Typical mine cooling system layout and components

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Background information

With the ever-increasing need and escalating cost of electrical energy, the necessity for energy- efficiency initiatives on the demand side rises, especially when there are restrictions on the supply side. The mining sector in South Africa accounted for 14.3% of all electrical energy supplied by Eskom (South Africa’s electrical energy utility) in 2016, of which up to 25% is used by mine cooling systems [1, 2]. It is evident from the utility’s electricity distribution results summary in Table 1 that the mining sector, with more than 1 000 customers, is among the largest consumers based on the percentage per customer scale [2]. The mining industry is faced with a number of challenges. For instance, the energy required to extract a unit of gold from the earth increased by a factor of four from 1970 to 2001. This results from mines becoming deeper and more energy being required to process the higher weight of ore for each ton of gold mined due to, among other things, higher hoisting, milling and cooling energy consumptions [3, 4]. Many energy-saving initiatives have been studied. Some of these initiatives were successfully implemented in the mining industry and primarily comprised load-shifting and energy- efficiency strategies implemented on large energy-consuming equipment typically found on mines, including compressed air, dewatering and cooling systems [5-20]. Energy recovery has also been implemented in the form of turbine systems, which became popular during the 1970s [21]. With the continued and growing strain on the energy utility and the high energy-consuming nature of the mining industry, every effort to realise additional energy savings in any of the previously implemented strategies or the suggestion of new strategies would be of valuable support to the sustainability of electricity in South Africa and elsewhere in the world. Energy savings achieved by controlling auxiliary equipment in mine cooling systems have been investigated [18, 19].
These cooling systems consist of surface refrigeration plants, which include pre-cooling towers, chillers, condenser cooling towers, bulk air coolers and all the associated pumps and fans. Although some statements of optimisation were made, it appears that these statements merely suggest manual trial-and-error optimisation in which the system’s operational parameters were varied to obtain a more energy-efficient operation of the cooling system. This was done as a manual iterative process for several iterations until acceptable energy-saving results were obtained. Du Plessis, Liebenberg and Mathews [18] and Bornman [19] suggest that the savings achieved by the mine’s cooling systems were significant, although one cannot claim that the integrated optimal operation had been achieved with energy consumption minimised as the objective function. It is important to consider the integrated cooling system by means of a simulation model. This allows one to observe the effect of energy consumption on the overall integrated cooling system when applying one strategy to a part of the system.
It is therefore important to consider the complete, integrated cooling system when applying the optimisation in order for the global optimum set of parameters to be determined for each set of boundary conditions, instead of optimising each component of the system in isolation without interpreting its effect on the overall cooling system. It has been suggested that a slight increase in one component’s energy consumption could realise a more significant energy reduction elsewhere in the system in some cases [22]. It is clear from these concluding remarks that there is an opportunity to investigate the possibility of determining the optimum energy-minimised operational parameters for the integrated cooling system. Although many models and energy improvements have been considered and implemented before, none were found where the integrated mine cooling system’s energy consumption was minimised. If this minimisation is successfully achieved, these optimal parameters can be used to operate the mine’s cooling system at its minimum energy consumption in real time, as the demand and other boundary conditions change dynamically, based on mining requirements and ambient climate conditions.

Problem statement

Many mine cooling system energy models have been considered in the past, but none of them simulated and quantified the complete integrated system on a component level. Therefore, it is necessary to construct a suitable integrated mine cooling system model that will simulate the cooling system on an integrated component basis to allow a holistic view of the system’s behaviour and energy consumption to variations in the system’s operational parameters. Although several mine cooling system energy-saving initiatives were previously investigated and some implemented, they did not include the mathematical optimisation of an integrated cooling system to operate at its energy minimum for all permutations of demand and ambient conditions. It is therefore necessary to couple a suitable simulation model to an optimisation platform to minimise the total energy consumption of the system.

Methodology

Following from the problem statement and research objectives, in order to determine the possibility of arriving at a matrix of energy-minimised system operational parameters, the cooling system considered as a case study will be simulated by the various modelling methods and strategies available and presented in the literature. This simulation model will be compared to the measured data that was obtained from the mine to determine the model’s accuracy and acceptability. The optimisation-friendly simulation model will be coupled with a commercially available optimisation platform, which will optimise the boundary control variables of the cooling system in an integrated fashion in order to arrive at the energy-minimised matrix of operational parameters for an entire year if feasible. These parameters along with the simulation model by which they are optimised, will be used to determine the system output at the energy-minimised operation, while ensuring that the demand requirements are still met and that the optimisation yields acceptable output results. Finally, the optimised energy consumption of the system will be compared to the system’s measured performance at current operating conditions to determine the energy savings that can be achieved by implementing the optimisation to the system.

Table of contents :

• Publications resulting from this investigation:
• Abstract
• Acknowledgements
• Table of contents
• Nomenclature
• Greek letters
• Subscripts and super-scripts
• Abbreviations
• List of tables
• List of figures
• 1 Introduction
  • 1.1 Background information
  • 1.2 Problem statement
  • 1.3 Research objectives
  • 1.4 Methodology
  • 1.5 Delineation and limitations
  • 1.6 Overview of the thesis
• 2 Literature review
  • 2.1 Preamble
  • 2.2 Typical mine cooling system layout and components
  • 2.3 Existing energy-saving initiatives
  • 2.4 Cooling system modelling
  • 2.5 Variable-flow energy-saving potential of a mine cooling system
  • 2.6 Optimisation overview
  • 2.7 Mine cooling system and simulation
  • 2.8 Conclusion
• 3 Case study – mine cooling system and simulation
  • 3.1 Preamble
  • 3.2 Cooling system overview
  • 3.3 Modelling approaches
  • 3.4 Cooling towers as direct contact heat exchangers
  • 3.5 Water-cooled chillers
  • 3.6 Pumps and fans
  • 3.7 Simulation model parameter determination and verification
  • 3.8 Conclusion
• 4 Case study – baseline simulation
  • 4.1 Preamble
  • 4.2 Baseline simulation and validation
  • 4.3 Optimisation
  • 4.4 Conclusion
• 5 Case study – optimisation
  • 5.1 Preamble
  • 5.2 Optimisation platform
  • 5.3 Optimisation application and results
  • 5.4 Conclusion
• 6 Conclusion
  • 6.1 Introduction and literature
  • 6.2 Mine cooling system and simulation
  • 6.3 Optimisation and results
  • 6.4 Recommendations
• 7 References
  • Appendix A
  • Appendix B
  • Appendix C

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