A Many-Objective Optimization for an Eco-Efficient Flue Gas Desulfurization Process Using a Surrogate-Assisted Evolutionary Algorithm

A Many-Objective Optimization for an Eco-Efficient Flue Gas Desulfurization Process Using a Surrogate-Assisted Evolutionary Algorithm

The flue gas desulfurization process in coal-fired power plants is energy and resource-intensive but the eco-efficiency of this process has scarcely been considered. Given the fluctuating unit load and complex desulfurization mechanism, optimizing the desulfurization system based on the traditional...

Full description

Bibliographic Details
Main Authors: Quande Dong, Cui Wang, Shitong Peng, Ziting Wang, Conghu Liu
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sustainability
Subjects:
data-driven modeling
many-objective optimization
NSGA-III
Kriging model
eco-efficiency
Online Access:https://www.mdpi.com/2071-1050/13/16/9015

Internet

https://www.mdpi.com/2071-1050/13/16/9015

Similar Items