20 research outputs found
Optimal Pricing to Manage Electric Vehicles in Coupled Power and Transportation Networks
We study the system-level effects of the introduction of large populations of
Electric Vehicles on the power and transportation networks. We assume that each
EV owner solves a decision problem to pick a cost-minimizing charge and travel
plan. This individual decision takes into account traffic congestion in the
transportation network, affecting travel times, as well as as congestion in the
power grid, resulting in spatial variations in electricity prices for battery
charging. We show that this decision problem is equivalent to finding the
shortest path on an "extended" transportation graph, with virtual arcs that
represent charging options. Using this extended graph, we study the collective
effects of a large number of EV owners individually solving this path planning
problem. We propose a scheme in which independent power and transportation
system operators can collaborate to manage each network towards a socially
optimum operating point while keeping the operational data of each system
private. We further study the optimal reserve capacity requirements for pricing
in the absence of such collaboration. We showcase numerically that a lack of
attention to interdependencies between the two infrastructures can have adverse
operational effects.Comment: Submitted to IEEE Transactions on Control of Network Systems on June
1st 201
Spatiotemporal Arbitrage of Large-Scale Portable Energy Storage for Grid Congestion Relief
Energy storage has great potential in grid congestion relief. By making
large-scale energy storage portable through trucking, its capability to address
grid congestion can be greatly enhanced. This paper explores a business model
of large-scale portable energy storage for spatiotemporal arbitrage over nodes
with congestion. We propose a spatiotemporal arbitrage model to determine the
optimal operation and transportation schedules of portable storage. To validate
the business model, we simulate the schedules of a Tesla Semi full of Tesla
Powerpack doing arbitrage over two nodes in California with local transmission
congestion. The results indicate that the contributions of portable storage to
congestion relief are much greater than that of stationary storage, and that
trucking storage can bring net profit in energy arbitrage applications.Comment: Submitted to IEEE PES GM 2019; 5 pages,4 figure
Stochastic Optimization of Coupled Power Distribution-Urban Transportation Network Operations with Autonomous Mobility on Demand Systems
Autonomous mobility on demand systems (AMoDS) will significantly affect the
operation of coupled power distribution-urban transportation networks (PTNs) by
the optimal dispatch of electric vehicles (EVs). This paper proposes an
uncertainty method to analyze the operational states of PTNs with AMoDS. First,
a PTN operation framework is designed considering the controllable EVs
dispatched by AMoDS as well as the uncontrollable driving behaviors of other
vehicle users. Then, a bi-level power-traffic flow (PTF) model is proposed to
characterize the interaction of power distribution networks (PDNs) and urban
transportation networks (UTNs). In the upper level, a social optimum model is
established to minimize the operating cost of PDNs and UTNs embedded with
controllable EVs. In the lower level, a stochastic user equilibrium (SUE) model
is established to minimize the operating cost of uncontrollable EVs and
gasoline vehicles (GVs) in UTNs. Finally, a probabilistic PTF analysis method
is developed to evaluate PTN operations under environmental and human
uncertainties. A regional sensitivity analysis method is proposed to identify
the critical uncertainties and quantify the impacts of their distribution
ranges on PTN operations. The effectiveness of the proposed method is verified
by the PTN consisting of a 21-bus PDN and a 20-node UTN.Comment: 10 pages, 13 figure