In this project, we successfully achieved effective Energy Consumption Prediction by utilizing machine learning models, with a specific focus on the Random Forest Model. Our study was conducted using a comprehensive dataset that encompassed power consumption data for region one, region two, and region three in the city of Tétouan. The dataset included various factors such as temperature, humidity, wind speed, general diffusion rate, and diffusion rate, which were measured at regular intervals of either every 10 minutes or hourly. To determine the most suitable model, we employed various machine-learning techniques and conducted model training and evaluation. Through analyzing their score values, we were able to identify the model that performed the best in accurately predicting energy consumption.
The details can be accessed from here: Project Report