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Advances in Optimization and Modelling of Coal Mining

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "H: Geo-Energy".

Deadline for manuscript submissions: closed (5 May 2025) | Viewed by 2916

Special Issue Editors


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Guest Editor
Department of Mining, Faculty of GeoEngineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15 St., 50-421 Wrocław, Poland
Interests: computational methods of spatial modelling of ore deposits and mine planning; modelling and calculation of mining transport systems
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E-Mail Website
Guest Editor
Department of Mining, Faculty of GeoEngineering, Mining and Geology, Wroclaw University of Science and Technology, Na Grobli 15 St., 50-421 Wrocław, Poland
Interests: applications of mathematics and computer methods in mining engineering; computer systems for maintenance management and inventory control; reliability of transport systems and their components (esp. belt conveying systems); economic analysis of their operation; NDT methods of conveyor belts condition; stochastic methods in mining and simulation models; quality assurance and quality control; investment decision making and economic evaluation; risk analysis; optimization in mine designs and production scheduling; modelling of mines and power plants cooperation in liberalized energy markets; energy risk modelling; ETS market analyzing and modelling

Special Issue Information

Dear Colleagues,

Global coal production amounted to approximately 175 exajoules (1018 J) in 2022, which represents a 75% increase since the beginning of the 21st century, while global electric energy production has doubled since then. The most populous countries like China and India continue to develop fossil-fuelled power generation projects that, in contrast, are being abandoned in the EU due to rigorous climate protection policies. Looking globally, the rising scale of coal mining—one of the most energy-exhausting and environmentally aggressive branches of the economy—introduces challenges for researchers. Optimisation efforts of coal mining operations should be targeted to both improving the overall efficiency and mitigating their environmental impact. One methods for decreasing carbon emissions from fossil-fuelled power plants is the co-firing of coal and biomass; however, this creates a set of hazard and handling problems to be solved. The rapidly increasing share of unstable RESs has created the need to address the temporal and random surpluses and shortages of RESs by providing effective methods of balancing them. The coal-fuelled power generation complex contains various and not yet utilised possibilities of energy supply (not only directly from burning the coal) or storage with the use of intensive energy-consuming operations that can be controlled considering the interim needs of balancing the electric energy in the grid.

These problems encourage researchers to begin investigations with novel modelling and calculating methods applying online data acquisition, cloud computing, and artificial intelligence algorithms to build effective digital twins of coal-fuelled power complexes that can help to achieve a higher level of sustainable electric energy generation comprising renewable and fossil-fuelled sources.

The proposed topics of this Special Issue of Energies are:

  1. Energy policy;
  2. Coal assets policy;
  3. Energy security;
  4. Coal-bed methane;
  5. Energy audit of coal handling mine and power plant;
  6. Coal energy sources for present and future;
  7. Coal-fired energy dilemma;
  8. Coal combustion efficiency;
  9. Clean coal technology;
  10. Energy climate nexus;
  11. Geoeconomics of coal;
  12. Coal and biomass handling and cofiring.

Dr. Witold Kawalec
Dr. Leszek Jurdziak
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • coal mining
  • energy production
  • process modelling
  • coal deposit modelling
  • digital twin
  • coal quality tracking
  • coal processing
  • fossil fuels
  • green power
  • carbon emissions
  • dynamic control of energy
  • surplus of RES
  • black and green power management
  • overburden removal control
  • energy conversion and storage

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Published Papers (1 paper)

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Research

30 pages, 3939 KiB  
Article
Predictive Modeling of Conveyor Belt Deterioration in Coal Mines Using AI Techniques
by Parthkumar Parmar, Leszek Jurdziak, Aleksandra Rzeszowska and Anna Burduk
Energies 2024, 17(14), 3497; https://doi.org/10.3390/en17143497 - 16 Jul 2024
Cited by 2 | Viewed by 2024
Abstract
Conveyor belts are vital for material transportation in coal mines due to their cost-effectiveness and versatility. These belts endure significant wear from harsh operating conditions, risking substantial financial losses if they fail. This study develops five artificial neural network (ANN) models to predict [...] Read more.
Conveyor belts are vital for material transportation in coal mines due to their cost-effectiveness and versatility. These belts endure significant wear from harsh operating conditions, risking substantial financial losses if they fail. This study develops five artificial neural network (ANN) models to predict conveyor belt damage using 11 parameters from the Belchatow brown coal mine in Poland. The models target five outputs: number of repairs and cable cuts, cumulative number of repairs and cable cuts, and their ages. Various optimizers (Adam, Nadam, RMSprop, Adamax, and stochastic gradient descent or SGD) and activation functions (ReLU, Swish, sigmoid, tanh, Leaky ReLU, and softmax) were tested to find the optimal configurations. The predictive performance was evaluated using three error indicators against actual mine data. Superior models can forecast belt behavior under specific conditions, aiding proactive maintenance. The study also advocates for the Diagbelt+ system over human inspections for failure detection. This modeling approach enhances proactive maintenance, preventing total system breakdowns due to belt wear. Full article
(This article belongs to the Special Issue Advances in Optimization and Modelling of Coal Mining)
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