Reducing CO2 emissions and energy consumption of heat-integrated distillation systems.

Distillation systems are energy and power intensive processes and contribute significantly to the greenhouse gases emissions (e.g. carbon dioxide). Reducing CO2 emissions is an absolute necessity and expensive challenge to the chemical process industries in orderto meetthe environmental targets as agreed in the Kyoto Protocol. A simple model for the calculation of CO2 emissions from heat-integrated distillation systems is introduced, considering typical process industry utility devices such as boilers, furnaces, and turbines. Furnaces and turbines consume large quantities of fuels to provide electricity and process heats. As a result, they produce considerable amounts of CO2 gas to the atmosphere. Boilers are necessary to supply steam for heating purposes; besides, they are also significant emissions contributors. The model is used in an optimization-based approach to optimize the process conditions of an existing crude oil atmospheric tower in order to reduce its CO2 emissions and energy demands. It is also applied to generate design options to reduce the emissions from a novel internally heat-integrated distillation column (HIDiC). A gas turbine can be integrated with these distillation systems for larger emissions reduction and further energy savings. Results show that existing crude oil installations can save up to 21% in energy and 22% in emissions, when the process conditions are optimized. Additionally, by integrating a gas turbine, the total emissions can be reduced further by 48%. Internal heat-integrated columns can be a good alternative to conventional heat pump and other energy intensive close boiling mixtures separations. Energy savings can reach up to 100% with respect to reboiler heat requirements. Emissions of these configurations are cut down by up to 83%, compared to conventional units, and by 36%, with respect to heat pump alternatives. Importantly, cost savings and more profit are gained in parallel to emissions minimization.