Maximizing load capacity factor through a carbon-neutral environment via a simulation of carbon peak

Carbon emissions are a global issue, especially among manufacturers, and China is facing many problems to lower such pollutants due to its goal of attaining carbon neutrality. This research applies a mathematical model to achieve the desired goal of decreasing CO2 with the innovation of carbon neutrality tools and by moving towards high quality under the load capacity factor (LCF). We adopt a simulation-based optimization approach at different carbon peaks and manipulate various scenarios in order to find the best decisions for carbon neutrality tools. The results indicate that the green innovation fund, CO2 emission tax, and CO2 emission cap have significant roles in maximizing LCF. First, the green innovation fund plays a crucial part in reducing carbon emissions. Second, a CO2 emission tax allows manufacturers to produce less than the green innovation fund and CO2 emission cap. Third, the CO2 emission cap strategy conversely allows manufacturers to produce more than the CO2 emission tax strategy. This study provides reference for policymakers to achieve carbon neutrality and for the government to determine the best carbon-neutral tools under carbon peak. Lastly, the findings help manufacturers maximize LCF and profit and clean up the environment.