  Shared electric vehicles (SEVs) have emerged as a promising solution to
contribute to sustainable urban mobility. However, ensuring the efficient
operation and effective battery management of SEV systems remains a complex
challenge. This challenge stems from factors such as slow plug-in charging, the
potential role of SEVs in balancing grid load pressure, and the optimization of
SEV operations to ensure their economic viability. To tackle these challenges,
this paper introduces an integrated strategy for optimizing various aspects of
SEV systems, encompassing strategies like Vehicle-to-Grid (V2G),
Battery-to-Grid (B2G), and battery swapping. This approach is built on a
space-time-energy network model that facilitates the optimization of battery
charging and discharging scheduling, SEV operations like relocations and
battery swapping, battery swapping station selection and the number of
batteries. The objective of this approach is to maximize profits while
addressing operational constraints and the complexities of energy management
within SEV systems. Given the substantial complexity that arises with
large-problem scales, the paper introduces a column generation-based heuristic
algorithm. Extensive experimental validation is conducted, including
sensitivity analysis on different charging speeds and fleet sizes. The results
illuminate the impact of varying charging rates and fleet sizes on performance
indicators. Notably, it is observed that battery swapping is particularly
effective as an auxiliary charging method when the number of vehicles is
limited. Conversely, in scenarios with a large fleet, the necessity for battery
swapping diminishes. Moreover, results show the effectiveness of V2G and B2G
technologies in grid load balancing.
