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Optimization of mine ventilation fan speeds according to ventilation on demand and time of use tariff

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  • Chatterjee, Arnab
  • Zhang, Lijun
  • Xia, Xiaohua

Abstract

In the current situation of the energy crisis, the mining industry has been identified as a promising area for application of demand side management (DSM) techniques. This paper investigates the potential for energy-cost savings and actual energy savings, by implementation of variable speed drives to ventilation fans in underground mines. In particular, ventilation on demand is considered in the study, i.e., air volume is adjusted according to the demand at varying times. Two DSM strategies, energy efficiency (EE) and load management (LM), are formulated and analysed. By modelling the network with the aid of Kirchhoff’s laws and Tellegen’s theorem, a nonlinear constrained minimization model is developed, with the objective of achieving EE. The model is also made to adhere to the fan laws, such that the fan power at its operating points is found to achieve realistic results. LM is achieved by finding the optimal starting time of the mining schedule, according to the time of use (TOU) tariff. A case study is shown to demonstrate the effects of the optimization model. The study suggests that by combining load shifting and energy efficiency techniques, an annual energy saving of 2540035kWh is possible, leading to an annual cost saving of USD 277035.

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  • Chatterjee, Arnab & Zhang, Lijun & Xia, Xiaohua, 2015. "Optimization of mine ventilation fan speeds according to ventilation on demand and time of use tariff," Applied Energy, Elsevier, vol. 146(C), pages 65-73.
    • Handle: RePEc:eee:appene:v:146:y:2015:i:c:p:65-73
    DOI: 10.1016/j.apenergy.2015.01.134
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    References listed on IDEAS

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    5. Jie Hou & Gang Nie & Guoqing Li & Wei Zhao & Baoli Sheng, 2023. "Optimization of Branch Airflow Volume for Mine Ventilation Network Based on Sensitivity Matrix," Sustainability, MDPI, vol. 15(16), pages 1-14, August.
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    7. Yonggang Gou & Xiuzhi Shi & Jian Zhou & Xianyang Qiu & Xin Chen, 2017. "Characterization and Effects of the Shock Losses in a Parallel Fan Station in the Underground Mine," Energies, MDPI, vol. 10(6), pages 1-20, June.
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    11. Nikodem Szlązak & Marek Korzec, 2022. "The Solution of the Main Fan Station for Underground Mines Being Decommissioned in Terms of Reducing Energy Consumption by Ventilation," Energies, MDPI, vol. 15(13), pages 1-13, June.
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    13. Kalantari, Hosein & Ali Ghoreishi-Madiseh, Seyed, 2023. "Study of mine exhaust heat recovery with fully-coupled direct capture and indirect delivery systems," Applied Energy, Elsevier, vol. 334(C).
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    15. Junqiao Li & Yucheng Li & Wei Zhang & Jinyang Dong & Yunan Cui, 2022. "Multi-Objective Intelligent Decision and Linkage Control Algorithm for Mine Ventilation," Energies, MDPI, vol. 15(21), pages 1-17, October.
    16. Prince, & Hati, Ananda Shankar, 2021. "A comprehensive review of energy-efficiency of ventilation system using Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    17. Ghoreishi-Madiseh, Seyed Ali & Sasmito, Agus P. & Hassani, Ferri P. & Amiri, Leyla, 2017. "Performance evaluation of large scale rock-pit seasonal thermal energy storage for application in underground mine ventilation," Applied Energy, Elsevier, vol. 185(P2), pages 1940-1947.
    18. Zijun Li & Huasen Liu & Yu Xu & Rongrong Li & Mintao Jia & Mengsheng Zhang, 2021. "Numerical Analysis on the Thermal Performance in an Excavating Roadway with Auxiliary Ventilation System," IJERPH, MDPI, vol. 18(3), pages 1-17, January.

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