Artificial Intelligence‐Driven Flow Optimization in Renewable Energy Systems

Artificial intelligence (AI) is changing the scenario for renewable energy systems by enhancing fluid dynamics and energy management. This Chapter looks at how AI helps better manage fluid movements and energy in wind, hydroelectric, and solar power systems. In the field of wind energy, AI is improving the design of turbine blades through machine learning and computational fluid dynamics. This innovation helps to lower air resistance by 15–20%. It boosts energy production by as much as 12%. Artificial intelligence-powered pitch control systems can change the angle of the blades instantly to respond to different wind conditions. Predictive maintenance models are also in play, accurately predicting gear failures 92% of the time, which reduces unexpected downtime by 35%. In hydroelectric systems, AI enhances the modeling of fluid flow, which helps to reduce energy losses caused by turbulence. When AI is combined with high-performance computing, it speeds up fluid dynamics simulations, cutting down design times by 25–40%. Artificial intelligence improves the management of power networks by matching energy production with demand, leading to a 30% increase in forecast accuracy. In solar power, AI-optimized trackers change the direction of solar panels in real-time, which increases energy collection by 20%. In hybrid systems that use both wind and solar energy, AI helps maintain a steady power supply by balancing the energy coming from each source. Even with these improvements, issues like low data quality and expensive computing remain. Future studies should look into physics-informed AI models to better optimize renewable energy systems, making them more efficient and scalable.