Optimal Integration of Rooftop PV and Wind Powers for Cost-Efficient and Low-Carbon Operation of Sustainable Railway Systems

This paper focuses on the environmental and economic impact of electric railway systems (ERS) and introduces Railway Energy Management Systems (REMS) as a green solution to reduce greenhouse gas (GHG) emissions and CO2 pollution and reducing the operational cost of the station while allowing surplus electricity sales to the grid market. The research utilizes Mixed Integer Linear Programming (MILP) to optimize the operation cost and GHG reduction of railway station electrical systems in Milan, Italy. The study considers Renewable Energy Resources (RERs), Energy Storage Systems (ESSs), Regenerative Braking Energy (RBE), and the electrical grid. It also incorporates real-time data to account for the probabilistic and stochastic behaviors of these elements, leading to a significant cost reduction of 56.09% in smart railway station operations. MATLAB is employed to solve the model effectively, demonstrating the suitability and effectiveness of the proposed approach with compelling evidence of operational cost and GHG reductions in various scenarios, achieving a reduction of 3458.26 kg/day in the best scenario.