An Optimal Operation Model and Ordered Charging/Discharging Strategy for Battery Swapping Stations

Abstract

Abstract:The economic operation of battery swapping stations (BSSs) is significant for the promotion of large-scale electric vehicles. This paper develops a linear programming model to maximize the daily operation profits of a BSS by considering constraints of the battery swapping demand of users and the charging/discharging balance of batteries in the BSS. Based on the BSS configuration and data from electric taxis in Beijing, we simulate the operation situation and charging/discharging load of the BSS in nine scenarios with two ordered charging and discharging strategies. The simulation results demonstrate that the model can achieve the maximum daily profits of the BSS. According to the sensitivity analysis, the battery swapping price for batteries is the most sensitive, followed by the number of batteries in the BSS, while the operation-maintenance costs and battery depreciation costs are least sensitive. In addition, the charging and discharging of batteries in the BSS can be coordinated by increasing the battery quantity of the BSS and formulating the ladder-type battery swapping price.

Electric Vehicles for Public Transportation in Power Systems: A Review of Methodologies

“…Focusing on BSSs, it is crucial to develop methodologies to maximize the daily operation profits. Thus, the authors of [73] proposed a linear programming model by considering constraints on the battery swapping demand of users and charging state of batteries. A real case study from the ETs in Beijing was used to prove the effectiveness of the methodology.…”

Optimal Dispatching Strategy for Shared Battery Station of Electric Vehicle by Divisional Battery Control

“…It is assumed that the real battery demand b re fluctuate frequently around the predicted battery demand b pr . The simulation of the process can be expressed in (26)- (28). It is proved that the SOC and S bb of the batteries which customers swap in the 24 time slots follows Gaussian distribution approximately [42], [43].…”

“…Recently, an increasing number of researchers and power engineers have started to investigate the model and schedule of BSS and BCS from different perspectives. For example, in [28], from the perspective of swapping price, an optimization model to maximize the daily revenue considering the battery swapping income, depreciation cost and operation and maintenance cost was proposed. As pointed out by [29], it's especially important to meet the growing demand for chargeswap service.…”

“…In [36], a generic nonparametric method was introduced to the prediction of customers' battery demand, according to typical BSS, the authors have proven that the proposed methods can predict the customers' battery demand, and the probabilistic interval is suitable for predicting the horizon 24h ahead. Most of previous papers focused on changing the charging rates to manage the SOCs of batteries and control the total load power [28], [37], [38]. The first way is to provide several fixed charging rates [39], which is hard to realize smooth power regulation and control the SOC of each battery flexibly.…”

“…Moreover, the transportation system and manpower not only cause extra cost, but increase additional time. As for charge-swap station, Liang et al [28], Sarker et al [32], and Li et al [40] proposed some conceptual frameworks, but little actual business model was put forward. In this paper, a shared battery station (SBS) system and its business model are proposed in detail.…”