Optimal Train Operation for Minimum Energy Consumption Considering Track Alignment, Speed Limit, and Schedule Adherence

Abstract

Developing an optimal train speed profile for energy-efficient train operation is significant in both theory and applications but very difficult and complex to achieve. An optimization method that minimizes energy consumption by considering track alignment, speed limit, and schedule adherence is proposed. The objective function is total energy consumption, and the decision variables include the timing of train motion regimes. A simulated annealing algorithm (SA) is developed to search for the optimal train operation or “golden run.” The developed model is applied to a segment of the New Haven line of the Metro-North Commuter Railroad, which runs between Woodlawn, New York, and New Haven, Connecticut. A sensitivity analysis is conducted, and the relationship between model parameters and decision variables are explored.