Numerical Optimization of a Waste-to-Energy Plant Under Different Operating Conditions

The combustion process for using municipal solid waste (MSW) as a fuel within a waste-to-energy plant calls for a detailed understanding of the following phenomena. Firstly, this process depends on many input parameters such as MSW proximate and ultimate analysis, the season of the year, primary and secondary air-inlet velocity and, secondly, on output parameters such as the temperatures or mass-flow rates (MFR) of the combustible products. The variability and mutual dependence of these parameters can be difficult to manage in practice. Moreover, another problem is how these parameters can be tuned to achieving optimal combustion with minimal pollutant emissions during the initial plant-design phase. In order to meet these goals, a waste-to-energy plant with bed-combustion was investigated by using a computational fluid dynamics (CFD) approach with ANSYS CFX 12.0 code within a WORKBENCH 2 environment. In this paper, the adequate variable input boundary conditions based on the real measurement and practical calculations of known MSW composition compared with other authors are used and the whole computational work is updated using real plant geometry and the appropriate turbulence, combustion and heat transfer models. Furthermore, the operating parameters were optimized on output parameters through a trade-off study. The different operating conditions were varied and the fluid flow direction, residence time, temperature field, velocity-field, nitric oxide formation and combustion products through the plant’s combustion chamber and preheat intersection in 3D were predicted and visualized. Optimization in real-time has showed the amounts for each input parameter when meeting the optimal operating conditions. Finally, the response charts between the input and output parameters are presented in order to monitor the dependence among these parameters. Further simulations have to be done to include the geometry dimensions as input parameters when applying the CDF simulation and numerical optimization within the project phase.