Innovative AI tools in Renewable Energy Sources

Abstract

The article analyzes the role of artificial intelligence (AI) in the renewable energy sources (RES) sector, highlighting its importance in optimizing energy production, distribution, and storage processes. AI enables precise forecasting of energy production, minimizing the effects of weather instability and increasing the operational efficiency of renewable energy systems by up to 25%. AI-based tools also allow for dynamic adjustment of wind turbines and photovoltaic panels, which reduces energy losses and operating costs. An important application of AI is predictive maintenance, which reduces failures through early detection of faults. Smart grid management enables the optimal use of renewable energy sources by analyzing demand and supply and integrating different energy storage technologies. AI also supports the planning of renewable energy investments, helping to select optimal locations for wind and solar farms. However, the implementation of AI in the energy sector faces challenges, such as the need for access to large data sets, the cost of integration with existing systems, and cybersecurity issues. Despite these barriers, the future of AI in RES looks promising, especially in the context of its integration with IoT, big data and quantum technologies. With the right technological and regulatory support, AI can become a key element of the global energy transition, increasing the stability and profitability of renewables and supporting the fight against climate change.