5,814 research outputs found
Electrical Vehicles in the Smart Grid: A Mean Field Game Analysis
In this article, we investigate the competitive interaction between
electrical vehicles or hybrid oil-electricity vehicles in a Cournot market
consisting of electricity transactions to or from an underlying electricity
distribution network. We provide a mean field game formulation for this
competition, and introduce the set of fundamental differential equations ruling
the behavior of the vehicles at the feedback Nash equilibrium, referred here to
as the mean field equilibrium. This framework allows for a consistent analysis
of the evolution of the price of electricity as well as of the instantaneous
electricity demand in the power grid. Simulations precisely quantify those
parameters and suggest that significant reduction of the daily electricity peak
demand can be achieved by appropriate electricity pricing.Comment: submitted to IEEE Journal on Selected Areas in Communications: Smart
Grid Communications Serie
The BARISTA: A model for bid arrivals in online auctions
The arrival process of bidders and bids in online auctions is important for
studying and modeling supply and demand in the online marketplace. A popular
assumption in the online auction literature is that a Poisson bidder arrival
process is a reasonable approximation. This approximation underlies theoretical
derivations, statistical models and simulations used in field studies. However,
when it comes to the bid arrivals, empirical research has shown that the
process is far from Poisson, with early bidding and last-moment bids taking
place. An additional feature that has been reported by various authors is an
apparent self-similarity in the bid arrival process. Despite the wide evidence
for the changing bidding intensities and the self-similarity, there has been no
rigorous attempt at developing a model that adequately approximates bid
arrivals and accounts for these features. The goal of this paper is to
introduce a family of distributions that well-approximate the bid time
distribution in hard-close auctions. We call this the BARISTA process (Bid
ARrivals In STAges) because of its ability to generate different intensities at
different stages. We describe the properties of this model, show how to
simulate bid arrivals from it, and how to use it for estimation and inference.
We illustrate its power and usefulness by fitting simulated and real data from
eBay.com. Finally, we show how a Poisson bidder arrival process relates to a
BARISTA bid arrival process.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS117 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
- …