
Real-time optimization of PV output and storage scheduling, enhancing self-generation priority strategy

Large model predicts campus energy consumption curves, maximizing surplus electricity revenue

Edge controller integrates AI decision algorithms for second-level demand response and load optimization

Mining load characteristics based on LSTM algorithm, intelligently regulating commercial loads

AI-enhanced control algorithms embedded at the edge, ensuring power supply reliability

Regional energy router powered by large models, optimizing V2G strategies and carbon neutrality goals