Despite the lack of a global greenhouse gas emission reduction agreement, regional schemes are moving forward to limit CO2 and other GHG emissions to the atmosphere. In the United States, the state of California is moving forward with regulations that will cap emissions from installations producing over 25,000 tonne CO2e/year. Refinery energy generation equipment such as boilers and fired-heaters fall under this limit and will be obliged to reduce CO2 emissions.
The initial step for refineries to reduce CO2 emissions is through energy efficiency efforts. Reduced energy consumption results in lower CO2 emissions from the combustion of fossil fuels.
There are three types of energy efficiency projects: 1) equipment energy efficiency, where equipment is upgraded to more energy efficient ones; 2) operational energy efficiency, where operating strategies of energy-intense assets are optimized; and what we call 3) “chemical” energy efficiency, where energy efficiency is achieved through improved chemistry.
Often refineries run their gas treating units with the sole objective of meeting environmental compliance with sulfur emission limits. MEA (monoethanolamine) or DEA (diethanoalamine) are used to ensure complete removal of H2S from the refinery gas stream, and since these solvents often present corrosion issues, solvent concentration in water is maintained at a low level. In addition, solvent recirculation is kept high as an “insurance” against environmental excursions. This practice results in excessive energy consumption and subsequent excessive CO2 emissions.
There are two ways to reduce energy consumption in gas treating system. The first is taking a closer look at the system mass and energy balance and establish appropriate operating conditions and key performance indicators to reduce energy consumption while maintaining environmental performance. The second is upgrading the chemistry of the solvent to reduce water content while maintaining or improving H2S removal capabilities.
This paper will discuss these two approaches in more detail, including the use of simulators to determine optimum process conditions and the importance of continuous monitoring of process and solvent conditions. The paper will also share real field experience and learnings from actual implementation of these practices.
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