Artificial Intelligence
Powering the Future of Renewable Energy
Jhon Quiñones (TU Delft - Electrical Engineering, Mathematics and Computer Science)
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Abstract
Artificial Intelligence (AI) is rapidly transforming renewable energy systems by optimizing performance, enhancing reliability, and supporting the global transition toward sustainability. Historically, energy systems evolved from centralized fossil fuel based grids toward decentralized renewable solutions, driven by environmental concerns, world conflicts, and technological advancements. The recent emergence of AI has accelerated this evolution, enabling advanced analytics, intelligent forecasting, and automated decision-making processes. AI techniques, such as machine learning, deep neural networks, and reinforcement learning, now play crucial roles in improving several procesess such as, the efficiency and predictability of solar and wind energy production, hydropower operations, marine energy systems, bioenergy optimization, and geothermal energy management. Furthermore, AI-driven system-level integration is essential for integrating intermittent renewable sources into existing grids, ensuring balance, stability, and cost-effectiveness. Policy-making and financial decisions leverage AI for risk assessment, scenario analysis, and strategic planning, facilitating informed investments and robust policy frameworks. This chapter explores how AI is not merely enhancing but reshaping renewable energy systems, highlighting its potential for achieving global energy and environmental goals.