Enhancing Energy Efficiency: Predictive Modeling for Electricity Bills

Abstract

The goal of this is to create a predictive model for electricity bills that is both accurate and dependable. Cost-effectiveness and energy efficiency are the most crucial factors. The ability to estimate electricity use helps both people and corporations to effectively control costs. To tackle this difficulty, this study makes use of sophisticated time series analytic tools. The project starts with gathering historical billing and consumption data for various time periods. It next concentrates on a thorough preparation step to guarantee data integrity. Trends and seasonality in the dataset are important factors to examine in exploratory data analysis (EDA). The time series data is broken down into its essential elements-trend, seasonality, and residual-to enable precise forecasting. In order to improve the efficacy of the forecasting model, pertinent external features are also engineered, such as weather data, holidays, and special events.