A New Distributed Power System for Stability Prediction And Analysis

Abstract

Grid system is prone to all kinds of disturbances. These disturbances only appear in a moment, but often cause cascading failures. Aiming at this problem, a prediction and analysis system for distributed power grid stability is developed. Firstly, combined with advanced data processing technology, the factors affecting the stability of power grid are analyzed and described. Secondly, a combined model KRR-XGBoost is proposed to predict the grid stability index, and the grid stability can be judged according to the predicted results. In order to verify the effectiveness of the model, we take the UCI distributed grid stability data set as an example to carry out the test. The experimental results show that compared with the other four models, this model can provide more accurate prediction results and better predict the stability of distributed power system, which further provides effective design guidance and cost optimization for distributed power supply system.