Artificial Intelligence for Flow Optimization in Renewable Energy Systems

Numerous sectors have recognized the remarkable potential of deep learning (DL) and artificial intelligence (AI) to enhance long-term sustainability. Although AI may address 134 of the 169 Sustainable Development Goals (SDGs), the fast advancement of these technologies needs stringent regulatory monitoring to guarantee integrity, reliability, and ethical compliance. The renewable power sector has effectively used AI and DL to enhance grid reliability, enhance energy management, and detect faults. They have shown potential in two domains: optimizing waste management processes and statistical analysis in solar energy installations. The combination of a hybrid application of DL and AI systems has enhanced the availability of extensive spatial data to generate better exposure models and disease prediction. The AI-based technologies are supported in the sustainable energy field because surveys and real-life deployments point out that technologies decrease greenhouse gas emissions and power wastage and save on power. The study explores the status of AI and DL techniques to assess their possible uses to promote sustainable electricity options and environmental conservation, along with the SDGs.