An Intellectual Monitoring Of Power Sector By Machine Learning Applications

Abstract

Power sector growth has been primarily focused on increasing the scale at which electricity is generated and transmitted throughout the course of the past century, which has been the case for the bulk of the twentieth century. As a result of the applications have been introduced. These include WAMSin the middle of other applications. This has presented unmatched tests to power grids that have been functioning reliably for periods. In order to meet these difficulties, the power sector must develop and deploy sophisticated automated management and control methods as soon as possible. With the context of the power sector in mind, this study investigates and forecasts the application of leading-edge machine learning technologies in power grids, as well as putting forth some novel concepts that are not previously considered. Some novel machine learning applications for the power sector have been studied and suggested, and some have already been implemented. Additionally, the benefits and drawbacks of each are addressed in detail.