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Energy efficiency assessment of electric shovel operating in opencast mine

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  • Topno, Seema Ashishan
  • Sahoo, Lalit Kumar
  • Umre, B.S.

Abstract

Electric shovels are used for loading in opencast mines. Energy efficiency assessment of electric shovel is important to minimise its electrical energy usage. Specific power consumption (SPC) has been used as performance indicator to assess energy efficiency of shovel. A modelling framework is developed for estimating SPC of electric shovel from operating time and power measured for each process. The model is illustrated with a case study of 42 cu. m. P & H shovel operating in a large opencast mine of India. The SPC of shovel is optimized for actual operating cycle time components (idle time and digging time). Results of field measurements show that digging operation consumes maximum power in comparison to other operations of electric shovel in a cycle. The model has been used to assess the energy saving potential of electric shovel by using the real time operational data. The minimum SPC of electric shovel is 0.12 kWh/cum for zero idle time and the energy saving potential is 13.45%. The optimization of SPC has also been done for different digging conditions. The model developed can help to set a target for energy consumption of electric shovel operating in a mine.

Suggested Citation

  • Topno, Seema Ashishan & Sahoo, Lalit Kumar & Umre, B.S., 2021. "Energy efficiency assessment of electric shovel operating in opencast mine," Energy, Elsevier, vol. 230(C).
    • Handle: RePEc:eee:energy:v:230:y:2021:i:c:s0360544221009518
    DOI: 10.1016/j.energy.2021.120703
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    References listed on IDEAS

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    1. Sahoo, Lalit Kumar & Bandyopadhyay, Santanu & Banerjee, Rangan, 2014. "Benchmarking energy consumption for dump trucks in mines," Applied Energy, Elsevier, vol. 113(C), pages 1382-1396.
    2. Qiushi Bi & Guoqiang Wang & Yongpeng Wang & Zongwei Yao & Robert Hall, 2020. "Digging Trajectory Optimization for Cable Shovel Robotic Excavation Based on a Multi-Objective Genetic Algorithm," Energies, MDPI, vol. 13(12), pages 1-20, June.
    3. Wang, Ning & Wen, Zongguo & Liu, Mingqi & Guo, Jie, 2016. "Constructing an energy efficiency benchmarking system for coal production," Applied Energy, Elsevier, vol. 169(C), pages 301-308.
    4. Monica Carvalho & Dean L. Millar, 2012. "Concept Development of Optimal Mine Site Energy Supply," Energies, MDPI, vol. 5(11), pages 1-20, November.
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    Cited by:

    1. Nie, Wen & Jiang, Chenwang & Liu, Qiang & Guo, Lidian & Hua, Yun & Zhang, Haonan & Jiang, Bingyou & Zhu, Zilian, 2024. "Study of highly efficient control and dust removal system for double-tunnel boring processes in coal mines," Energy, Elsevier, vol. 289(C).
    2. Nie, Wen & Jiang, Chenwang & Sun, Ning & Guo, Lidian & Xue, Qianqian & Liu, Qiang & Liu, Chengyi & Cha, Xingpeng & Yi, Shixing, 2023. "Analysis of multi-factor ventilation parameters for reducing energy air pollution in coal mines," Energy, Elsevier, vol. 278(PA).

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