Global concern about the energy crisis and its environmental impact has focused on sustainable alternatives. 1e electric railway system (ERS) is a major electrical energy consumer, contributing to greenhouse gas (GHG) emissions and CO2 pollution. 1is study introduces railway energy management systems (REMSs) as a green solution to address these challenges. REMS not only mitigates environmental risks but also enables surplus electricity sales to the grid market. 1is research formulates an AC optimal power 9ow (AC-OPF) problem by the utilization of mixed integer linear programming (MILP) for optimization of the railway station electrical system operation cost. In this paper, renewable energy resources (RERs), energy storage systems (ESSs), and regenerative braking energy (RBE) are taken into account, as well as the electrical grid. Additionally, by considering the probabilistic and stochastic behaviors of RERs, ESSs, and RBE, using real-time data, signi@cant cost reductions in the daily operations of smart railway stations are achieved. With the aid of MATLAB, the model is eAectively solved, and the results provide compelling evidence of the suitability and remarkable eAectiveness of the proposed model.

Sustainable Electric Railway System Integrated With Distributed Energy Resources: Optimal Operation and Smart Energy Management System

Mohsen Davoodi;Hamed Jafari Kaleybar;Morris Brenna;Dario Zaninelli
2025-01-01

Abstract

Global concern about the energy crisis and its environmental impact has focused on sustainable alternatives. 1e electric railway system (ERS) is a major electrical energy consumer, contributing to greenhouse gas (GHG) emissions and CO2 pollution. 1is study introduces railway energy management systems (REMSs) as a green solution to address these challenges. REMS not only mitigates environmental risks but also enables surplus electricity sales to the grid market. 1is research formulates an AC optimal power 9ow (AC-OPF) problem by the utilization of mixed integer linear programming (MILP) for optimization of the railway station electrical system operation cost. In this paper, renewable energy resources (RERs), energy storage systems (ESSs), and regenerative braking energy (RBE) are taken into account, as well as the electrical grid. Additionally, by considering the probabilistic and stochastic behaviors of RERs, ESSs, and RBE, using real-time data, signi@cant cost reductions in the daily operations of smart railway stations are achieved. With the aid of MATLAB, the model is eAectively solved, and the results provide compelling evidence of the suitability and remarkable eAectiveness of the proposed model.
2025
Electric railway, Energy Management System, renewable energy sources, MILP
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1283727
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