Abstract
We study the system-level effects of the introduction of large populations of Electric Vehicles (EVs) on the power and transportation networks. We assume that each EV owner solves a decision problemto 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 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 optimumoperating pointwhile 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.
Original language | English (US) |
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Article number | 2590259 |
Pages (from-to) | 863-875 |
Number of pages | 13 |
Journal | IEEE Transactions on Control of Network Systems |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - Dec 2017 |
Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Signal Processing
- Computer Networks and Communications
- Control and Optimization
Keywords
- Coupled infrastructure systems
- Electric vehicles
- Equilibrium
- Mobility
- Networked control systems