Forecasting solar energy generation in the mediterranean region up to 2030–2050 using convolutional neural networks (CNN)

Abstract

This study investigates the significant rise in solar energy production across the Mediterranean region from 2010 to 2022, attributing this growth to technological advancements, cost reductions, and favorable geographic conditions. Utilizing a Convolutional Neural Network (CNN) model, the research forecasts solar energy production for Spain, Egypt, Turkey, France, and Greece up to 2050. Results indicate that Spain is projected to lead with an estimated production of 42,547,680 watt-hours in the summer of 2050, while Turkey is anticipated to reach 20,528,640 watt-hours during the same period. The findings highlight robust growth in all analyzed countries due to increased investments in renewable energy infrastructure and supportive government policies. Quantitative analysis reveals a substantial decline in solar installation costs, exemplified by a decrease from $7.53 per watt in 2010 to $2.65 in 2021 in the U.S., which further stimulates solar energy expansion. The study emphasizes the critical role of government initiatives in promoting renewable energy adoption and outlines how solar energy can significantly contribute to reducing carbon emissions and enhancing energy security. Comparisons with regions such as the Middle East and southwestern United States suggest commonalities in solar potential but also highlight challenges posed by climatic variability and infrastructure differences. The robustness of the CNN model is demonstrated through its ability to integrate real-time climate data, enhancing forecasting accuracy by accounting for factors like solar radiation changes and extreme weather events. The research concludes by advocating for further refinement of the model through hybrid techniques and climate change scenario integration to bolster predictive capabilities. Overall, these insights provide valuable guidance for policymakers and energy producers in planning sustainable energy production strategies for the future.