  Electricity demand of electric railways is a relatively unexplored source of
flexibility in demand response applications in power systems. In this paper, we
propose a transactive control based optimization framework for coordinating the
power grid network and the train network. This is accomplished by coordinating
dispatchable distributed energy resources and demand profiles of trains using a
two-step optimization. A railway based dynamic market mechanism (rDMM) is
proposed for the dispatch of distributed energy resources (DER) in the power
network along the electric railway using an iterative negotiation process, and
generates profiles of electricity prices, and constitutes the first step. The
train dispatch attempts minimize the operational costs of trains that ply along
the railway, while subject to constraints on their acceleration profiles, route
schedules, and the train dynamics, and generates demand profiles of trains and
constitutes the second step. The rDMM seeks to optimize the operational costs
of the underlying DERs while ensuring power balance. Together, they form an
overall framework that yields the desired transactions between the railway and
power grid infrastructures. This overall optimization approach is validated
using simulation studies of the Southbound Amtrak service along the Northeast
Corridor (NEC) in the United States, which shows a 25% reduction in energy
costs when compared to standard trip optimization based on minimum work, and a
75% reduction in energy costs when compared to the train cost calculated using
a field dataset.
