Development of a Prototype Power Distribution Misuse Monitoring System

Abstract

In order to satisfy the rising need for efficient energy Synchro phasor systems have a vast data volume for wide-range tracking and power system operation. In the context of the big data problem, the design of conventional intrusion detection systems, using rules manually generated on the basis of expert expertise, is know-how intensive. This article introduces a clear and integrated approach to developing a hybrid IDS which learns temporary transmission line requirements including disruptions, showed normal processes and cyber-attacks. A machine learning algorithm called general trajectory mining is used to learn patterns for situations by fusing synchrophasor calculation data with power system audit logs automatically and reliably. An IDS prototype has been developed and validated as a proof of concept. For a multiple, seven power transmitting devices, the IDS prototype classifies disruptions, regular control operations and cyber assault correctly for distance security.