Identifying and improving inefficient deep-level mine compressed air distribution networks

Abstract

The cost of electricity in South Africa is regularly increasing, and the energy availability factor (EAF) is worsened by poorly maintained plants, generation failures, sabotage, and coal and cable theft. This directly impacts the industrial mining sector, not only by reducing profit margins but also through load curtailment, where mining operations are running 20% to 30% below capacity due to electrical constraints. Platinum-group metals (PGMs) are the leading commodity by sales, with the largest ore deposit in South Africa. Due to the recent decline in basket prices, approximately 25% of the production of primary PGMs is now unprofitable when considering the current spot prices. The long-term sustainability of this sector is greatly at risk, as cost-focused restructuring led to job cuts and postponed investments. With electricity accounting for 90% of total utility costs, compressed air is the highest electrical consumer next to mining processes. Compressed air is also the key energy source used for pneumatic equipment in conventional mining. Insufficient pressure delivery to consumers may hinder operational performance and subsequently production rates. Shaft personnel often increase compressor supply pressures to accommodate low-delivery pressures and related complaints, increasing operational costs and lowering profitability. An extensive literature review focused on addressing the issue of low compressed air delivery pressures due to system inefficiencies. This review highlighted the need for a safer and simpler method to address the issue. The proposed solution involved examining the haulage distribution network as a potential option for improving delivery pressures. To achieve this, mathematical relationships between variables that describe pressure were analysed from first principles to gain a clear understanding of compressed air distribution in distant underground networks. A methodology was developed to model the compressed air supply at known consumer demands. When applying the developed methodology to a case study mine, a verified baseline model was developed, with each level's pressure profile calibrated to an average mean average percentage error (MAPE) of 4.56%. A weighted MAPE (WMAPE) was introduced to account for high average percentage error (APE) during the blasting shift periods, skewing the MAPE of each level due to low-pressure values. With the weights based on the significance of pressure, a WMAPE of 2.99% for all levels on average was observed. Furthering the developed method's steps, subsequent strategies were applied to effectively prioritise inefficient levels and identify infrastructural inefficiencies within the haulage distribution network using the developed baseline model. Limitations to identified localised inefficiencies can be addressed using the wastage-depressurisation method, developed to approximate the wastage on the respective level. The case study mine's compressed air infrastructure does not correctly conform to the dimensional requirements specified in the mine's compressed air engineering standards. The infrastructural requirements are also insufficiently specified, contradictive, and outdated. These standards are, therefore, considered inadequate based on the mine's extensively developed compressed air network at current flow demands. Solutions to improve inefficiencies were considered and simulated to provide predictive measures of the impact of implementation and the feasibility of implementation to the case study levels. The implementation of Scenario 2 to Case Study A achieved an average pressure improvement of 47.1 kPa (+9.5%), which is strongly correlated with the predicted improvement of 51.6 kPa (+10.4%). A large crosscut wastage was found in Case Study B.