A Cost-Efficient Energy Management System for Battery Swapping Station

Extensive penetration of electrified transportation (xEVs) would require a framework pertaining to smart grid applications for optimizing the grid-to-vehicle (G2V) and vehicle-to-grid (V2G) management. Under this framework, an xEV aggregator would be an intermediary between an independent system operator and individual xEVs, which would offer flexibilities for operating electricity markets. In this paper, we propose a mix integer linear programming based optimal energy management system for battery swapping station (BSS) by participating in the day ahead, real-time and ancillary services. To incorporate the dynamicity of energy price and xEVs load in the optimization model, a suitable forecasting method is selected and suitability of the selected model has been discussed. Furthermore, we propose an incentive-based vehicle-to-vehicle game theoretic approach to assess the expected profit of the BSS aggregator. Later, the validation of the proposed framework is discussed through a case study considering a fleet of 100 xEVs. To incorporate real-time scenario, multitype electric vehicles (EVs) are considered.