Machine-Learning-Assisted Multi-Energy Coupling and Battery–Grid Coordination for Deep Decarbonization of Smart Integrated Energy Systems: Modeling, Optimization, and Applications
A machine-learning-assisted, renewable-driven framework for multi-energy coupling and scenario-based multi-objective optimization of electricity–heat–hydrogen–storage systems and provides a data-driven modeling and decision framework for battery–grid coordination and deep decarbonization in smart integrated energy syst...