A Review of Research on Advanced Control Methods for Underground Coal Gasification Processes

Ján Kačur (), Marek Laciak, Milan Durdán, Patrik Flegner and Rebecca Frančáková
Additional contact information
Ján Kačur: Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, Němcovej 3, 042 00 Kosice, Slovakia
Marek Laciak: Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, Němcovej 3, 042 00 Kosice, Slovakia
Milan Durdán: Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, Němcovej 3, 042 00 Kosice, Slovakia
Patrik Flegner: Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, Němcovej 3, 042 00 Kosice, Slovakia
Rebecca Frančáková: Institute of Control and Informatization of Production Processes, Faculty BERG, Technical University of Košice, Němcovej 3, 042 00 Kosice, Slovakia

Energies, 2023, vol. 16, issue 8, 1-36

Abstract: Underground coal gasification (UCG) is a clean coal mining technology without significant environmental impacts. This technology can also be used in deep, hard-to-reach seams or deposits affected by tectonic disturbances, where conventional mining is impossible. Several techniques and methods have been investigated worldwide to support the process control of UCG. Global research focuses on the control of UCG operating parameters to stabilize or to optimize the performance of the underground reactor during energy conversion. This paper studies recent research in the field of UCG control and compares individual control techniques and possibilities for practical application. The paper focuses on advanced control methods that can be implemented in an in situ control system (e.g., adaptive control, extremum seeking control, and robust control). The study investigates control methods that ensure desired syngas calorific value or maximization. The review showed that robust control techniques such as sliding mode control and model predictive control have the most significant potential, and achieve the best results despite their complexity. In addition, some methods have been investigated through simulation or experimentally. The paper aims to give the reader an overview of the given issue and to alert the practice to recent research in the given area.

Keywords: UCG; modeling; advanced control; control algorithm; control methods; optimization; automation; review (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/16/8/3458/pdf (application/pdf)
https://www.mdpi.com/1996-1073/16/8/3458/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:16:y:2023:i:8:p:3458-:d:1123866

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().