AI Technologies Applied to Energy Systems and Smart Grids

Dear Colleagues,

Energy systems and smart grids are essential assets in addressing the urgent challenges posed by climate change and global warming. To mitigate these risks, smart grids must effectively integrate diverse energy system technologies, including renewable sources, while also managing the inherent complexities of the grid. Renewable energy sources, such as solar energy and wind power, are highly variable and unpredictable, which introduces new challenges in balancing supply and demand. Additionally, grid constraints, such as transmission limits and the need for real-time adjustments, make managing energy flow even more complex.

In this context, the design and management of optimized energy systems, along with advanced smart grids and energy storage solutions, become crucial. These systems must be not only competitive in the market but also provide the reliability and robustness typically associated with traditional fossil fuel-based power generation technologies. Energy storage systems play a vital role in stabilizing the grid by storing excess energy during periods of low demand and releasing it when needed.

Artificial intelligence (AI) plays a key role in optimizing these systems by handling the vast number of variables involved, including fluctuating energy production, grid constraints, and real-time demand. AI-driven algorithms are capable of learning from historical data, predicting future trends, and making real-time decisions to balance the grid efficiently. This level of intelligence allows smart grids to adapt dynamically to changing conditions, offering a higher degree of flexibility and reliability than conventional systems. The integration of AI into optimization algorithms thus ensures that energy systems are not only efficient but also resilient, contributing to the broader goal of sustainability. 

Dr. Jacopo Carlo Alberizzi
Dr. Luciano De Tommasi
Guest Editors

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