Estimation of gross calorific value of coal: A literature review

被引：5
作者：
Vilakazi, Lethukuthula [1 ]
Madyira, Daniel [2 ]
机构：
[1] Tshwane Univ Technol, Mech & Mechatron Engn Dept, Pretoria, South Africa
[2] Univ Johannesburg, Mech Engn Sci Dept, Johannesburg, South Africa
来源：
INTERNATIONAL JOURNAL OF COAL PREPARATION AND UTILIZATION | 2025年 / 45卷 / 02期
关键词：
Coal; gross calorific value; higher heating value; proximate and ultimate analysis; HIGHER HEATING VALUE; NEURAL-NETWORKS; PREDICTION; REGRESSION; RADIATION; MODELS;
D O I：
10.1080/19392699.2024.2339340
中图分类号：
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号：
0807 ; 0820 ;
摘要：
The gross calorific value (GCV), also known as the higher heating value (HHV) of coal is the amount of heat emitted upon complete combustion of coal. The GCV of coal is used to estimate various technoeconomic parameters such as boiler efficiency, combustion values, and production costs. This study seeks to examine the methods that are used to estimate the GCV of coal. These methods can be classified as either mathematical, experimental, or online methods." It was found that linear and non-linear regression, differential scanning calorimetry (DSC), artificial intelligence (AI) methods have all been frequently used to estimate the GCV. The challenge with these approaches is that they include sophisticated machinery that demand expert operation, and the task is time consuming. Accurate and timely analysis of the GCV coal is a crucial stage in power plants, which can be achieved with online monitoring of the GCV of coal. There is not much literature on the topic of online monitoring of the coal GCV because it hasn't been studied extensively. In power plant operation, online monitoring of the GCV of coal is a promising technology that hasn't been studied extensively.
引用
收藏
页码：390 / 404
页数：15
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