Benchmarking and contribution analysis of carbon emission reduction for renewable power systems considering multi-factor coupling

The renewable power system serves as a vital path towards achieving carbon peaking and neutrality goals. Accurately quantifying the carbon reduction emissions of renewable power systems and evaluating the contribution of various influencing factors to carbon reduction is quite important, which is related to the formulation of energy policies and regional power planning by the power grid or relevant departments. However, in the current research, there are few studies related to the quantification of carbon emission reduction, and in terms of optimal scheduling, the existing studies often only consider a single factor, ignoring the coupling effect between multiple factors, which makes the contribution of each optimization strategy to carbon emission reduction unclear. Therefore, based on the current power system scheduling mechanism and dual-carbon background, this paper optimizes the carbon emission reduction benchmark factor and its corresponding weight, proposes a new carbon emission reduction benchmark of renewable power system, and verifies the accuracy of this benchmark based on the classical scheduling model. On this basis, the mathematical models of thermal power deep peak shaving (DPS), electricity export (ELE) and green certificate trading (GCT) are established. Each factor is introduced into the classical scheduling model to simulate and verify the promoting effect of each influencing factor on carbon emission reduction. Finally, the above different influencing factors were constructed in different coupling scenarios to calculate the carbon emission reduction under each scenario, and the contribution degree of each influencing factor to carbon emission reduction was analyzed sharply according to the value of cooperation game instead of the traditional calculation method. The results show that the proposed benchmark can reduce the error by 2.6%-15.5 %. In the carbon emission reduction contribution simulation, the three factors have coupling effects, and deep peak shaving and electricity export are more sensitive to carbon emission reduction contribution. This study provides valuable insights for the development of carbon reduction strategies for renewable power systems.