COMPUTATIONAL SIMULATION FOR POLLUTANT EMISSION REDUCTION IN COMBUSTION PLANTS

Partner: ORGREZ

field: the energy industry

The company ORGREZ provides services and supplies in several fields of power and thermal engineering, generally in the processes of fuel energy conversion and electricity production and distribution. The Division for Ecology Systems deals with greenhouse gas issues and air protection technologies, both in terms of technologies for regulating and reducing pollutant emissions and systems for monitoring and evaluating pollutant emissions, especially CO₂, NO_X, and ash.

The objective of IT4Innovations was to determine whether Computational Fluid Dynamics (CFD) simulations could be used for both the fast and efficient description of the Selective Catalytic Reduction (SCR) process, and therefore as a tool to mediate the design of a computational application for the design of this technology. It belongs to the group of DeNO_x technologies used to achieve the required reduction of the concentration of nitrogen oxides (NO, NO₂, N₂O) in the exhaust gases of combustion plants to the required level given by the applicable emission limits of specific combustion plants.

Numerical simulation of the SCR represents a complex definition of a given thermochemical process, for which one of the key issues is the definition of the inlet boundary conditions. CFD simulation of the combustion process and measured field data can be used as a source for these conditions’ parameters. The SCR model was tested on the geometry of a coal combustion boiler and project design data specified by the catalyst manufacturer, with a waste incineration boiler selected and municipal waste as the fuel. The CFD simulation resulted in a numerical description of the process of NO_X concentration reduction, additional oxidation of CO to CO₂, and conversion of SO₂ to SO₃. Currently, the design of the SCR plant is based on experience and simplified semi-empirical calculations. However, the use of numerical modelling and simulations will make the process more efficient and faster. Moreover, and most importantly, it will extend the application possibilities of the process, allowing subsequent optimisation of the designed solution and, thanks to high-performance computing, these simulations can be completed in a relatively short time.