With the growing concerns about energy shortage and demand supply imbalance, demand side management (DSM) activities has found its way into the mining industry. This study analyzes the potential to save energy and energy-costs in underground mine ventilation networks, by application of DSM techniques. Energy saving is achieved by optimally adjusting the speed of the main fan to match the time-varying flow demand in the network, which is known as ventilation on demand (VOD). Further cost saving is achieved by shifting load to off-peak or standard times according to a time of use (TOU) tariff, i.e. finding the optimal mining schedule. The network is modelled using graph theory and Kirchhoff’s laws; which is used to form a non-linear, constrained, optimization problem. The objective of this problem is formulated to minimize the energy cost; and hence it is directly given as a function of the fan speed, which is the control variable. As such, the operating point is found for every change in the fan speed, by incorporating the fan laws and the system curve. The problem is solved using the fmincon solver in Matlab’s optimization toolbox. The model is analyzed for different scenarios, including varying the flow rate requirements and tariff structure. Although the results are preliminary and very case specific, the study suggests that significant energy and energy-cost saving can be achieved in a financially viable manner. / Dissertation (MEng)--University of Pretoria, 2014. / tm2015 / Electrical, Electronic and Computer Engineering / MEng / Unrestricted