  The rapid progression of sophisticated advance metering infrastructure (AMI),
allows us to have a better understanding and data from demand-response (DR)
solutions. There are vast amounts of research on the internet of things and its
application on the smart grids has been examined to find the most optimized
bill for the user; however, we propose a novel approach of house loads,
combined with owning a battery electric vehicle (BEV) equipped with the BEV
communication controllers and vehicle-to-grid (V2G) technology. In this paper
we use the Stackelberg game approach to achieve an efficient and effective
optimized algorithm for the users (followers) based on time dependent pricing.
We also assumed an electricity retailer company (leader) and a two-way
bilateral communication procedure. The usage-based side of the game has been
studied together with demand side management (DSM). Real-time pricing (RTP)
from time-of-use (TOU) companies has been used for better results, and Monte
Carlo simulation (MCS) handles the uncertain behavior of BEV drivers. Numerical
results compared to those from the simulation show that with this method we can
reshape the customer's demand for the best efficiency.
