Multi-Objective Sustainable Operational Optimization of Fluid Catalytic Cracking

Fluid Catalytic Cracking (FCC) constitutes a critical process in petroleum refining, facing increasing pressure to align with sustainable development goals by improving energy efficiency and reducing environmental impact. This study tackles a multi-objective optimization challenge in FCC operations,...

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Bibliographic Details
Published in:Sustainability Vol. 17; no. 22; p. 10045
Main Authors: Pang, Shibao, Lin, Yang, Shi, Hongxun, Yin, Rui, Tao, Ran, Li, Donghong, Li, Chuankun
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.11.2025
Subjects:
Algorithms
Backup software
Carbon
Catalytic cracking
Emission standards
Emissions
Emissions (Pollution)
Energy consumption
Energy efficiency
Environmental impact
Gasoline
Greenhouse gases
Mathematical optimization
Neural networks
Optimization
Pareto optimum
Petroleum
Petroleum refineries
Profits
Refining
Sustainability
Sustainable development
Variables
China
ISSN:2071-1050, 2071-1050
Online Access:Get full text
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Summary:Fluid Catalytic Cracking (FCC) constitutes a critical process in petroleum refining, facing increasing pressure to align with sustainable development goals by improving energy efficiency and reducing environmental impact. This study tackles a multi-objective optimization challenge in FCC operations, seeking to simultaneously maximize the gasoline production and minimize the coke yield—the latter being directly linked to CO2 emissions in FCC. A data-driven optimization model leveraging a dual Long Short-Term Memory architecture is developed to capture complex relationships between operating variables and product yields. To efficiently solve the model, an Improved Multi-Objective Whale Optimization Algorithm (IMOWOA) is proposed, integrating problem-specific adaptive multi-neighborhood search and dynamic restart mechanisms. Extensive experimental evaluations demonstrate that IMOWOA achieves superior convergence characteristics and comprehensive performance compared to established multi-objective algorithms. Relative to the yields before optimization, the proposed methodology increases the gasoline yield by 0.32% on average, coupled with an average reduction of 0.11% in the coke yield. For the studied FCC unit with an annual processing capacity of 2.6 million tons, the coke reduction corresponds to an annual CO2 emission reduction of approximately 10,277 tons, delivering benefits to sustainable FCC operations.
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ISSN:2071-1050
2071-1050
DOI:10.3390/su172210045