Time Sights (Forecast Electric Energy)

Abstract

This aims to develop an accurate and reliable predictive model for forecasting electricity bills. Energy efficiency and cost saving are the most important things. The prediction of electricity consumption is help's individuals and businesses to manage the cost efficiently. This project employs advanced time series analysis techniques to address this challenge. The project begins with the collection of historical electricity consumption and billing data, spanning multiple time periods, and focuses on a comprehensive preprocessing phase to ensure data integrity. Exploratory Data Analysis (EDA) must take main into consideration trends and seasonality in the dataset. To facilitate accurate forecasting, the time series data is decomposed into its key components, including trend, seasonality, and residual. Additionally, relevant external features, such as weather data, holidays, and special events, are engineered to enhance the forecasting model's performance.