Neural Network Evaluation of Combustion Process for Continuous Control of Small Scale Biomass Fired Boilers

Vrána, Stanislav; Plaček, Viktor; Oswald, Cyril; Šulc, Bohumil; Neuman, P.

doi:10.3182/20140824-6-za-1003.00259

Cited by 7 publications

(2 citation statements)

References 9 publications

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“…Vrána et al had evaluated the combustion process for small scale biomass fired boilers. The control algorithm applied for these boilers provided optimal efficiency with minimum impact on the environment [5]. Garcíaa et al had studied the size-up, monitor, and performance optimization of a 120 kW capacity boiler.…”

Section: Introductionmentioning

confidence: 99%

Multi-response optimization of the characteristics of wooden fuel sources for boiler applications

Karthick¹,

Saravanan²,

Moshi³

et al. 2023

Bull. Chem. Soc. Eth.

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ABSTRACT. Various kinds of biomass fuels are used for boiler and other kinds of thermal applications. The presence of moisture, ash and calorific value are known to be the most significant quality factors which influence the effective performance of a biomass fuel for a plant. The reasons for measuring the above mentioned quality factors are to perform the economic analysis and to control the combustion. The relevant industries are interested to obtain a method for predicting these quality factors quickly and consistently; and also to identify biomass fuels containing optimal level of these factors. In the present work, five different biomass fuels have been considered such as rubber wood, eucalyptus wood, mixed wood (tamarind tree and neem tree woods), palm shell with fiber and juliflora woodchips. The moisture content in the considered woods have been found to be 27.74 wt.%, 37.78%, 30.19 wt.%, 23.26 wt.% and 37.01 wt.% respectively. The main objective of this work is to maximize the efficiency of production. Grey relational analysis has been carried out to optimize the moisture content, ash content and calorific value in order to achieve cost savings and fuel efficiency. Also, the economic analysis has been done with the operational costs. KEY WORDS: Biomass, Fuels, Energy, Boiler, Optimization Bull. Chem. Soc. Ethiop. 2023, 37(4), 1055-1064. DOI: https://dx.doi.org/10.4314/bcse.v37i4.20

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Section: Introductionmentioning

confidence: 99%

Multi-response optimization of the characteristics of wooden fuel sources for boiler applications

Karthick¹,

Saravanan²,

Moshi³

et al. 2023

Bull. Chem. Soc. Eth.

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“…So there is a need to achieve simultaneously controlled values of the required boiler heat output and optimal conditions for the combustion process from both the efficiency and emissions point of view [4][5][6]. Therefore, the operation of biomass-fired boilers has to be properly controlled using a classical cascade [7] and also advanced control algorithms and methods [8,9] with the possibility of on-line system monitoring [10].…”

Section: Introductionmentioning

confidence: 99%

Using Special Filter with Membership Function in Biomass Combustion Process Control

et al. 2018

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The paper deals with the special filtration method using a filter with membership function. The paper presents a model of a filter, its specific characteristics and some parameters that have an impact on quality of filtration. A filter with different membership functions (Gauss, Bell, Power and Triangle) was designed and tested for specific demands, which followed from the experience with the realization of a biomass combustion control system. Data obtained from the combustion process were extremely noisy (influenced by various transfer errors, disturbances and external interferences) and, therefore, had to be properly filtered. The paper also describes some results of filter simulation in the Matlab Simulink environment and its implementation into an on-line monitored process control system of biomass combustion. It was proven by implementation that such a filter can be useful for the signal filtering of oxygen concentration and carbon monoxide emission sensing and it can be very useful in reducing signal interferences arising in biomass combustion.

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Image-based deep neural network prediction of the heat output of a step-grate biomass boiler

2017

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Neural Network Evaluation of Combustion Process for Continuous Control of Small Scale Biomass Fired Boilers

Cited by 7 publications

References 9 publications

Multi-response optimization of the characteristics of wooden fuel sources for boiler applications

Multi-response optimization of the characteristics of wooden fuel sources for boiler applications

Using Special Filter with Membership Function in Biomass Combustion Process Control

Image-based deep neural network prediction of the heat output of a step-grate biomass boiler

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