A Learning-Based System for Monitoring Electrical Load in Smart Grid

Abstract

This paper mainly presented a system which can make a prediction to the distribution transformer's load status in smart grid. Since the operation of distribution transformer's load status is generally in the post processing stage at the current stage, lacking forecasting work on distribution transformer's operation and load status. Given the issues above, to reduce costs, ensure the security of power supply, and improve the emergency response capabilities, we presented a prediction system, which can predict the load status of distribution transformer by utilising the data mining algorithm. Besides, the system also provides a platform for the management and maintenance of electrified wire netting's information. In this system, users can conveniently manage the vast and multifarious data sets.