• CHITIKESHI SAI PRANATHI
• BONAGIRI VARUN
• RAVIKANTI SAHITHI
• Dr. ATTILI VENKATA RAMANA

Smart Grid, named after the next generation of the power grid, has a flow between electricity and consumption and offers the delivery of an automated energy-efficient network. Despite being a power grid and efficient it does require some attention when it comes to load analysis as it is an automated system and system components are dependent on each other. This paper proposes a novel method for load factor analysis using two machine learning algorithms (RFE) and Logistic Regression (LR). These methods perform daily and monthly load analysis on Smart Grid using the feature selection process; Results are shown as a graphic format i.e., weekly and daily.

Random Forest, Logistic Regression, feature selection process, load forecasting, smart grid

"ELECTRICITY LOAD FORCASTING IN SMART GRID", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.833-836, May 2020, Available :http://www.jetir.org/papers/JETIR2005252.pdf

"ELECTRICITY LOAD FORCASTING IN SMART GRID", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. pp833-836, May 2020, Available at : http://www.jetir.org/papers/JETIR2005252.pdf