Optimal sizing of Energy Storage Systems in railway transportation

This study introduces two different Linear Programming (LP) formulations and a Mixed Integer Linear Programming (MILP) formulation to optimize Energy Storage System (ESS) sizing in different scenarios, aiming to identify the solution that maximizes the return on investment associated with ESS installation. The proposed models are suitable for both railway substations supporting train operations with integrated photovoltaic (PV) energy and on-board ESS. The models consider operational variables, energy tariffs, load demands, and economic implications, proposing adaptable solutions across a variety of scenarios. Two real-world case studies are used to validate the models, and extensive numerical tests are performed to assess the effectiveness of the proposed models and study the impact of different parameters on the installation choices and the profitability of the investment. In the first case study, financial benefits have been analyzed by examining the impact of varying installed capacity of PV plants and cost-to-price ratios. Results demonstrate that, under current cost parameters, installing an ESS is economically advantageous. Moreover, limiting the State of Charge (SoC) to an interval between 20% and 100% doubles the profitability index (PI) of the investment, compared to scenarios with no SoC restrictions. In the second case study, concerning the deployment of an on-board ESS for hybrid trains in non-electrified track scenarios within the European context, results show that optimizing battery capacity and power line allocation enables partial electrification, significantly reducing infrastructure costs while ensuring operational requirements.