A Method for Energy Storage Capacity Configuration in the Power Grid Along Mountainous Railway Based on Chance-Constrained Optimization

Fang Liu, Jian Zeng, Jiawei Liu, Zhenzu Liu (), Qiao Zhang, Yanming Lu and Zhigang Liu
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Fang Liu: State Grid Sichuan Electric Power Company, Chendu 610041, China
Jian Zeng: State Grid Sichuan Electric Power Company, Chendu 610041, China
Jiawei Liu: State Grid Sichuan Electric Power Company, Chendu 610041, China
Zhenzu Liu: School of Electrical Engineering, Southwest Jiaotong University, Chendu 610032, China
Qiao Zhang: School of Electrical Engineering, Southwest Jiaotong University, Chendu 610032, China
Yanming Lu: School of Electrical Engineering, Southwest Jiaotong University, Chendu 610032, China
Zhigang Liu: School of Electrical Engineering, Southwest Jiaotong University, Chendu 610032, China

Energies, 2025, vol. 18, issue 19, 1-16

Abstract: To address the challenges of weak power-grid infrastructure, insufficient power supply capacity along mountainous railways, and severe three-phase imbalance caused by imbalanced traction loads at the point of common coupling (PCC), this paper proposes an energy storage configuration method for mountainous railway power grids considering renewable energy integration. First, a distributionally robust chance-constrained energy storage system configuration model is established, with the capacity and rated power of the energy storage system as decision variables, and the investment costs, operational costs, and grid operation costs as the objective function. Subsequently, by linearizing the three-phase AC power flow equations and transforming the model into a directly solvable linear form using conditional value-at-risk (CVaR) theory, the original configuration problem is converted into a mixed-integer linear programming (MILP) formulation. Finally, simulations based on an actual high-altitude mountainous railway power grid validate the economic efficiency and effectiveness of the proposed model. Results demonstrate that energy storage deployment reduces overall system voltage deviation by 40.7% and improves three-phase voltage magnitude imbalance by 16%.

Keywords: imbalanced traction loads; energy storage configuration; renewable energy integration; distributionally robust; chance constrained (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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