Low carbon scheduling optimization of integrated energy system in high altitude area based on information gap decision theory

A low-carbon scheduling model for Tibetan region addresses high-altitude oxygen demand, heat-energy contradiction, wind power curtailment, and pollution. It integrates CSP, GSHP, P2G-CCS to optimize electricity, heat, and oxygen production. Employing IGDT mitigates uncertainties, ensuring a robust solution. Using CPLEX for optimization, the model validates its effectiveness through simulation, offering a comprehensive approach to sustainable energy management.