A method to optimise compressed air supply pressure to hydropower mine refuge bays

Abstract

The cost of electricity is rapidly increasing in South Africa. This leads to high operational costs for deep-level mines, which furthermore reduces production. As companies mine deeper, temperatures generally increase partly due to the higher virgin rock temperature. The mine is responsible for making life sustainable underground and therefore services are provided underground. These services include compressed air, drinking water, ventilation, cooling, pumping, and hoisting. Compressed air consumes up to 20% of the mine's electrical energy. In the case of deep-level hydropower mines, high-pressure water is used to drill and extract ore from the gold reef. The primary, continuous compressed air users on the demand-side of deep-level hydropower mines are refuge bays. Refuge bays are a safe and secure go-to gathering area for mining personnel in case of an emergency. Refuge bays are prone to being oversupplied with compressed air due to inefficiencies such as leaks and misuses. Therefore, an opportunity exists to reduce the compressed air consumption in deep-level hydropower mines. Existing energy-saving methods include a combination of demand- or supply-side management techniques. On the demand-side, energy-saving strategies include leak auditing techniques or the identification of inefficiencies. Supply-side management focuses on the improvement of compressed air supply by using methods such as adjusting guide vane angles and pressure setpoint control. The objective of this study is to construct an analytical method based on the law of conservation of energy to determine the minimum gauge pressure that each refuge bay should receive, based on its size and occupancy, while still adhering to regulations. In the case study that was investigated, it was found that the refuge bay with the highest pressure requirement, according to the method developed, requires roughly 87 kPa supply pressure while currently receiving 238 kPa. Thereafter, a simulation model was constructed within the boundary of the case study. The simulation was verified, yielding an error of 5%. In addition, the simulation was validated by manual measurements, achieving an error of 3%. The simulation model was implemented by reducing the compressed air setpoint. It was found that the setpoint can be reduced by 35 kPa throughout a typical 24-hour period. This reduction in pressure setpoint resulted in an annual cost saving of over R 50 000.