Day-ahead Optimized Scheduling of Wind Power Systems Incorporating Carbon Trading

In light of the "dual carbon" strategy and energy structure transformation, studying economic dispatch of power systems considering carbon trading mechanisms and wind power uncertainty is crucial. This paper presents an optimized dispatch model for wind power integrated power systems considering carbon trading mechanisms. Under the premise of ensuring stable power system operation, it constructs a dynamic optimized dispatch model that considers wind power costs and introduces carbon trading costs to further investigate the impact of wind power integration on grid operation. The Latin Hypercube Sampling method is used to simulate wind power uncertainty, clearly defining backup compensation costs for insufficient wind output and wind curtailment costs for excess output. By incorporating the carbon trading mechanism based on wind power’s impact on system dispatch, the model balances both low-carbon and economic performance. Finally, the model is validated using an IEEE-30 bus system, demonstrating improved wind power utilization and reduced system carbon emissions.