Keywords: rail transit, sustainable operation, energy optimization, regenerative braking, simulation, genetic algorithm, speed profile.

Facing unprecedented increases in operational expenses, rail operators are seeking new methods to reduce costs. Traction is their largest expense and despite their low energy intensities, the scale of operations causes large overall energy consumptions. This, coupled with the environmental impact of fossil fuel consumption is cause for concern. Modern railcars are equipped with the regenerative braking feature allowing them to generate electrical energy on braking. The energy can be stored for later use or transmitted directly to an accelerating train to reduce the energy used for acceleration. This study presents an intelligent method for harvesting the kinetic energy of an electric train through coasting and regenerative braking, and optimal positioning of the wayside energy storage system (WESS) units on a multi-segment rail line. Coasting saves energy by maintaining motion with propulsion disabled, and regenerative braking converts the kinetic energy of the train into electrical energy for the powering of subsequent acceleration cycles. The study entails the design of a model that simulates the movement of the train over an existing alignment section while considering alignment topography, speed limits, and train schedule. The main contribution of this research is the optimization of the number and locations of the WESS units using optimized speed profiles to maximize the net present value (NPV) of the energy recovery project. In this study, the optimized speed profiles are obtained with and without WESS installation and used as inputs to a linear programming (LP) simulation model. Hence, the model begins with inputs that are already optimized, ensuring a greater degree of processing speed and accuracy. The decision variables are the number and locations of the WESS units, and the output of the simulator is the optimized NPV. The results can be used for the planning of smart infrastructural Facing unprecedented increases in operational expenses, rail operators are seeking new methods to reduce costs. Traction is their largest expense and despite their low energy intensities, the scale of operations causes large overall energy consumptions. This, coupled with the environmental impact of fossil fuel consumption is cause for concern. Modern railcars are equipped with the regenerative braking feature allowing them to generate electrical energy on braking. The energy can be stored for later use or transmitted directly to an accelerating train to reduce the energy used for acceleration. This study presents an intelligent method for harvesting the kinetic energy of an electric train through coasting and regenerative braking, and optimal positioning of the wayside energy storage system (WESS) units on a multi-segment rail line. Coasting saves energy by maintaining motion with propulsion disabled, and regenerative braking converts the kinetic energy of the train into electrical energy for the powering of subsequent acceleration cycles. The study entails the design of a model that simulates the movement of the train over an existing alignment section while considering alignment topography, speed limits, and train schedule. The main contribution of this research is the optimization of the number and locations of the WESS units using optimized speed profiles to maximize the net present value (NPV) of the energy recovery project. In this study, the optimized speed profiles are obtained with and without WESS installation and used as inputs to a linear programming (LP) simulation model. Hence, the model begins with inputs that are already optimized, ensuring a greater degree of processing speed and accuracy. The decision variables are the number and locations of the WESS units, and the output of the simulator is the optimized NPV. The results can be used for the planning of smart infrastructural upgrades, the reduction of energy consumption or the mitigation of environmental pollution.

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