Trade-off between simulation accuracy and complexity for mine compressed air systems

Abstract

In South Africa, the industrial sector is responsible for a large portion of the country's total annual electricity consumption. The mining sector alone contributes approximately 15%, which makes it one of the largest electricity consumers in the country. A significant electricity consumer on a mine is compressed air. Compressed air generation is a process with various challenges that can contribute to unnecessary operational expenses. Examples of these challenges are leakages and the continuous operation of compressors when compressed air is not required. Numerous other factors also contribute to compressed air generation being an expensive as well as a wasteful process. Simulation software has the potential to identify problem areas within a compressed air network. Limited data availability on mines, however, often restricts the capability of simulation software. Simulation accuracy depends on the amount of available data to ensure accurate comparisons between actual system events and characteristics, as well as simulated predictions. The need arose to determine the acceptability of simulation accuracy based on the availability of data on any mine. A method was developed to test simulation accuracies based on data availability. Three simulations, namely, a detailed, standard and simplified model were devised. The simulation models were created using actual data from Mine-A, which has been equipped to record a full variety of operational data. The recorded data was used to simulate the compressed air network of Mine-A accurately. The three simulation models were each a simplified version of the previous one. Simplification entails reducing the number of simulation components. By reducing the number of components, the time and financial impact related to creating simulations can be reduced. The study investigated the impact that a reduction in simulation complexity has on simulation accuracy. It was discovered that a simplified compressed air simulation model is able to achieve a simulation error of only 4.87%. Finally, from the results gathered from this study, it can be concluded that simplifying compressed air simulations has little effect on simulation accuracy. Simplified compressed air simulations are therefore recommended because of the significant decrease in development time without compromising simulation accuracy.