  The adoption of electric vehicles (EVs), including electric taxis and buses,
as a mode of transportation, is rapidly increasing in cities. In addition to
providing economic and environmental benefits, these fleets can potentially
participate in the energy arbitrage market by leveraging their mobile energy
storage capabilities. This presents an opportunity for EV owners to contribute
to a more sustainable and efficient energy system while also reducing their
operational costs. The present study introduces deterministic and single-stage
stochastic optimization frameworks that aim to maximize revenue by optimizing
the charging, discharging, and travel of a fleet of electric vehicles in the
context of uncertainty surrounding both spatial and temporal energy prices. The
simulations are performed on a fleet of electric delivery trucks, which have to
make deliveries to certain locations on specific dates.
  The findings indicate the promising potential of bidirectional electric
vehicle charging as a mobile grid asset. However, it is important to note that
significant revenue is only realized in scenarios where there is substantial
variation in prices between different areas, and when these price variations
can be accurately forecasted with a high level of confidence.
