Analysis of Sustainability in Hydroelectric, Wind, and Solar Energy Systems with Artificial Intelligence

The increasing energy demand and environmental sustainability goals have made the effective use of renewable energy sources mandatory. The efficient and sustainable operation of hydroelectric, wind and solar energy systems is of great importance. Artificial intelligence (AI)-based analysis and prediction models increase the performance of these systems and provide optimization in energy production processes. In our study, artificial intelligence-supported analysis methods in hydroelectric, wind and solar energy systems were conducted, and the effects of machine learning and deep learning-based models on sustainable energy production estimates and system efficiency between 1995-2021 were evaluated. The algorithms used in the study aim to increase the accuracy of energy production estimates by utilizing historical data and to better adapt to variable environmental factors. In our study, many comprehensive data sets were used to perform global and regional analysis of hydroelectric, wind and solar energy production. The findings show that artificial intelligence-based models provide significant improvements in production estimates, maintenance planning and resource management in renewable energy systems.