Two-Stage Robust Optimization Scheduling of Park-Level Hydrogen-Electric Coupling Systems With Demand Response and Carbon Trading

ObjectivesHydrogen energy, as a clean energy source with high energy density and zero carbon emissions, is an important component of future energy systems. For park-level hydrogen-electric coupling systems (HECS), a two-stage robust optimization scheduling model that considers demand response and tiered carbon trading is proposed.MethodsFirst, a park-level HECS is established, consisting of wind and solar power generation units, backup generation units, energy storage systems, and hydrogen-electric conversion devices. Then, demand response and tiered carbon trading are integrated into the model, aiming to minimize the total costs of system energy procurement, operation and maintenance, and carbon emissions, thereby establishing a deterministic optimization model for the system. Finally, a source-load uncertainty set is incorporated into the deterministic optimization model to mitigate the effect of source-load uncertainty on scheduling results, forming a two-stage robust optimization model. This model is re-established using a master-slave framework and solved using the column-and-constraint generation method.ResultsWith source-load uncertainty coefficients of 12 and 6, demand response loads with an adjustable ratio below 0.5 can reduce the system's operating costs by 1.6%. The introduction of tiered carbon trading can reduce carbon emissions by 604.9 kg.ConclusionsThe proposed model can improve the risk resilience of park-level HECS, and the integration of demand response and tiered carbon trading can ensure the economic and low-carbon operation of HECS.