The Combinating Optimizing Algorithm for Grounding Grid Fault Diagnosis

Grounding grid is commonly installed in the substation. When it´s damaged, not only restoring and improving work affects the production, but also it is difficult to carry this work out. In this paper, a new nonlinear constraint optimization model is established in order to find out the corrosion and abruption of the grounding grid. Due to the characteristics of grounding grid fault diagnosis, a combined optimizing algorithm is proposed, in which evolutionary strategy in groups and two kinds of adaptive functions are used. In order to reduce the infeasibility of the particle, in each step, after using PSO, linear programming is used to make partial updating around every particle, so the rate and efficiency is improved. When some particle is near enough to the optimal particle, we renew it by the way the initial particle is generated so as to increase the diversity and prevent precocity of the swarm. The algorithm proposed here could solve the multi-solution problem when touchable nodes are not enough, so we can find out corrosions of the grounding grid.