Zhang Shaoquan

Application of genetic algorithm-neural network for the correction of bad data in power system

There are small amounts of bad data in power system real time data. If we do not correct them, they will have impact on security and stability of the power system. This text put forward a bad data correction algorithm based on genetic neural network algorithm. In order to overcome the BP neural networks own defects, we use the genetic algorithm to define the optimum structure and the best initialized weights of the BP neural network. In this article, we use the real-time power data of Kunming power grid to simulation. The simulation results are accurate, and prove that this method can meet the need of improving the accuracy of the correction of bad data and enhancing the performance of the network.

Insulation characteristics analysis of the spacer with the temperature sensor

To study the effect of the temperature sensor on the spacers, the experimental platform of the temperature sensor and spacers model is constructed in this paper. It is studied that the flashover process is acquired with increasing the voltage using the sensor installing on the surface of the spacers, the simulated measuring temperature sensor by the steel, the ultraviolet instrument, and the ICCD. The results show that it is a big effect of the measuring temperature sensors installed on the surface on the spacers.