Publication

Abstract : Load forecasting is essential for effective energy management and planning in power systems. This study compares the Seasonal Autoregressive Integrated Moving Average (SARIMA) and Prophet models for predicting hourly electricity consumption data from PJM Interconnection LLC. The primary objective is to identify the best-performing model between the two. The results reveal key insights into the strengths and weaknesses of each model, providing valuable guidance for their application in various load-prediction scenarios. The findings aim to improve the accuracy and reliability of statistical forecasting methods in energy management.