Optimisation of electric arc model parameters based on simplex annealing and genetic algorithms

This paper presents the method for obtaining the coefficients of the dynamic Cassie-Mayr electric arc model by means of annealing and genetic optimisation algorithms. The extraction of the coefficients can be obtained by means of the iterative fitting process based on e.g. multiple measurements results. However, this requires a significant effort and can generate significant costs. The approach presented in this paper relies solely on simulations. The methodology used herein consists in finding the match to the maximum produced TRV generated during high-voltage shunt reactor current breaking, for ideal switch and conductance based Cassie-Mayr circuit breaker models. This is done for a given chopping current value assigned to the ideal switch which is used as a target. The arc model coefficients are obtained by means of the optimisation process for various values of the desired chopping current level to be reflected by the Cassie-Mayr conductance-based electric arc model. As a result, an advanced conductance based model can be used for assessment of switching overvoltage. Genetic and simplex annealing algorithms have been selected for optimisation. The models as well as the optimisation process were conducted in EMTP-ATP software using its built-in functionalities. The article presents the error assessment and sample traces.