scholarly journals Technical requirements regarding the equipment of reciprocating engines in mine gas utilisation, especially for gases with low contents of methane

2006 ◽  
Vol 125 (2) ◽  
pp. 3-9
Author(s):  
Guido DROSTE

Some basic constructional features of generating sets produced by DEUTZ Power Systems equipped with gas engines fueled with air – Coal Mine Methane mixture have been presented in the paper. The way of preparing of air-gas mixture, gas set up and ignition ability have been described here. Some operation features of gensets with Deutz TCG 2032 have been discussed.

2001 ◽  
Vol 123 (02) ◽  
pp. 46-51
Author(s):  
Michael Valenti

Manufacturers of fuel cells are working to improve the economics of electrochemical devices to make them more competitive with conventional fossil fuel power systems for industrial plants and vehicles. FuelCell Energy of Danbury, Connecticut, is designing a system to convert polluting coal mine methane into electricity. General Electric MicroGen of Latham, New York, plans to introduce a residential fuel cell system by the end of the year to provide remote homes with backup current and heat. Another residential system is being developed by International Fuel Cells of South Windsor, Connecticut. The Department of Energy’s National Energy Technology Laboratory in Morgantown, West Virginia, is sponsoring a program to determine the feasibility of feeding coal mine methane to fuel cells. The program involves building a 250-kilowatt fuel cell system at the Nelms mining complex operated by Harrison Mining Corp. in Cadiz, Ohio. A fuel cell system planned for the Nelms complex will assist these automotive engines in consuming methane emissions while generating electricity.


2017 ◽  
Vol 204 ◽  
pp. 1526-1534 ◽  
Author(s):  
Jing Cai ◽  
Chun-Gang Xu ◽  
Zhi-Ming Xia ◽  
Zhao-Yang Chen ◽  
Xiao-Sen Li

2014 ◽  
Vol 68 ◽  
pp. 253-259 ◽  
Author(s):  
R. Hernández-Gómez ◽  
D. Tuma ◽  
M.A. Villamañán ◽  
M.E. Mondéjar ◽  
C.R. Chamorro

2016 ◽  
Vol 97 ◽  
pp. 137-141 ◽  
Author(s):  
Fernando J. Pérez-Sanz ◽  
M. Carmen Martín ◽  
César R. Chamorro ◽  
Teresa Fernández-Vicente ◽  
José J. Segovia

Fuel ◽  
2021 ◽  
Vol 305 ◽  
pp. 121467
Author(s):  
Namrata Gaikwad ◽  
Jitendra Sangwai ◽  
Praveen Linga ◽  
Rajnish Kumar

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

Author(s):  
Huaming Dai ◽  
Huiwei Zhu ◽  
Pan Yang ◽  
Hongchao Dai ◽  
Song He ◽  
...  

ACS Omega ◽  
2021 ◽  
Author(s):  
Jianhua Fu ◽  
Dengke Wang ◽  
Xuelong Li ◽  
Zhiming Wang ◽  
Zhengjie Shang ◽  
...  

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.


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