Optimizing Multi-Timescale Scheduling of Combined Cooling, Heating, and Power Systems Under Penalty-Reward Tiered Carbon Trading

As the penetration of global new energy into power systems increases, the impact of carbon trading on energy systems continues to grow. Therefore, it is crucial to study the effects of carbon trading mechanisms on the operational characteristics of power systems that include new energy sources. This paper focuses on China, the world’s largest energy-consuming economy, and proposes a multi-time-scale optimization scheduling method for a Combined Cooling, Heating, and Power (CCHP) system that considers a reward-penalty tiered carbon trading mechanism. This method effectively enhances the economic, environmental, and stability performance of the CCHP system. Firstly, the relationship between different carbon trading mechanisms and carbon trading volumes is analyzed to identify the carbon trading mechanism with the highest correlation to economic efficiency. Based on this analysis, a carbon trading model is introduced into the system’s economic dispatch strategy, constructing an economic model for the CCHP system under the influence of the carbon trading mechanism. While considering economic efficiency, this study also aims to improve system stability by proposing a multi-time multi-layer rolling optimization scheduling method. This method adjusts equipment output to respond to random fluctuations caused by uncertainties in energy sources and loads. The optimization results of the case study show that the introduction of the reward-penalty tiered carbon trading mechanism can reduce the carbon emissions of the park and improve economic performance. Additionally, the multi-time multi-layer rolling optimization scheduling effectively mitigates random fluctuations in supply and demand, ensuring stable system operation.