Conference article

There is potential for optimizing thermal oxidizer plants to increase industrial energy efficiency results in environmental and economic dimension of sustainability. In the present work; genetic algorithm is implemented for three thermal oxidizer cases in three different petrochemical plants to optimize the fuel cost for the three Heat Recovery Steam Generators (HRSG’s) which are going to be used for the recovery of the heat from the outlet of the thermal oxidizer units. Generally; thermal oxidizers are used in petrochemical plants to burn waste gases in the plant to reduce the environmental impact of the off-gases of plant and normally the waste heat are released to the atmosphere via a stack. The optimization results have been compared for three cases. Five decision variables have been selected and the objective function was optimized. By increasing the fuel price; the values of thermo-economical decision variables tend to those thermodynamically optimal designs.

Heat Recovery Steam Generator (HRSG); thermo-economics; Optimization; Thermal Oxidizer; Genetic Algorithm; Low Density Polyethylene (LDPE) Plant