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

2021 ◽  
Vol 13 (16) ◽  
pp. 9015
Author(s):  
Quande Dong ◽  
Cui Wang ◽  
Shitong Peng ◽  
Ziting Wang ◽  
Conghu Liu
Keyword(s):  
Flue Gas ◽  
Power Plants ◽  
Mechanistic Model ◽  
Computational Cost ◽  
Kriging Model ◽  
Flue Gas Desulfurization ◽  
Pareto Optimal ◽  
Unit Load ◽  
Pareto Optimal Front ◽  
Desulfurization Process

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 mechanistic model poses a great challenge. In this regard, the present study optimized the eco-efficiency from the perspective of operating data analysis. We formulated the issue of eco-efficiency improvement into a many-objective optimization problem. Considering the complexity between the system inputs and outputs and to further reduce the computational cost, we constructed a Kriging model and made a comparison between this model and the response surface methodology based on two accuracy metrics. This surrogate model was then incorporated into the NSGA-III algorithm to obtain the Pareto-optimal front. As this Pareto-optimal front provides multiple alternative operating options, we applied the TOPSIS to select the most appropriate alternative set of operating parameters. This approach was validated using the historical operation data from the desulfurization system at a coal-fired power plant in China with a 600 MW unit. The results indicated that the optimization would cause an improvement in the efficiency of desulfurization and energy efficiency but a slight increase in the consumption of limestone slurry. This study attempted to provide an effective operating strategy to enhance the eco-efficiency performance of desulfurization systems.

The development of a genetic method to optimize the flue gas desulfurization process

2021 ◽  
Vol 26 (jai2021.26(1)) ◽  
pp. 59-73
Author(s):  
Fedorchenko I ◽  
◽  
Oliinyk A ◽  
Stepanenko A ◽  
Fedoronchak T ◽  
...  
Keyword(s):  
Sulfur Dioxide ◽  
Flue Gas ◽  
Power Plants ◽  
Electric Energy ◽  
Flue Gas Desulfurization ◽  
Adaptive Mutation ◽  
So2 Emissions ◽  
Genetic Method ◽  
Desulfurization Process ◽  
Using Data

Sulfur dioxide is one of the most commonly found gases, which contaminates the air, damages human health and the environment. To decrease the damage, it is important to control the emissions on power stations, as the major part of sulfur dioxide in atmosphere is produced during electric energy generation on power plants. The present work describes flue gas desulfurization process optimizing strategy using data mining. The optimisation modified genetic method of flue gas desulfurization process based on artificial neural network was developed. It affords to represent the time series characteristics and factual efficiency influence on desulfurization and increase its precision of prediction. The vital difference between this developed genetic method and other similar methods is in using adaptive mutation, that uses the level of population development in working process. It means that less important genes will mutate in chromosome more probable than high suitability genes. It increases accuracy and their role in searching. The comparison exercise of developed method and other methods was done with the result that new method gives the smallest predictive error (in the amount of released SO2) and helps to decrease the time in prediction of efficiency of flue gas desulfurization. The results afford to use this method to increase efficiency in flue gas desulfurization process and to decrease SO2 emissions into the atmosphere

scholarly journals Investigation of the emission control of sulfur trioxide aerosols based on heterogeneous condensation and the deflectors tray of the desulfurization tower

RSC Advances ◽  
2020 ◽  
Vol 10 (63) ◽  
pp. 38515-38523
Author(s):  
Rui Zhang ◽  
Xiaodong Si ◽  
Lingling Zhao ◽  
Linjun Yang ◽  
Hao Wu
Keyword(s):  
Flue Gas ◽  
Sulfur Trioxide ◽  
Emission Control ◽  
Flue Gas Desulfurization ◽  
Heterogeneous Condensation ◽  
Desulfurization Process

In this paper, control over the emission of sulfur trioxide aerosols was investigated based on heterogeneous condensation in the wet flue gas desulfurization process.

scholarly journals Study on SO3 Cooperative Removal Effect of Ultra-low Emission Technology in Coal-fired Power Plants

2018 ◽  
Vol 53 ◽  
pp. 04005 ◽  
Author(s):  
Ding Yang ◽  
Yi Luo ◽  
XingLian Ye ◽  
WeiXiang Chen ◽  
Jun Guo ◽  
...  
Keyword(s):  
Low Temperature ◽  
Flue Gas ◽  
Power Plants ◽  
Electrostatic Precipitator ◽  
Removal Rate ◽  
Flue Gas Desulfurization ◽  
Paper Briefly ◽  
Low Emission ◽  
Electrostatic Precipitators

SO3 is one of the main precursors of atmospheric PM2.5, and its emission has attracted more and more attention in the industry. This paper briefly analyzes the harm of SO3 and the method of controlled condensation to test SO3. The effect of cooperative removal of SO3 by ultra-low emission technology in some coal-fired power plants has been tested by using the method of controlled condensation. The results show that the cooperative removal of SO3 by ultra-low emission technology in coal-fired power plants is effective. The removal rate of SO3 by low-low temperature electrostatic precipitators and electrostatic-fabric integrated precipitators can be exceeded 80%, while the removal rate of SO3 by wet flue gas desulfurization equipment displays lower than the above two facilities, and the wet electrostatic precipitator shows a better removal effect on SO3. With the use of ultra-low emission technology in coal-fired power plants, the SO3 emission concentration of the tail chimney reaches less than 1 mg / Nm3.

Factors Affecting Slurry Oxidation in a Wet Flue Gas Desulfurization Process

2019 ◽  
Vol 145 (10) ◽  
pp. 04019058
Author(s):  
Shuangchen Ma ◽  
Fang Xu ◽  
Dongsheng Xu ◽  
Defeng Li ◽  
Yanfei Yu
Keyword(s):  
Flue Gas ◽  
Flue Gas Desulfurization ◽  
Factors Affecting ◽  
Desulfurization Process

Performance of sulfite/FeIIIEDTA fuel cell: Power from waste in flue gas desulfurization process

2019 ◽  
Vol 375 ◽  
pp. 122008 ◽  
Author(s):  
Seonjeong Cheon ◽  
Kwiyong Kim ◽  
Hyung Chul Yoon ◽  
Jong-In Han
Keyword(s):  
Fuel Cell ◽  
Flue Gas ◽  
Flue Gas Desulfurization ◽  
Desulfurization Process
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