Enhancing Energy Efficiency in DC Railways Using Optimized Fractional-Order Proportional-Integral Controller for Energy Storage System

The increasing energy demand and environmental impact of transportation systems have intensified the need for more efficient railway energy management strategies. Although electric railway systems provide a sustainable alternative, the dynamic nature of traction power systems and the inadequate use of regenerative braking energy still result in significant energy losses. In order to improve energy efficiency and state-of-charge (SOC) stability, this study proposes an optimized fractional-order proportional-integral (FOPI) controller for the control of a wayside energy storage system (ESS) in a DC railway network. The parameters of the FOPI controller are tuned via recent metaheuristic tool of barrel theory-based optimizer (BTO) such that the error between the desired and actual charging/discharging voltages of the ESS is minimized under nonlinear and time-varying operating conditions. The BTO is characterized by strong exploration/exploitation balance that prevents the approach from falling in local optima. Also, the approach has low sensitivity to user-defined parameters. The proposed approach was evaluated using a MATLAB/Simulink (version 2021b) model of a double-track DC railway system incorporating realistic train operations and three distinct traffic scenarios including ideal, perturbed, and stochastic conditions. The BTO was compared to other approaches of particle swarm optimization (PSO) and gray wolf optimizer (GWO). Also, statistical tests using the Friedman, Kruskal–Wallis, ANOVA, and Wilcoxon rank tests were conducted to assess the suggested approach. The obtained results confirm the robustness and competence of the proposed controller compared to either the conventional static control approach or optimized controller via the comparable approaches. As a result, the suggested controller achieved higher total energy savings, improved utilization of regenerative braking energy, and enhanced power demand distribution across substations. While minor increases in SOC deviation were observed in certain scenarios, the overall system performance showed improved robustness and adaptability. These findings highlight the effectiveness of integrating fractional-order PI control designed via the suggested BTO for advanced energy management in railway applications.