Journal of East China Normal University(Natural Sc ›› 2019, Vol. 2019 ›› Issue (5): 133-142.doi: 10.3969/j.issn.1000-5641.2019.05.011

• Computational Intelligence in Emergent Applications • Previous Articles     Next Articles

Prediction of power network stability based on an adaptive neural network

ZHAO Bo, TIAN Xiu-xia, LI Can   

  1. College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai 200090, China
  • Received:2019-07-27 Online:2019-09-25 Published:2019-10-11

Abstract: The safety and stability of the power grid serves as the basis for reform, development, and stability of power enterprises as well as for broader society. With the increasing complexity of power grid structures, safety and stability of the power grid is important for ensuring the rapid and effective development of the national economy. In this paper, we propose an optimal neural network stability prediction model and compare performance with classical machine learning methods. By analyzing the UCI2018 grid stability simulation dataset, the experimental results show that the proposed method can achieve higher prediction accuracy and provide a new approach for research of power big data.

Key words: grid stability, support vector machine, decision tree, neural network

CLC Number: