Desulfurize the algorithmic way

People who fly into a rage always make a bad landing. -- Will Rogers

Algorithms are all the rage. A previous post titled Of algorithms and roses highlighted an article articulating the what and why of our algorithmic obsession.

The theme of today’s post: Consider designing a Google® search using algorithm + a keyword of your choice.

For example ...
Google® algorithm desulfurization

TIP: Try this technique using other hot topics. Here are some examples ...

robotic desulfurization
artificial intelligence desulfurization
big data desulfurization

The results may surprise you. They may even inspire you. They energized me.

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About 441,000 results (0.44 seconds)

Data-Based Optimal Tracking Control for Natural Gas ...
Oct 23, 2019 - In this paper, a data-based adaptive dynamic programming (ADP) algorithm is presented to solve optimal control for natural gas desulfurization.
by W Zhou - ‎2019 - ‎Related articles
Abstract:
Desulfurization control of natural gas has long been a challenging industrial issue owing to its inherent difficulty in establishing accurate mathematical model for the nonlinear and strong coupling process. In this paper, a data-based adaptive dynamic programming (ADP) algorithm is presented to solve optimal control for natural gas desulfurization. First, neural network (NN) is used to reconstruct the dynamics of the desulfurization system via the input and output production data. Then, an improved unscented Kalman filter (IUKF) aided ADP method is presented to solve optimal control problem for desulfurization system, where IUKF algorithm is developed as a new weight-updating strategy for the action network and the critic network. The IUKF aided algorithm can improve the convergence speed as well as the anti-interference ability of the ADP controller. Furthermore, the proposed IUKF-ADP algorithm is implemented using the heuristic dynamic programming (HDP) structure. Finally, the effectiveness of the proposed IUKF-ADP algorithm is demonstrated through experiments of the natural gas desulfurization system.
Free full text source: https://ieeexplore.ieee.org/document/8880683
Free full text source: https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8880683

J Zhu - ‎2015 - ‎Cited by 33 - ‎Related articles
A concise algorithm for calculating absorption height in spray tower for wet limestone–gypsum flue gas desulfurization
Article in Fuel Processing Technology 129:15–23 · January 2015 with 140 Reads 
Jie Zhu, Shi-chao Ye, Jie Bai, Zhen-yuan Wu
Abstract
In this paper, a concise model for wet limestone–gypsum flue gas desulfurization system with spray tower has been presented, aiming at the prediction of the absorption height in a spray tower. The equations of droplet motion and mass balance were incorporated and developed to simulate the droplet movement, distribution and mass transfer of SO2 in the absorption section. The calculation results were in good agreement with the plant values of the absorption height. The influences of operating parameters on the absorption height were analyzed. The results show that absorption height declines with increasing liquid–gas ratio and pH value of the slurry, and increases with increasing droplet diameter, gas flow rate, gas temperature, inlet SO2 concentration and absorption efficiency, respectively. As the most sensitive parameter, the droplet diameter is crucial for the good prediction of absorption height. This model can provide engineering guidance to design a spray tower absorber.
source: https://www.researchgate.net/publication/265387013_A_concise_algorithm_for_calculating_absorption_height_in_spray_tower_for_wet_limestone-gypsum_flue_gas_desulfurization

Design of the Algorithm on the Flue Gas Desulfurization Controller
Article in International Journal of Control and Automation 9(8):233-240 · August 2016 with 2 Reads 
Qing-hua Shang, Su Wang, He-long Zhang, Xin-yue Zhao
Abstract
In view of the low speed and precision of the flue gas desulfurization system, this paper presents a hybrid method with parameter self adjustment. Through the analysis of the control system of flue gas desulfurization of flue gas and the transfer function of the object, and established the control system of flue gas desulfurization, perturbation models obtained a new flue gas desulfurization of the mixed sensitivity controller algorithm, simulation by Matlab show that this algorithm has certain advantages compared with at present commonly used algorithm.
source: https://www.researchgate.net/publication/307916349_Design_of_the_Algorithm_on_the_Flue_Gas_Desulfurization_Controller

