Solar Power Generation Prediction for Better Energy Efficiency using Machine Learning

• Published in: 2022 7th International Conference on Communication and Electronics Systems (ICCES) pp. 1185 - 1191
• Main Authors: Mantri, Vishesh, Sharma, NamoNarayan, Jayaraman, Ramkumar
• Format: Conference Proceeding
• Language: English
• Published: IEEE 22.06.2022
• Subjects: etc; Machine learning; Machine Learning (ML); Machine learning algorithms; Mean absolute error (MAE); Mean Square Error (MSE); Photovoltaic systems; Prediction algorithms; Predictive models; Renewable energy sources; Root Mean Square Error (RMSE); Solar energy
• DOI: 10.1109/ICCES54183.2022.9835749

The solar energy plant works by converting solar energy into electricity. The utilization of sunlight energy has escalated in recent years. Not only the electricity is conserved through the medium of a PV power plant but it also contributes towards the environment. The solar energy gets converted into electricity directly using photovoltaics. Nowadays, machine learning model is used in many everyday applications. The main necessity of Artificial intelligence is data. The past dataset is collected and that dataset is used to build a machine learning model. The necessary pre-processing techniques are applied like univariate analysis and bivariate analysis are implemented. The data is visualized for better under-standing of the features and based on that a classification model is built by using machine learning algorithm and comparison of algorithms are done based on their performance metrics like accuracy MAE, MSE, R2 etc.