Forecasting Cost Saving Through Solar System Installation

• Published in: 2023 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2023 - Proceedings
• Main Author: Razak S.A.B.; Zaini N.; Latip M.F.A.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168326990&doi=10.1109%2fI2CACIS57635.2023.10193393&partnerID=40&md5=c526ed67a28f9c9c8a55da5151d77b12

The benefits of installing solar panels for electricity generation are not widely understood. Thus, this study aims to raise awareness by analyzing solar energy generation and simulating potential cost savings based on solar irradiance data. A Linear Regression model was developed by identifying the correlation between actual solar energy generation and solar irradiance data at a specific location. The study employs MSE, RMSE, and R-squared metrics to evaluate prediction accuracy. The developed model has a low MSE and RMSE value of 5.9 and 2.43, respectively, and a high R-squared value of 0.75, indicating high prediction accuracy. This model can predict solar power generation at specific locations based on solar irradiance data, enabling the estimation of cost savings from reduced electricity bills and maximum power generated by the solar panels. © 2023 IEEE.