Refinery Pre-Heat Train Network Simulation Undergoing Fouling: Assessment of Energy Efficiency and Carbon Emissions

Fouling in crude preheat trains in oil refineries causes additional fuel and production costs, operating difficulties, CO2 emissions, and safety issues. Crude oil fouling deposition mechanisms are still not well understood. Current exchanger design methodologies (based on empirical fouling factors), operating practices, and mitigation solutions (ranging from the use of chemical additives to tube inserts) do not prevent efficiency losses or disruption of operations. Moreover, current analysis and design methodologies neglect local effects and dynamics of fouling, in favor of lumped, steady-state, “averaged” heuristic models. In this paper, a dynamic and distributed model recently developed that accounts for localized fouling growth as a function of process conditions is used to simulate the dynamic behavior of the hot end of a refinery preheat train. The network is simulated by a simultaneous solution of all exchangers, combined according to a desired configuration, within gPROMS, a commercial dynamic simulation environment. The overall network model allows capturing some complex interactions within the network over time and enables the rigorous computation of several key indicators which are highly dependent on fouling. These include throughput reduction, additional energy requirements, and overall economic and CO2 emission impacts.