DLSU Senior High School Research Congress Conference Proceedings
Document Type
Paper Presentation
Research Advisor (Last Name, First Name, Middle Initial)
Gue, Ivan Henderson V.
Abstract/Executive Summary
Energy security remains a significant concern for the Philippines amid rising demand, growing population, and continuous modernization. Given the Philippines' history of energy problems, attention to energy is necessary. With this, the study aims to forecast the Philippines' possible annual energy consumption from 2025 to 2030, considering population growth as a potential variable influencing the Philippines’ projected energy consumption trends. The study employs a machine learning approach using the linear regression model, which was found to have the best performance in forecasting future energy consumption based on MATLAB’s Linear Regression Learner app. Prior to forecasting, historical data from 2010 to 2023 were analyzed in the study's correlation analysis to assess the relationship between energy consumption and population growth, revealing a strong positive linear relationship (r = 0.9). The linear regression model, on the other hand, showed high predictive accuracy ( R² = 0.93, RMSE = 4060.9 GWh, MAPE = 3.9%) with results projecting an increase in energy consumption from 109,750 GWh in 2024 to 122,710 GWh by 2030. The comparative analysis between DOE’s projected energy supply data and the study’s forecasted energy consumption indicates supply exceeding demand by 43,286 GWh by 2030. These findings suggest that DOE’s estimated energy supply is sufficient to meet the country’s needs through 2030.
Keywords
energy consumption forecasting; machine learning; machine learning forecasting; Philippine energy consumption; Philippine energy supply