| Title |
Optimal Swapping and Power Operation Scheduling for Battery Charging Swapping Station Considering PV Uncertainty: A Distributionally Robust Optimization Approach |
| Authors |
박준희(Jun-Hui Park) ; 성가연(Ga-Yeon Seong) ; 이민규(Min-Gyu Lee) ; 이상윤(Sangyoon Lee) |
| DOI |
https://doi.org/10.5370/KIEE.2026.75.5.1086 |
| Keywords |
Battery charging swapping station; Photovoltaic system; Nodal carbon intensity; Distributionally robust optimization. |
| Abstract |
This study proposes an optimal power operation scheduling strategy for battery swapping charging station (BCSS) integrated with a photovoltaic (PV) system, explicitly considering nodal carbon intensity and the uncertainties of PV generation. The primary objective is to minimize the total operation cost, which comprises i) power purchasing cost for battery charging, ii) the revenue from power selling to the grid, and iii) the carbon cost associated with power injection, while satisfying electric vehicle battery swapping requirements. To address the stochastic uncertainty of PV generation, we formulate the scheduling problem using a Wasserstein metric-based distributionally robust optimization approach. Finally, simulation results demonstrate the comparative performance of the proposed method under varying cost coefficients and the distributional ambiguity parameters, such as the sample size and confidence level. |