Reliability, Market Dynamics, and Energy Trading With AI in Wind Energy

Abstract

This chapter explores artificial intelligence's transformative impact on wind energy, addressing intermittency challenges to enhance reliability, market integration, and trading efficiency. As wind power expands to meet decarbonization goals, supplying over one-third of global electricity by 2050, its variability strains grids and markets, incurring balancing costs and penalties. The analysis dissects reliability issues, highlighting AI's role in predictive maintenance via machine learning on SCADA data for failure anticipation, deep learning for real-time fault detection using convolutional neural networks, and adaptive controls to minimize downtime and extend asset life. These advancements shift operations from reactive to proactive, leveraging vast datasets to predict and prevent disruptions. It then examines electricity market dynamics, where forecast errors lead to imbalances