A Linearized Optimization Model for Multiple Emissions Reduction in Power Generation Sector
- Type: Conference Presentation
- Conference Type: AIChE Spring Meeting and Global Congress on Process Safety
- Presentation Date: August 18, 2020
- Duration: 20 minutes
- Skill Level: Intermediate
- PDHs: 0.40
The power generation sector is considered as one of the major contributors to air pollution. There are different air emissions that can be emitted from power generation and among these are CO2, NOx and SOX emissions which will be the focus of this research. In this study, an optimization model was formulated and written in a general format. The objective of this model is to select the best pollution control strategy for the power generation to reduce all selected emissions to specific level while meeting the electricity demand at minimum cost. Three different mitigation options were considered t and these are: fuel balancing, switching and implementing different control technologies. The model was formulated as MINLP and linearized to have the global optimum solution. The results shows that applying FGD technology is the best option to reduce SO2 emissions and it can achieve up to 85% SO2 reduction but the cost will increase. For CO2, the best option was to apply capture technology. All of these results were obtained as a derision making support based on the specified reduction target.
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|AIChE Member Credits||0.5|
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|AIChE Undergraduate Student Members||Free|
|Computing and Systems Technology Division Members||Free|