Jan 6, 2020 - Based upon a design of experiment algorithm, the petcoke matrix, the evolved gases and the residue coke breeze were monitored by energy‐ ...
by K Pourabdollah - ‎2020 - ‎Related articles
RESEARCH ARTICLE Free Access
Optimization of operating conditions in desulfurization of petroleum coke using induction heating
Kobra Pourabdollah, Masoud Samadian Zakaria, Seyed Mohammad Mir Najafizadeh
Abstract
The matrix structure and properties of petcoke samples can be impressed by uniform and in situ thermal treatment. In this work, a novel hyphenated thermal approach was applied to investigate the ferromagnetic‐based desulfurization of petcoke samples and the effect of controlling parameters. Induction heating furnace and capillary gas chromatography (CGC) were designed and assembled to study the thermal desulfurization of ferromagnetic petcoke, which was prepared by penetration of some metallic elements (e.g., Fe, Cr, and Ni) into the coke framework. Based upon a design of experiment algorithm, the petcoke matrix, the evolved gases and the residue coke breeze were monitored by energy‐dispersive X–ray spectroscopy mapping, CGC, and electrical resistivity measurements. The results revealed that during petcoke formation, ferromagnetic metals were diffused and distributed throughout the coke matrix leading to the acceleration of the induction heating in the second stage of thermal treatment. Moreover, the evolved gas analysis showed the role and the rank of drainage rate, particle size, desulfurization temperature, induction frequency, and feed humidity parameters on the yield of desulfurization process. The effect of magnetic desulfurization on the specific electrical resistivity of coke breeze was identified as an industrial opportunity to be used in the cathodic protection systems.
1 INTRODUCTION
The majority of calcination processes are conducted in rotary furnaces1 in contact with atmospheric oxygen. However, there are many circumstances that the calcination process must be performed in the absence of oxygen such as the calcination of heterogeneous catalysts2-4 and the calcination of coke particles. During coke calcination, the desulfurization degree depends mainly on the final temperature, the sulfur content, and the chemical structure of sulfur‐containing compounds.
Desulfurization of coke breeze is carried out via nonthermal and thermal methods. Some examples of the nonthermal methods are including ammonia‐assisted desulfurization,5 desulfurization by recycling coking oven gas,6 and blowing additional gas.7 On the other hand, sulfur loss during calcination of coke samples is typically referred to thermal desulfurization, and it is known that sulfur loss increases as the calcination temperature increases. Morsi and Ibrahim8 published a review of thermal desulfurization and claimed that the main sulfur‐containing compounds in coke structure bound to the carbon matrix. The sulfur content of raw coal has been investigated to be pyrite (~50%), sulfate (~20%), thiophene (~20%), and elemental sulfur (~10%). However, after thermal desulfurization, it becomes pyrite (~40%), sulfate (~34%), thiophene (~16%), elemental sulfur (~7%), and sulfoxide (~3%).9 Hence, it is obvious that in thermal desulfurization, the sulfur content from the pyrite decreases significantly, whereas the sulfated sulfur increases.
On the other hand, the induction heating of synthesized MgFe2O4 particles has been reported at inert atmosphere and frequency of 265 kHz, whereas the aim was not desulfurization.10 Treatment and purification of Ti─Al alloys,11 iron,12 cobalt, nickel, and titanium13 as well as extraction of noble gases14 and preparation of expansible graphite15 have been well reported in the literatures. Likewise, the desulfurization of carbon saturated iron has been investigated in induction furnace by sodium carbonate and sodium sulfate16; however, the induction heating of coke breeze has not been reported because of its diamagnetic properties. The coke matrix has been studied when Fe─Si particles was doped into blast furnace coke.17 Diffusion of ferromagnetic elements changes the diamagnetic property of coke breeze to ferromagnetic and improves the induction heating capability of the produced matrix.
The goal of this work is the presentation of a novel hyphenated approach in order to investigate the effect of controlling parameters on ferromagnetic‐based desulfurization of petcoke. In this paper, the ferromagnetic coke samples were synthesized, and their effect on induction heating and sulfur reduction of coke matrix was discussed. The ferromagnetic matrix of coke samples was thermally diffused with ferromagnetic elements of Fe, Ni, and Cr. The experiments were conducted by a continuous‐feed induction furnace equipped with a cylindrical graphite susceptor and a product‐cooling heat exchanger. The results revealed that the impregnation of the abovementioned ferromagnetic elements enhances the coke heating rate leading to increasing the temperature of coke breeze and improve the desulfurization process.
Free full text source: https://onlinelibrary.wiley.com/doi/full/10.1002/apj.2398

