November 22, 2024
Reza Azin

Reza Azin

Academic Rank: Professor
Address: -
Degree: Ph.D in -
Phone: -
Faculty: Faculty of Petroleum, Gas and Petrochemical Engineering

Research

Title
Improvement of Energy Efficiency in Gas Condensate StabilizationUnit: Process Optimization Through Exergy Analysis
Type Presentation
Keywords
Condensate stabilization, Exergy analysis, Energy optimization, Process modeling, CO2emissions
Researchers Abdollah hajizade (First researcher) , Mohamad Mohamadi-Baghmolaei (Second researcher) , Fatemesadat Mirghaderi (Third researcher) , Reza Azin (Fourth researcher) , Sohrab Zendehboudi (Fifth researcher) , Taghi Sanaei (Not in first six researchers) , Sajjad Keshavarzian (Not in first six researchers)

Abstract

Gas condensate stabilization is a common process in gas refineries and petrochemical industries. Thisprocess is energy-consuming since it uses distillation columns and furnaces to separate different cutsfrom the condensate feed. This study aims to improve the performance of the gas condensate stabilizationunit in a large petrochemical company in terms of energy efficiency and loss prevention. The case underinvestigation is the gas condensate stabilization unit in the Nouri Petrochemical Company, treating 568 t/hof raw condensate feed. This plant includes two distillation columns, two furnaces, pumps, heat exchangers,and air coolers. A hybrid energy and exergy analysis is conducted in this study. First, the validation of thesimulation phase is performed, and a parametric sensitivity analysis is conducted to explore the effects ofvarious parameters, such as operating temperature and pressure, on the process performance. After that,the most influential variables are identified using thermodynamic analyses for optimization and designpurposes. An optimization method is employed to attain the maximum production improvement and exergyefficiency. The exergy analysis shows 187.4 MW total exergy destruction in the plant; furnaces account for79% of the total exergy destruction. According to the sensitivity analysis results, the energy consumptionof the process could be reduced by 33.7 MW; this is an 18% reduction in the plant's energy consumption.The optimal process conditions outperform the current and design states (4.6% improvement in exergyefficiency). The fuel gas consumption is reduced by 2.1 t/h, leading to a reduction of 128 t/d CO2 emissions