7 Quantum machine learning in renewable energy systems
Yash Mahajan, Muskan Sharma, Abdullah Alzahrani · 2024
The transition to renewable energy sources is crucial in combating climate change, but it presents challenges such as intermittency and grid integration. Quantum Machine Learning (QML) emerges as a promising technology to address these obstacles. This chapter explores the intersection of QML and renewable energy systems, highlighting its potential to optimize energy grid design, improve energy storage solutions, and enhance predictive modeling of renewable resources. By simulating quantum systems, QML facilitates the discovery of optimal renewable energy materials and enhances energy storage technologies. This chapter investigates the transformative potential of QML in shaping a sustainable energy future.