Optimized Scheduling Model for Integrated Energy Systems under Carbon Trading Mechanisms
Research findings on Sustainable Energy highlight the effectiveness of an optimized scheduling model for integrated energy systems (IESs) under carbon trading mechanisms. The model, developed by a team of researchers from North China Electric Power University, successfully integrates vehicle-to-grid (V2G) technology and demand response (DR) mechanisms to reduce total costs and carbon emissions. The study found that the introduction of the carbon trading mechanism and DR mechanism leads to a reduction of 19.59% in total costs and 18.41% in carbon emissions, respectively. Furthermore, when the V2G mechanism is incorporated, the total costs and carbon emissions are further reduced by 19.25% and 16.46%, respectively.
Key Takeaways:
- The optimized scheduling model developed by the researchers integrates V2G technology and DR mechanisms to reduce total costs and carbon emissions.
- The model reduces total costs by 19.59% and carbon emissions by 18.41% when the carbon trading mechanism and DR mechanism are introduced.
- Incorporating the V2G mechanism further reduces total costs by 19.25% and carbon emissions by 16.46%.
- The study found that the introduction of the carbon trading mechanism leads to a reduction in total costs and carbon emissions.
- The model was developed by a team of researchers from North China Electric Power University, with funding from the National Natural Science Foundation of China and other organizations.
Statistics:
- 19.59% reduction in total costs when the carbon trading mechanism and DR mechanism are introduced.
- 18.41% reduction in carbon emissions when the carbon trading mechanism and DR mechanism are introduced.
- 19.25% reduction in total costs when the V2G mechanism is incorporated.
- 16.46% reduction in carbon emissions when the V2G mechanism is incorporated.
Sources:
- Digital Journal: New Study Details Findings on Sustainable Energy (2025). [1]
- NewsRx: New Findings in Sustainable Energy Described from North China Electric Power University (2025). [2]
Note: [1] and [2] are external sources and may be accessed at the provided URLs or alternatively through academic databases.