Combustion Characteristics of Coal Mine Methane in a Preheated-Burner Packed with Raschig Rings

Author(s):  
Huaming Dai ◽  
Huiwei Zhu ◽  
Pan Yang ◽  
Hongchao Dai ◽  
Song He ◽  
...  
2015 ◽  
Vol 90 ◽  
pp. 489-498 ◽  
Author(s):  
Huaming Dai ◽  
Baiquan Lin ◽  
Kaige Ji ◽  
Chaoqun Wang ◽  
Qingzhao Li ◽  
...  

2014 ◽  
Vol 24 (5) ◽  
pp. 671-676 ◽  
Author(s):  
Baiquan Lin ◽  
Huaming Dai ◽  
Chaoqun Wang ◽  
Qingzhao Li ◽  
Ke Wang ◽  
...  

2014 ◽  
Vol 28 (6) ◽  
pp. 3688-3695 ◽  
Author(s):  
Jun Ren ◽  
Chuanjin Xie ◽  
Xuan Guo ◽  
Zhifeng Qin ◽  
Jian-Ying Lin ◽  
...  

2019 ◽  
Vol 6 (8) ◽  
pp. 473-478 ◽  
Author(s):  
Jianxiong Sheng ◽  
Shaojie Song ◽  
Yuzhong Zhang ◽  
Ronald G. Prinn ◽  
Greet Janssens-Maenhout

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3049
Author(s):  
Marek Borowski ◽  
Piotr Życzkowski ◽  
Klaudia Zwolińska ◽  
Rafał Łuczak ◽  
Zbigniew Kuczera

Increasing emissions from mining areas and a high global warming potential of methane have caused gas management to become a vital challenge. At the same time, it provides the opportunity to obtain economic benefits. In addition, the use of combined heat and power (CHP) in the case of coalbed methane combustion enables much more efficient use of this fuel. The article analyses the possibility of electricity production using gas engines fueled with methane captured from the Budryk coal mine in Poland. The basic issue concerning the energy production from coalbed methane is the continuity of supply, which is to ensure the required amount and concentration of the gas mixture for combustion. Hence, the reliability of supply for electricity production is of key importance. The analysis included the basic characterization of both the daily and annual methane capture by the mine’s methane drainage system, as well as the development of predictive models to determine electricity production based on hourly capture and time parameters. To forecast electricity production, predictive models that are based on five parameters have been adopted. Models were prepared based on three time variables, i.e., month, day, hour, and two values from the gas drainage system-capture and concentration of the methane. For this purpose, artificial neural networks with different properties were tested. The developed models have a high value of correlation coefficient. but showed deviations concerning the very low values persisting for a short time. The study shows that electricity production forecasting is possible, but it requires data on many variables that directly affect the production capacity of the system.


2017 ◽  
Vol 105 ◽  
pp. 4983-4989 ◽  
Author(s):  
Jing Cai ◽  
Chungang Xu ◽  
Zhiming Xia ◽  
Zhaoyang Chen ◽  
Xiaosen Li

2021 ◽  
Vol 86 ◽  
pp. 103733
Author(s):  
Zhen Lou ◽  
Kai Wang ◽  
Jie Zang ◽  
Wei Zhao ◽  
Binbin Qin ◽  
...  

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