A concise algorithm for calculating absorption height in spray tower for wet limestone–gypsum flue gas desulfurization
Article in Fuel Processing Technology 129:15–23 · January 2015 with 140 Reads 
Jie Zhu, Shi-chao Ye, Jie Bai, Zhen-yuan Wu
Abstract
In this paper, a concise model for wet limestone–gypsum flue gas desulfurization system with spray tower has been presented, aiming at the prediction of the absorption height in a spray tower. The equations of droplet motion and mass balance were incorporated and developed to simulate the droplet movement, distribution and mass transfer of SO2 in the absorption section. The calculation results were in good agreement with the plant values of the absorption height. The influences of operating parameters on the absorption height were analyzed. The results show that absorption height declines with increasing liquid–gas ratio and pH value of the slurry, and increases with increasing droplet diameter, gas flow rate, gas temperature, inlet SO2 concentration and absorption efficiency, respectively. As the most sensitive parameter, the droplet diameter is crucial for the good prediction of absorption height. This model can provide engineering guidance to design a spray tower absorber.
source: https://www.researchgate.net/publication/265387013_A_concise_algorithm_for_calculating_absorption_height_in_spray_tower_for_wet_limestone-gypsum_flue_gas_desulfurization

Improved FGD Operation Efficiency with Self-Tuning Predictive APC-Software
Dr. Volker Stephan, Christoph Möller STEAG Energy Powitec GmbH, Germany Dr. Peter Deeskow STEAG Energy Services GmbH, Germany
Created for the fair “POWER-GEN Europe” and presented   on June 7th 2014 in Cologne
1 Motivation
Efficiency is a very common objective in today’s power plant operation. Much work and effort are spent to optimize the combustion, heat transfer, heat recovery, turbine and generator performance. On the other side, every power station also has a considerable power consumption on its own. To minimize its own demands for electricity will also increase the power plants efficiency. In this paper we will describe a new approach to optimize the FGD operation of the hard-coal fired 560MW power plant Walsum 9 in Germany. In this plant, a wet scrubbing flue gas desulfurization (FGD) is used, which consumes in average about 2.4MW of  electricity, because considerable mass flows of the scrubbing reagent (limestone) need to be pumped to the spray nozzles usually located at different elevations in a vertical spray tower.
2 Problem Description
The flue gas desulfurization system (in German abbreviated “REA”) in the Walsum 9 power station was originally built for sulfur removal of two blocks. It is a wet scrubber system that uses limestone solvent to absorb the SO2. Its design for two blocks resulted in a very powerful and flexible structure featuring many degrees of freedom to operate that aggregate. As figure 1 shows, there are two independent desulfurization subsystems each featuring five pumps feeding the reagents into the SO2 -absorber at five different elevations of spray nozzles.
Free full text source: https://www.steag.com/uploads/pics/Paper_APC_Improved_FGD_Operation_Efficiency_eng.pdf

Modeling and optimization of wet flue gas desulfurization system based on a hybrid modeling method
Yishan Guo, Zhewei Xu, Chenghang Zheng, Jian Shu, Hong Dong, Yongxin Zhang, show all
Pages 565-575 | Received 19 Jul 2018, Accepted 12 Nov 2018, Accepted author version posted online: 30 Nov 2018, Published online: 13 Mar 2019
ABSTRACT
Sulfur dioxide (SO2) is one of the main air pollutants from many industries. Most coal-fired power plants in China use wet flue gas desulfurization (WFGD) as the main method for SO2 removal. Presently, the operating of WFGD lacks accurate modeling method to predict outlet concentration, let alone optimization method. As a result, operating parameters and running status of WFGD are adjusted based on the experience of the experts, which brings about the possibility of material waste and excessive emissions. In this paper, a novel WFGD model combining a mathematical model and an artificial neural network (ANN) was developed to forecast SO2 emissions. Operation data from a 1000-MW coal-fired unit was collected and divided into two separated sets for model training and validation. The hybrid model consisting a mechanism model and a 9-input ANN had the best performance on both training and validation sets in terms of RMSE (root mean square error) and MRE (mean relative error) and was chosen as the model used in optimization. A comprehensive cost model of WFGD was also constructed to estimate real-time operation cost. Based on the hybrid WFGD model and cost model, a particle swarm optimization (PSO)-based solver was designed to derive the cost-effective set points under different operation conditions. The optimization results demonstrated that the optimized operating parameters could effectively keep the SO2 emissions within the standard, whereas the SO2 emissions was decreased by 30.79% with less than 2% increase of total operating cost.

