مدل سازي و بهينه سازي تك هدفه مصرف انرژي و توليد آلاينده هاي گازي در يك مجموعه توليد هم زمان حرارت - توان پالايشگاهي

Single-objective Modeling and Optimizing Energy Consumption and Emission of Gaseous Pollutants in a Refinery Heat and Power Cogeneration System

In this research the modeling and optimizing of energy consumption in a refinery heat and power cogeneration system has been investigated. The thermo-dynamical modeling of main part of the system includes the co-firing boiler, gas turbine and steam turbine. In the boiler modeling by using equations of perfect gas, combustion of the liquid and gaseous fuels has been considered in the stoichiometric conditions and also by using the additional air coefficient in real conditions, separately. The model of the gaseous pollutants resulting from the combustion process in the condition of the boiler furnace has been corrected by observing the thermodynamical and aerodynamical conditions of the boiler. In the case of gas and steam turbines, the fundamental thermodynamic concepts and available experimental information from resources have been used to calculate the relations between the rate of the transitional operative fluid mass and useful output power. After validation of presented model, the optimization of energy consumption and emission of gaseous pollutants in a refinery heat and power cogeneration system have been considered. By introducing the independent variants of system and considering their operational limitations, optimum choice is obtained with considering the expense factors of energy consumption and emission of gaseous pollutants. By determining the thermal and electrical requirements of a refinery cogeneration system and selecting the data, the results of modeling represents the validation of presented models for equipments and proper coherence of used equation in the system. Finally, single objective optimization of energy consumption and emission of gaseous pollutants have been investigated by selecting the independent variants of the system. The results have been compared to determine the variance of the selection of the purpose function which is the most important basis of the optimization process.