To Analyze Energy Consumption on BESCOM and Classify using ML Approach

To Analyze Energy Consumption on BESCOM and Classify using ML Approach

Dr Manjunath C R, Mithun C, K Vivek, K M S Veerendra Kumar, Lakum Sai Charan

Manjunath.cr@cmr.edu.in , mithun.c@cmr.edu.in , vivek.k@cmr.edu.in , veerendra.kumar@cmr.edu.in ,

lakum.saicharan@cmr.edu.in

UG scholar, Dept of CSE SoET, CMR University, Bengaluru, India

Professor,  Dept of CSE SoET, CMR University, Bengaluru, India

I.  ABSTRACT
Karnataka, a rapidly developing state in India, faces significant changes in energy demand due to population growth, urbanization, and industrialization. This study analyzes Karnataka's energy consumption patterns, particularly focusing on the Bangalore Electricity Supply Company Limited (BESCOM) area, and explores the application of Machine Learning (ML) for classification. It examines historical data, projections, and the impact of initiatives like the Gruha Jyothi Scheme, which provides free electricity to eligible households. The research highlights the need for accurate energy forecasting and efficient management to address consumption trends and ensure sustainable energy distribution. ML methods offer promising tools for predicting consumption, identifying patterns, and improving operational efficiency within the energy sector. The Gruha Jyothi scheme offers up to 200 units of free electricity each month for eligible households.

II. KEYWORDS
Energy Consumption, BESCOM, Classification, Gruha Jyothi.