Implications: Sulfur dioxide (SO2) is one of the main pollutants generated during coal combustion in power plants, and wet flue gas desulfurization (WFGD) is the main facility for SO2 removal. A hybrid model combining SO2 removal mathematical model with data-driven model achieves more accurate prediction of outlet concentration. Particle swarm optimization with a penalty function efficiently solves the optimization problem of WFGD subject to operation cost under multiple operation conditions. The proposed model and optimization method is able to direct the optimized operation of WFGD with enhanced emission and economic performance.
Introduction

Sulfur dioxide (SO2) is one of the major pollutants contributing to frequent hazy weather in China. A large amount of SO2 in the atmosphere comes from coal combustion. As the amount of coal for power generation accounts for 45% of the total coal consumption in 2015 (National Bureau of Statistics [NBS] 2017), the Chinese government has specified the importance of pollutant emissions of coal-fired power plants and emission limits have been tightened (Ministry of Environmental Protection of PRC 2011). Owing to the advantages such as a high desulfurization efficiency and proper adaptation to various types of coal, wet flue gas desulfurization (WFGD) has been widely adopted. More than 80% of the power plants in China are using WFGD as their main method for desulfurization (Wang and Hao 2012).

In the flue gas treatment systems in coal-fired power plants, WFGD systems are commonly installed downstream of the electrostatic precipitators (Sui et al. 2016) and the pressure charging fans, operating at positive pressure. Exhaust flue gas enters the WFGD system from the entrance, which is located at the lower part of the tower. The exhaust gas comes into mass transfer and chemical reactions in countercurrent mode with the limestone slurry droplets, which are introduced through injection nozzles of three to five spray stages in the higher part of the tower. SO2 in the flue gas is absorbed by slurry droplets, reacts with calcium carbonate (CaCO3), and produces CaCO3, which is oxidized to calcium sulfate (CaSO4) before crystallized into gypsum and separated from the slurry.

Aimed at enhanced environmental and economic performance of WFGD, modeling and optimization of SO2 removal in WFGD has been a subject of research in recent years. Mathematical models of WFGD, basing on the microlevel mass transfer theories, including penetration theory (Brogren and Karlsson 1997), surface renewal theory (Gerbec, Stergarsek, and Kocjancic 1995; Zhong et al. 2008), stagnant-film theory (Warych and Szymanowski 2001, 2002), and two-film theory (Dou et al. 2009; Kallinikos et al. 2010; Neveux and Le Moullec 2011; Zhu et al. 2015b), and reaction kinetics, including chemical absorption (Neveux and Le Moullec 2011), gypsum conversion (Tan et al. 2017), and limestone dissolution (Carletti et al. 2015), have been comprehensively studied and shown good agreement with experimental and industrial results. At the same time, data-driven models, based on the large amount of operating data and machine learning platforms, are also generated using various methods such as artificial neural networks (ANNs) (Ren, Sun, and Deng 2012; Warych and Szymanowski 2002) and regression analysis (Hou, Bai, and Yin 2013), results of which have shown a good forecasting performance.

In this paper, different forms of prediction models are studied, and a hybrid modeling method of WFGD is proposed. A comprehensive cost model for industrial WFGD is built before particle swarm optimization (PSO) with a penalty function designed for the optimization of WFGD. A case study is carried out based on the operation data from a 1000-MW unit, and the performance of model prediction and operation optimization is analyzed. Modeling and optimization results proved that the optimized operating parameters are able to minimize the total operating cost, with SO2 emissions meeting the emission standards.
Free full text source: https://www.tandfonline.com/doi/full/10.1080/10962247.2018.1551252
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Jean Steinhardt served as Librarian, Aramco Services, Engineering Division, for 13 years. He now heads Jean Steinhardt Consulting LLC, producing the same high quality research that he performed for Aramco.

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