Current legislation imposes tighter restrictions to reduce the impact of process industry on environment. This work presents the dynamic simulation and optimization results for an existing sulfuric acid plant. Operational problems may occur when the process is disturbed due to production rate changes or catalyst deactivation, the non-linear response of the plant leading to sustained oscillations. Since the plant is operated near full capacity, only minor increases in energy production can be achieved. However, the SO x emissions can be significantly reduced by ~40% or more, by optimizing the operating parameters.
IntroductionMost sulfuric acid plants are rather old and are facing now additional challenges that aim to maximize the amount of energy produced while reducing the environmental impact. Sulfuric acid is the chemical product manufactured in largest quantity in terms of mass, with about 40 million tons produced annually only in USA. It has a wide range of uses and plays an important role in the production of almost all manufactured goods. Approximately 65% of the H 2 SO 4 produced is used in the production of agricultural fertilizers. This study presents the results of the dynamic simulation and optimization of an existing sulfuric acid plant (PFI -Phosphoric Fertilizers Industry, Greece). Due to the partnership with Process Systems Enterprise Ltd. (PSE), and thanks to its powerful features, gPROMS was selected to perform all simulation tasks.1 The dynamic model developed in this study includes also a graphical user interface (GUI) built in MS Excel, that allows scenario evaluation and operator training. The model has been successfully used for dynamic simulations to evaluate the non-steady-state behavior of the plant and detect changes in product quality, as well as to minimize the total amount of sulfur oxides released in atmosphere. For the major units of the flowsheet, the main equations describing the dynamic model are given using the standard notation. Due to space limitations and model complexity, some modeling details were omitted but they are available upon request. Here we limit to present only the most important results of this study.