A statistical approach in determining the electrical short term demand in a rapid railway system

South Africa has commissioned a new rapid railway system between the cities of Pretoria and Johannesburg. Commuter rail has proven to be more ideal, particular when considering the reduction of carbon emersions and the relief of congestion on city highways. This new railway system is being supplied by an electrical propulsion system which source is obtained from a local electrical supplier. Supply agreements for particularly high energy users and in this case essential services has meant carefully calculating the current and short term demand. This data is used to ensure that the energy supplier has reserved the appropriate capacity for this essential service. Short term forecast relate to the operational and maintenance function of commuter travel. Predicting a possible crisis can be met with a contingency plan. This paper evaluates the current energy trends of the commuter rail system and how from a statistical point of view, the data from energy loggers may be used to determine a short term load forecast and maximum demand. A statistical model has proven successful, especially because many forecasted data was derived from statistical data.