Abstract
This study aimed to find innovative ways to reduce the financial burden caused by the massive traction bill following the multi-billion-rand investment in the procurement of state-of-the-art passenger trains. A pioneering integrated approach to optimising energy and power management in a 3kV DC Railway System using hybridised decision-making methods in the context of energy savings through regenerative energy systems is presented. Hence this study conceptualised and developed integrated decision-making approaches and parameter ranking methods to improve regenerative energy recovery in the energy-intensive industry like the railway. Sensitivity analysis and ranking methods, energy savings techniques, strategies, and operational methods used within the urban railway system were conducted to enrich multicriteria decision methods. In line with the intended integrated approach to develop decision-making strategies, the interpretive structural modelling approach (ISM) method was identified as complementary to the analytic hierarchical process (AHP) as an integrated decision-making methodology for selecting energy savings methods. A ranking process to find out which of the numerous parameters are the most significant with regards to impact on the amount of regenerated energy that is potentially available to be recovered and stored for later use was conducted. Therefore, the uncertainty quantification techniques and validation using different sensitivity analysis methods, followed by the quantification of regenerative energy through mathematical approaches was undertaken. Furthermore, the conceptualised integrated decision framework and prioritisation method was developed and applied to rank energy savings solutions in 3kV DC railway systems and subjected to sensitivity analysis to test the stability of the model. The Morris sensitivity analysis (SA) method was used to rank the regeneration energy parameters. The SA and Cotter methods confirmed that the final ranking of the solutions and ranking of the parameters are consistent and reliable, respectively. In addition, optimisation techniques were applied to determine the best location and size of a proposed hybrid energy storage device (HESS) based on the quantification exercise conducted using mathematical models developed for the case study section of the railway line. This study developed methods to identify the most suitable techniques for maximising regenerative energy within the 3kV DC urban rail systems. The ranking of energy solutions parameters will help railway operators focus on optimizing the most critical parameters of the chosen solutions for recuperating regenerative energy in traction systems. An integrated framework will assist in ranking and selecting the most appropriate solutions amongst several alternatives and assist in decision-making by introducing an interpretive structural modelling approach. Finally, the four decision making methods applied in an integrated manner is effectively the first attempt in enhancing the understanding of interpretive structural modelling in the context of the multicriteria decision making methods in 3kV DC railways. The methods proposed in this research will be useful in a variety of organisational contexts where multi factor decisions, relationships and interactions are being considered at different levels.