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 ...
Gross calorific value (GCV) is one of the essential parameters for evaluating coal quality. Therefore, accurate GCV prediction is one of the primary ways to improve heating value as well as coal ...
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 ...
The estimation of β is denoted by B LS and calculated from (2) Y ^ = XB LS where Y ^ denotes estimation of coal calorific value. According to the least squares principle, B LS should minimize the value of ‖ YY ^ ‖ 2, and the solution of B LS is (3) B LS = (X ′ X)1 X ′ Y. Nonlinear regression modeling
The calorific value of a coal, which is usually termed the higher heating value (HHV) (also termed as the gross calorific value, GCV), is an important property for its use as a fuel. HHV is defined as the amount of heat released when a unit mass of the fuel is burnt completely, and the combustion products are cooled under standard conditions.
for Zonguldak coal is proposed. According to the proposed prediction method, calorific value is strongly related to ash content of each coal sample. In other words, one can easily estimate the calorific value of a coal with defined ash content. Correlation between measured and predicted calorific values is statistically significant (R2=).
This study aims to develop a globally valid prediction model for coal higher heating value (HHV) for the first time, and the Gaussian process regression method is performed to build the model. ABSTRACT This study aims to develop a globally valid prediction model for coal higher heating value (HHV). For the first time, the Gaussian process regression (GPR) method is performed to build the ...
the input of sulfur, hydrogen, total water and analytic water; the high calorific value, low calorific value and cartridge calorific value of coal can be calculated automatically [910]. The difference between high calorific value and low calorific value lies in whether the water in fuel combustion products is liquid or gaseous. Water is liquid ...
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.
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.
They concluded that three parameters (C, N and O) were enough to estimate the calorific value well. In recent years, many models predicting the calorific value of coal were established, which were based on machine learning methods including wavelet neural networks [9], artificial neural networks [10] and support vector regression [11].
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 ...
Price Chart Historical Data News. Newcastle coal futures increased to 128 per tonne as demand from China is set to rise as temperatures are falling. China's thermal coal imports for November are anticipated to reach approximately million metric tons, surpassing October's million and trailing only May's million, as per ...
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 ...
Timely monitoring of the calorific value of coal is beneficial to combustion regulation during the operation of coalfired power plants. An insitu measurement system applied to power plants was ...
Slovenian coal and estimation of coal heating value based on proximate analysis using regression and artificial neural networks. Central European Journal of Chemistry, 2013;
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 ...
Coal from Bangko, South Sumatra is a low rank coal which has the potential to be used as activated carbon material. The result of proximate analysis and calorific value of coal shows that Bangko coal is included in the lignite category, with fixed carbon %, volatile matter % and calorific value 4915 Cal/g.
gross calorific value is equal to or greater than 24 000 kJ/kg on an ashfree but moist basis. If bituminous coal is used in coke ovens it should be reported as coking coal. 2. Subbituminous coal: Nonagglomerating coal with a gross calorific value equal to or greater than 20 000 kJ/kg and less
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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 ...
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 ...
The calorific value of solid fuels, also referred to as the gross calorific value (GCV) or the higher heating value (HHV), is a crucial property for its use as a fuel in energy systems. The HHV of coal as a resource can be predicted by more effective algorithms that use schedule information in engineering, like ultimate analysis, enabling fast ...
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 ...
Mason conducted research work on 775 coal samples of all rank types and proposed an empirical relationship for estimating the calorific value of coal from ultimate analysis result and on further analysis with Dulong's, [19, 20] and formula, it has been found that data set gave poorer result.
India, the world's third largest coal producing country, is expected to maintain strong dependency on coal for the coming few decades. The gross calorific value (GCV) of coal is a key yardstick ...
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 ...
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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