Browsing by Author "Lategan, Luca"
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- ItemSystem analysis for improved energy recovery on Prasa’s electrical traction network(Stellenbosch : Stellenbosch University, 2017-03) Lategan, Luca; Vermeulen, H. J.; Stellenbosch University. Faculty of Engineering. Dept. of Electrical and Electronic Engineering.ENGLISH ABSTRACT: In the very competitive transport market, operators are constantly looking for ways to drive down operational expenses and act on social sentiment to promote their service. Energy recovery through regenerative braking provides an answer to both these issues by reducing energy expenditure and acting on the call for “greenness” by reducing the carbon-footprint of the operation. This thesis investigates the possible energy savings that can be realised through harnessing the regenerative braking capabilities of new Alstom train sets ordered by the Passenger Rail Agency of South Africa (Prasa). A dynamic load-flow analysis of the 3 kV DC and 33 kV AC electrical network of Metrorail Western Cape will be done to analyse the current capacity of, and future demand on the electrical network. The feasibility of introducing, as well as the ideal placement of, energy recovery equipment will be investigated. This will be done to maximise the potential energy savings and return on investment that can be realised through the regenerative braking capabilities of the new train sets. DIgSILENT PowerFactory, was chosen as simulation package to build a virtual model of the electrical traction network and conduct dynamic simulations. In order to validate the accuracy of the predicated future network state, with the future rolling stock, the simulation results of the existing rolling stock and electrical network were benchmarked against real measured data. Due to the good correlation between the simulation results and the measured data, the simulation results of the network with other rolling stock models should also prove to be equally accurate. The simulation model was adapted with the dynamic load model of the future train sets to simulate the projected future state of the electrical traction network. This offered insight into the predicted supply versus demand, over and under voltages as well as the effect of regenerative braking on the power flow. More ideal feeding and sectioning philosophies were also investigated. The new rolling stock’s installed power of 11;2MW is significantly higher than the 3;52MW of the current rolling stock. The simulation results of the future network state indicate that the new trains will not be able to operate at their intended performance levels. The proposed feeding and sectioning alterations will increase efficiency, but the installed capacity will have to be increased and a number of substations have been identified in this regard. To better utilise the new rolling stock’s regenerative capabilities, various options was investigated and the ideal location for the installation of energy recovery equipment was identified.