Abstract
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.
Highlights
Numerical simulation of the electromagnetic field lays on the basis of modern CAD in electrical engineering
The professional design of power system grounding is conducted analytical in homogenous soil, for simple structures configurations, according to the theoretical computation of the electromagnetic field [1], [2] and again for more complex devices, but using simplified relations imposed by standards and regulations, [3,4,5]
EXPERIMENTAL RESULTS At this point we have decided that a neural network with 3 inputs, 10 hidden neurons and one output, using tanh as transfer function, respectively L.M. as learning rule is the best option in terms of quality, learning time and computation resources
Summary
Numerical simulation of the electromagnetic field lays on the basis of modern CAD in electrical engineering. Analytical relations are very complicate, if exist, inaccurate and determinable for simplified structures, material parameters and variable behavior [1,2,3,4,5] All these difficulties can be hurdle using FEA [6,7,8,9,10,11]. This paper intend to structure a methodology, based on FEA and neural network to generalize the FEA result, meaning the grounding resistance value, for any variation of the geometrical and material parameter of the base configuration. An initial configuration, changed successively regarding the imposed variation limits for parameters (geometrical and material) will constitute the FEA models In this step, a large number of models will be analyzed, asking for great hardware and time resources. For the above grounding system, the methodology offers, virtually instantaneously, a value of the grounding resistance for any combination of the material and geometrical parameters, offering in this way a key to a close optimum configuration
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