(88d) Pressure-Driven Dynamic Simulation for Flare Minimization and Greenhouse Gas Reduction during an Ethylene Plant Startup

Flare emissions release volatile organic compounds (VOCs) and pollutants into the atmosphere, which react with nitrous oxide in sunlight to generate ground-level ozone and smog. A typical start-up of an ethylene plant flares approximately 5.0 million lbs of raw materials and generates at least 15.4 million lbs of CO_², 40.0 Klbs CO, 7.4 Klbs NOx, 15.1 hydrocarbons, and 100.0 Klbs HRVOCs. Hence, managing flare emission during startup, shutdown and malfunction (SSM) of an ethylene plant are very important. Flare source reduction approach employs simulation and optimization, emphasizes the upstream section of flare system and the whole plant integration, in which more upstream modification and optimization contribute in limiting unwanted products.

In this study, rigorous flow-driven and pressure-driven dynamic models of a front-end De-Ethanizer ethylene plant with sulfur recovery unit are constructed to serve as an optimization platform during plant startup. Since off-specification streams are inevitable during plant turnaround operations, to significantly reduce flaring emission, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the plant manufacturing returns to stable operation. Thus, the off-spec products will be able to be reused instead of being flared. Besides, charged gas compressor (CGC) startup is reportedly the most critical step and has largest amount of vent gas. Several scenarios of CGC feed at different flow rates and compositions are examined to find the least flaring one.  The pressure-driven model is utilized to investigate the inlet conditions at CGC suction, thus, guarantee the feasibility of the proposed startup strategy. These results serve as a basis for emission calculation and greenhouse gas study such as CO₂ control. The process can be considered from smaller scale (sectional model) to more comprehensive scale (whole plant model). The best results in these case studies are incorporated and validated in the integrated model of the whole plant in order to stabilize the system in the shortest time while minimizing material and energy loss.