Statistical analysis of industry scale up draft coal gasifier using response surface methodology for sustainable development
<p>Radhe Renewable Energy Pvt. Ltd, Rajkot has developed an updraft hot filtration type coal gasifier technology with a coal consumption capacity of approximately 35 metric tons daily for various industrial applications. This gasifier is intended to provide clean fuel gas for a porcelain insul...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Academy Publishing Center
2024-10-01
|
| Series: | Renewable Energy and Sustainable Development |
| Online Access: | http://apc.aast.edu/ojs/index.php/RESD/article/view/940 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | <p>Radhe Renewable Energy Pvt. Ltd, Rajkot has developed an updraft hot filtration type coal gasifier technology with a coal consumption capacity of approximately 35 metric tons daily for various industrial applications. This gasifier is intended to provide clean fuel gas for a porcelain insulator manufacturing plant at Bikaner Ceramics, Rajasthan. The present study represents a series of experiment runs that are designed and performed to observe the influence of two operating variables, specifically equivalence ratio (ER) and steam coal ratio (SCR), and their interactions on the performance evaluating parameters of gasifier like higher heating value, cold gas and carbon conversion efficiency for Indonesian coal. Steam coal ratio varies between 0.2 to 0.6 and the equivalence ratio within varies between 0.2 to 0.4 maximizing the coal gasification process which results in produced syngas with higher HHV up to 22.32 MJ/kg, improved CGE up to 84.90%, and enhanced CCE up to 97.90%. However, the increase in O<sub>2</sub> concentration with more air supply promotes the conversion of CO to CO<sub>2</sub> and enhances H<sub>2</sub>O percentages in the syngas quality. The excess O<sub>2</sub> tends to react with CO which will be converted into CO<sub>2</sub>. Response surface methodology as an experiment design method is considered to evaluate the effect of these two factors (independent variables) on the responses (dependent variables). An optimum combination of operating variables to attain responses with the desired quality is also anticipated by using the response surface optimizer tool in Minitab software.</p><p> </p><p><strong>Received: 02 August 2024 </strong></p><p><strong>Accepted: 02 October 2024 </strong></p><p><strong>Published: 14 October 2024</strong></p> |
|---|---|
| ISSN: | 2356-8518 2356-8569 |