Process Simulation and Optimization of Heat Pump Assisted Distillation Based Condensate Stabilization Unit

Abstract

The phenomena of global warming caused by excessive greenhouse gas emissions, particularly carbon dioxide gas, has seriously impacted many significant areas of human life. Over the last 30 years, the oil and gas sector has caused a gradual increased in terms of its carbon dioxide gas emission by a large portion. This research aims to conduct a conceptual study of techno-economic to compare heat pump-assisted distillation technologies against the conventional distillation method. This research has the objective of significantly reducing the utility consumption demand in the form of heating load and electrical power requirement, as well as minimizing the emission of carbon dioxide gas generated from gas turbine generator and steam boiler units. This research consists of a base case model that implements the conventional distillation method for the condensate stabilization process, while both optimized 1 and 2 implement heat pump-assisted distillation technologies, in the form of mechanical vapor recompression (in optimized model 1) and heat integrated distillation (in optimized model 2). All simulation models were prepared using process simulation software ASPEN HYSYS at steady state conditions with Peng-Robinson as a fluid package. The economic analysis conducted was based on a minimum feasibility estimate of class V with an accuracy of -30% / +50%. Optimized models 1 and 2 were able to reduce the total duty requirement by 23.68 % and 26.70 % compared to the base case model, thus causing a reduction in the OPEX by 51.11 % and 24.23 %. In line with the reduction of total duty requirement, the carbon dioxide gas emission rate for optimized models 1 and 2 has also decreased by 22.78 % and 36.18 % compared to the base case model. Furthermore, despite the slight increase in CAPEX, optimized models 1 and 2 still shows a positive trend in terms of their economic valuation, with a reduction in TAC compared to the base case model by 14.88 % and 4.86 % respectively.