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    The Application of a MIP Model to Select the Optimum Auxiliary Fan and Operational Settings for Multiple Period Duties

    Access Status
    Fulltext not available
    Authors
    Acunna, E.
    Hall, Stephen
    Hardcastle, S.
    Fava, L.
    Date
    2010
    Type
    Journal Article
    
    Metadata
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    Citation
    Acunna, Enrique and Hall, Stephen and Hardcastle, Stephen and Fava, Lorrie. 2010. The Application of a MIP Model to Select the Optimum Auxiliary Fan and Operational Settings for Multiple Period Duties. INFOR: Information Systems and Operational Research. 48 (2): pp. 95-102.
    Source Title
    INFOR: Information Systems and Operational Research
    ISSN
    0315-5986
    School
    WASM - Western Australian School of Mines
    URI
    http://hdl.handle.net/20.500.11937/32988
    Collection
    • Curtin Research Publications
    Abstract

    Ventilation systems can be the primary consumers of energy in underground mining operations. Systematically reducing ventilation costs without impinging on production will significantly improve the profitability of an operation. This paper presents an application of a mixed integer programming model (MIP) to assist in the selection of the optimum auxiliary fan to supply the required pressure and airflow to an underground mining activity across multiple time periods. The MIP model considers the pressures and airflows required to be delivered by the fan for each time period, along with the associated capital and operational expenditure in selecting the optimum fan, based on cost, across all the operating conditions. In the presented approach, the nonlinear performance characteristic curves of the fans are discretized to permit the implementation of linear techniques in the selection of the fan operational points for every period. A case study is presented to test the proposed MIP model and its applicability, plus show the potential savings that can be generated even over short time periods. The solution obtained is optimal in the discretized solution space, but in the ‘real life’ solution space, the fan selection is feasible and near optimal, outperforming the current practices.

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