Research of coupling technologies on NOx reduction in a municipal solid waste incinerator

Yang, Xucong; Liao, Yanfen; Wang, Yuqing; Chen, Xinfei; Ma, Xiaoqian

doi:10.1016/j.fuel.2021.122769

Cited by 16 publications

(2 citation statements)

References 44 publications

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“…Sections 3 and 4 are combustion grates. When passing through them, the waste starts to burn vigorously, the thickness of the layer is reduced, and the combustion temperature is generally above 700 • C [27]. The fifth section is a cooling section; the combustible part of the garbage in this section has been basically burned.…”

Section: Structure Of Grate-type Waste Incineratormentioning

confidence: 99%

Predictions of the Key Operating Parameters in Waste Incineration Using Big Data and a Multiverse Optimizer Deep Learning Model

Zhao,

Zhou,

et al. 2023

Sustainability

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In order to accurately predict the key operating parameters of waste incinerators, this paper proposes a prediction method based on big data and a Multi-Verse Optimizer deep learning model, thus providing a powerful reference for controlling the optimization of the incinerator combustion process. The key operating parameters that were predicted, according to the control objectives, were determined to be the steam flow, gas oxygen, and flue temperature. Firstly, a large amount of measurement data were collected, and 27 relevant control system parameters with a high correlation with the predicted variables were obtained via a mechanism analysis. The input variables of the prediction model were further determined using the improved WesselN symbolic transfer entropy algorithm. The delay time between the variables was found using a gray correlation coefficient, the prediction time was determined to be 6 min according to the delay time distribution of the flame feature, and the time delay compensation was applied to each parameter. Finally, the support vector machine was optimized using a Multi-Verse Optimization algorithm to complete the prediction of the key operating parameters. Experiments showed that the root mean square error of the proposed model for the three output variables—the steam flow, gas oxygen, and flue temperature—were 0.3035, 0.2477, and 1.6773, respectively, which provides a high accuracy compared to other models.

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Section: Structure Of Grate-type Waste Incineratormentioning

confidence: 99%

Predictions of the Key Operating Parameters in Waste Incineration Using Big Data and a Multiverse Optimizer Deep Learning Model

Zhao,

Zhou,

et al. 2023

Sustainability

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“…In a SNCR process, the reagent converts NOx into nitrogen and water vapor through reactions without catalysts. Because a catalyst is not used, a reducing agent is injected at high temperature (900–1100 °C) to achieve the activation energy required for the reaction [ 6 ]. Therefore, SCR technology is widely used as a NOx reduction process to comply with the emission regulations.…”

Section: Introductionmentioning

confidence: 99%

Recent trends in vanadium-based SCR catalysts for NOx reduction in industrial applications: stationary sources

Jeong

Lee

et al. 2022

Nano Convergence

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Vanadium-based catalysts have been used for several decades in ammonia-based selective catalytic reduction (NH3-SCR) processes for reducing NOx emissions from various stationary sources (power plants, chemical plants, incinerators, steel mills, etc.) and mobile sources (large ships, automobiles, etc.). Vanadium-based catalysts containing various vanadium species have a high NOx reduction efficiency at temperatures of 350–400 °C, even if the vanadium species are added in small amounts. However, the strengthening of NOx emission regulations has necessitated the development of catalysts with higher NOx reduction efficiencies. Furthermore, there are several different requirements for the catalysts depending on the target industry and application. In general, the composition of SCR catalyst is determined by the components of the fuel and flue gas for a particular application. It is necessary to optimize the catalyst with regard to the reaction temperature, thermal and chemical durability, shape, and other relevant factors. This review comprehensively analyzes the properties that are required for SCR catalysts in different industries and the development strategies of high-performance and low-temperature vanadium-based catalysts. To analyze the recent research trends, the catalysts employed in power plants, incinerators, as well as cement and steel industries, that emit the highest amount of nitrogen oxides, are presented in detail along with their limitations. The recent developments in catalyst composition, structure, dispersion, and side reaction suppression technology to develop a high-efficiency catalyst are also summarized. As the composition of the vanadium-based catalyst depends mostly on the usage in stationary sources, various promoters and supports that improve the catalyst activity and suppress side reactions, along with the studies on the oxidation state of vanadium, are presented. Furthermore, the research trends related to the nano-dispersion of catalytically active materials using various supports, and controlling the side reactions using the structure of shaped catalysts are summarized. The review concludes with a discussion of the development direction and future prospects for high-efficiency SCR catalysts in different industrial fields.

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Effects of flue gas recirculation on the thermal performance of the gas remediation well

Feng

Fan

et al. 2023

Applied Thermal Engineering

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Research of coupling technologies on NOx reduction in a municipal solid waste incinerator

Cited by 16 publications

References 44 publications

Predictions of the Key Operating Parameters in Waste Incineration Using Big Data and a Multiverse Optimizer Deep Learning Model

Predictions of the Key Operating Parameters in Waste Incineration Using Big Data and a Multiverse Optimizer Deep Learning Model

Recent trends in vanadium-based SCR catalysts for NOx reduction in industrial applications: stationary sources

Effects of flue gas recirculation on the thermal performance of the gas remediation well

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