Restoration of the current transformer secondary current under core saturation conditions based on ANN

Abstract

Relay protection and emergency automation is an integral part of electric power systems. The algorithms of the relay protection and emergency automation are based on the use of analysis of the parameters of the electrical mode - current and voltage - obtained from current and voltage instrument transformers. As a rule, these transformers operate on the basis of the laws of electromagnetism. Operational experience shows that the magnetic core of current transformers under fault conditions can be saturated. As a result, the shape of the measured current is distorted which can lead to false operation of the relay protection and emergency automation system. In this paper a comparative analysis of the existing methods is presented. The advantages and disadvantages of them are described. The problem of current transformer core saturation is reduced to a regression problem. To solve the problem an artificial neural networks-based method is proposed. Computational experiments for both proposed and existing methods are performed. The results of experiments show that the efficiency of the proposed method is 1.25 times higher relative to the most effective existing method. The method of re-scaling data at real-time work applied to the restoration of the distorted shape of current is proposed.

Keywords

• Current transformer
• Core saturation
• Protection system
• Artificial neural network