Finite Element Method Combined with Neural Networks for Power System Grounding Investigation

Even in homogenous soil and for simple geometrical structure the analytical design of a grounding system is a complex and not very accurate procedure. Using Finite Element Analysis (FEA) it can perform a precise design for complex grounding systems but with important hardware resources and time consumption. This paper proposes a methodology for power system grounding design, directed to ensure the advantages of the FEA but without its disadvantages. This is realized by adding the function emulation using neural networks. The vertical rod, buried in inhomogeneous soil is the subject of this presentation. Consequently, the first step was to perform FEA for a large number of configurations: different types of vertical rods connected to the surface, buried at various depths in different double-layer soil structures. Then, the results have been interpreted through a multi-layer perceptron (MLP) with one hidden layer. A compromise between the number of inputs and precision have been tested, in order to define a minimum number of FEA required to obtain an acceptable grounding system design, i.e. a desired grounding resistance, for any combinations of the geometrical and material parameters. The validation of the methodology was done based on data reported in various research works.

@article{Neamt2017,
  title     = {Finite Element Method Combined with Neural Networks for Power System Grounding Investigation},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {8},
  number    = {2},
  year      = {2017},
  publisher = {The Science and Information Organization},
  author    = {Liviu Neamt and Oliviu Matei and Olivian Chiver},
  doi       = {10.14569/IJACSA.2017.080225},
  url       = {https://doi.org/10.14569/IJACSA.2017.080225}
}