2. Methodology. Two sets of algorithms are designed to enable realtime coal change and type detection in a power plant. First, a Semisupervised Cascaded Clustering (SSCC) algorithm is designed for extracting coal classes from the historical sensor and coal label data from the plant, in a nonreal time manner.
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Estimation of coal Gross Calorific Value based on various analyses by random forest method ... based briquette due to the HCl gas increases the fixed carbon content of biocharbased briquette in the preparation process. When industrial hemp stems and polyvinyl chloride at the ratio of 1:1, the maximum high heating value of biocharbased ...
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This calorific value measurement technology based on NIRSXRF is safe, fast, and stable, providing a new way to optimize and control the utilization process of coal in coal washing plants, power ...
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The GCV, or higher heating value (HHV), is an indicator of chemically stored energy content of a coal [7, 8].It is usually a decisive parameter in the assessment of the value of the coal and thereby provides a basis for its purchase agreement [9, 10].GCV is the amount of energy released during the combustion of a coal.
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The bio coal had a calorific value of MJ/kg, moisture content of %, fixed carbon of % and ash content of %. The properties of the bio coal make it makes it usable as an alternative to coal and can be reintegrated back into the sugar processing industry as a substitute to coal. © 2018 The Autho s.
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The objective of this study was to compare different statistical algorithms for estimating the calorific value of coal based on a quantitative analysis of the elements in coal. Laserinduced breakdown spectroscopy (LIBS) was applied for the elemental analysis. Three different algorithms, including the correlation analysis (CA) method, the partial least squares (PLS) analysis method, and the ...
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Abstract. The higher heating value (HHV) of 84 coal samples including hard coals, lignites, and anthracites from Russia, Colombia, South Africa, Turkey, and Ukrania was predicted by multilinear regression (MLR) method based on proximate and ultimate analysis data. The prediction accuracy of the correlation equations was tested by Analysis of variance method. The significance of the predictive ...
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The present research work proposes an optimization procedure using Taguchi method and utility concept with the main objective of maximizing the calorific value of syngas with lower CO2 yield during coal gasification process using thermodynamic equilibrium model based on stoichiometric approach. After validating the model with experimental results, the effect of air supply and steam supply on ...
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N2 The purpose of this study was to enhance the accuracy of the calorific value estimation of coal by applying data preprocessing methods in laserinduced breakdown spectroscopy (LIBS). The SavitzkyGolay (SG)smoothing and SG derivative preprocessing methods were adopted to improve the accuracy of the prediction model.
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Estimation of Calorific Value of the Fuel ... (GCV) assumes all vapour produced during the combustion process is fully condensed. It is the total amount of heat produced, when unit mass/volume of the fuel has been burnt ... Factors affecting calorific value Calorific value of coal varies from one coal sample to another. It depends on the ash ...
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The study offers a detailed cost analysis of Coal Production from Surface Mining. In addition, the report incorporates the manufacturing process with detailed process and material flow, operating costs along with financial expenses and depreciation charges. Details: Germany based plant Q2 2023 From USD.
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second is Hua Ting coal, Ning Xia coal has lowest calorific value. In group A, the calorific value of coal was hardly increased, while the calorific value of the coal in group B and group C increased. It is not necessary to improve the calorific value after the coal blending, there is a problem of the optimum ratio.
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Abstract. New prediction models based on wavelet neural networks (WNNs) have been proposed to estimate the gross calorific value (GCV) of coals. The input sets for the prediction models are involved of the proximate and ultimate analysis components of coal and the oxide analyses of ash. The coal samples, which have been employed to develop and ...
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Slovenian coal and estimation of coal heating value based on proximate analysis using regression and artificial neural networks. Central European Journal of Chemistry, 2013;
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fuels. In India, coal as a fuel constitutes more than 50% of the total fossil fuel mix, used for energyrelated activities. Countryspecific CO 2 emission factors derived on the basis of the net calorific values1 (NCVs) of the different types of coal produced in the country, namely, coking, noncoking, and lignite have been used in this assessment.
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PDF | Coal quality is generally defined based on the ash contents. It is well known that the calorific value of coal is negatively affected by the... | Find, read and cite all the research you ...
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Request PDF | On Mar 16, 2016, Sahar Matin and others published Estimation of coal gross calorific value based on various analyses by random forest method | Find, read and cite all the research ...
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1. Introduction. Consumption of fossil fuels continues to grow, although there are signs that the rate of growth may be slowing [1].Also the abundance and versatility of coals makes a vital role for it in nowadays industrial fields like cement making and conversion to coke for the smelting of iron ore [2], [3].. The calorific value (CV) as an indicator of the chemically stored energy in coal ...
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In India utilities usually get coal from multiple sources and coal is priced essentially on the basis of gross calorific value (GCV). During combustion, GCV contributes only to the maximum possible heat release, though heat release rate is mostly controlled by coal proximate parameters ash, volatile matter, moisture and fixed carbon ...
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The purpose of this study was to enhance the accuracy of the calorific value estimation of coal by applying data preprocessing methods in laserinduced breakdown spectroscopy (LIBS). The SavitzkyGolay (SG)smoothing and SG derivative preprocessing methods were adopted to improve the accuracy of the prediction model. The relationship among the original, SGsmoothingpretreated, and SG ...
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In order to estimate the calorific value and measure the sulfur concentration, a new powerful technique for mixed coals was studied. Laserinduced breakdown spectroscopy (LIBS) does not require ...
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and calorific data collected from the coalbased industrial analysis data of each coalfired power plant, the drybased carbon content is weighted to calculate the content of the drybased carbon. And then calculate the carbon content per unit calorific value, and finally calculate the total CO 2 emissions in the past 5 years. It
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This study proposes a new combined estimation equation for the calorific value of coal. The modeling process in this study consists of two stages. In Stage1, a highperformance gross calorific value (GCV) prediction equation is developed using the Group Method Data Handling type Neural Network (GMDHtype NN) method based on proximate analysis ...
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There are a number of formulae proposed in the literature to estimate the calorific value of biomass fuels from its elementary components by proximate, ultimate and chemical analysis composition.
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Abstract. The calorific value of coal is important in both the direct use and conversion into other fuel forms of coals. Accurate calorific value predicting is essential in ensuring the economic, efficient, and safe operation of thermal power plants. Least squares support vector machine (LSSVM) is a variation of the classical SVM, which has ...
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In this study, the gross calorific value (GCV) of coal was accurately and rapidly determined using eight artificial intelligence models based on big data of 2583 observations of coal samples in the Mong Duong underground coal mine (Vietnam). Accordingly, the volatile matter, moisture, and ash were considered as the key variables (inputs) for determining GCV. Seven artificial neural network ...
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However, relatively lower calorific value, coupled with high ash content and inefficient combustion technologies aggravates emission of greenhouse gases and other pollutants from India's coal and lignite based thermal power plants. Main emissions from coal fired and lignite based thermal power plants are CO. 2, NO. x, SO. x, and
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The determination of operational parameters in the underground coal gasification (UCG) process should be considered in two aspects: first, the total coal in each UCG panel must be gasified and second, the calorific value of the produced gas should be acceptable. The main aim of this study is to present a model that meets these aspects and increasing the calorific value of syngas during this ...
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يرغب أحد موردي المواد من بلجيكا في إنتاج مسحوق الحجر الجيري لملابسه...
الهند غنية بالموارد المعدنية المختلفة وهي سوق مهم لمعالجة المعادن
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