Total site modeling and optimization for petrochemical low-carbon retrofits using multiple CO2 emission reduction methods

Aiming at the carbon dioxide (CO2) emissions from energy and material flow streams in petrochemical sites, a bi-objective optimization strategy based on retrofit improvements and total site techniques is constructed, which is referred to as the petrochemical CO2 emission reduction comprehensive (Petro-CERC) model. The fossil fuels for heat, steam and power provision, as well as the fossil-fired power importation are condsidered to shift to biomass fuel and renewable power in utilities and process units. A waste heat up-graded utilization system is introduced and adopted to improve the efficiency of heat energy, and a green combined heat and power system based on renewable and sustainable resources is established to reconstruct the conventional utility system. Carbon capture by the organic amine solvent absorption process is also integrated into the bi-objective optimization strategy. The CO2 emission reduction methods were applied individually to a petrochemical site in South China with an annual emission of 3.2 million tons CO2 for the sensitivity analysis. The proposed Petro-CERC model was then performed for the optimization of the combined application of the CO2 emission reduction methods. From the perspective of both carbon neutrality and economy, the optimal value at the trade-off point of CO2 emission is 464 thousand tons CO2/year, and the cost of achieving an 85% reduction of CO2 emission is $44.9 million. Further, the CO2 emission reduction strategies in different petrochemical sites are coupled with four different regions on a national scale according to the matching degree of the three standards of technical feasibility, economic development status and geographical appearance. Consequently, a multi-scenario application based on the four regions is applied in this case, and the feasibility of the CO2 emission reduction methods to achieve the near carbon neutral goal in these scenarios is evaluated.