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    Using simulation to prioritise implementation of platinum mine compressed air efficiency solutions

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    De Jager_MM.pdf (4.016Mb)
    Date
    2021
    Author
    De Jager, M.M.
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    Abstract
    Platinum mines are facing several challenges and a higher-than-inflation increase in electricity costs is amongst the most significant. Compressed air accounts for up to 38% of a platinum mine’s energy consumption. To improve the efficiency of compressed air systems, several energy efficiency solutions have been developed and proven to be successful. Unfortunately, mines do not have clarity regarding the most beneficial order for implementing energy efficiency solutions. This is further worsened by the capital expenditure required to implement these energy efficiency solutions, whilst uncertainty remains how feasible they may be. This motivates the need for this study, namely developing a methodology that prioritises the implementation order of mine compressed air efficiency solutions. Recent software advances have made it possible to use simulations to investigate the feasibility of energy efficiency solutions. A new methodology was created that uses simulation models to evaluate and prioritise the implementation order of energy efficiency solutions on deep-level platinum mines according to annual savings, payback periods, level of automation and implementation time. The methodology entailed analysing the system, creating simulation models, verifying simulation models and, finally, determining the implementation priority of the energy efficiency solutions. This methodology was applied to two case studies to determine the implementation priority of the energy efficiency solutions. The best projects were implemented first and unfeasible projects were avoided, which led to significant savings of R35.1 million per annum. Moreover, the methodology enabled the savings to be obtained in the shortest possible time with the smallest payback period. When the savings were extrapolated to the South African platinum mining industry, potential annual savings of R342 million were predicted. This implementation methodology contributes by ensuring that future energy efficiency projects are prioritised and implemented correctly to ensure that maximum savings are achieved at the lowest cost and in the shortest possible time. Furthermore, labour and investigations required for unfeasible energy efficiency solutions will be avoided.
    URI
    https://orcid.org/0000-0001-8935-6879
    http://hdl.handle.net/10394/37657
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    • Engineering [1424]

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