Estimation of ground enhancing compound performance using Artificial Neural Network

Grounding system constitutes an essential part of the protection system of electrical installations and power systems against lightning and fault currents. Therefore, it is of paramount importance that engineers ensure as low values for grounding resistance as possible, during the designing phase as well as the lifecycle of the grounding system. A widely used technique of reducing the grounding resistance value, in case of high soil resistivity values, or lack of adequate space for the installation of grounding systems, is the use of ground enhancing compounds. This paper presents a methodology, for the evaluation of grounding resistance, under various meteorological conditions, of grounding systems embedded in natural soil as well as in ground enhancing compounds, using Artificial Neural Network (ANN). The ANN training is based on field measurements that have been performed in Greece during the last year. As a matter of fact, this is a first step to develop a new method for estimating variations of grounding resistance value.