorithm(ISAO)is proposed to effectively solve the problem of extended Debye model parameter identification.The ISAO incorporates various improvement strategies,adopts Tent chaotic mapping and refractive mirror-learning mechanism to improve the search efficiency,introduces the Levy flight strategy and greedy strategy to enhance the optimization performance,and proposes the parameter presetting mechanism to further simplify the process of identification and improve the efficiency of the solution.Meanwhile,the ISAO is applied to the optimization of the parameters of the oil-paper insulated Debye equivalent circuit,and compared with several commonly used optimization algorithms for validation,which proves that the method has significant advantages in the identification of the parameters of the extended Debye model.
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