Joint Optimal Power Flow Routing and Vehicle-to-Grid Scheduling: Theory and Algorithms

Abstract

In a smart grid integrated with vehicle-to-grid (V2G) technique, electric vehicles (EVs) fleets under effective coordination can be considered as a massive aggregated power storage to provide frequency regulation service. In this article, we propose a hierarchical system model to jointly optimize power flow routing and V2G scheduling for providing regulation service. First of all, by installing power flow routers (PFRs) inside the power grid, we formulate the problem of optimal power flow (OPF) routing at the grid level. Through the utilization of the semidefinite programming (SDP) relaxation, we can transform the original non-deterministic polynomial-time hard (NP-hard) problem into a convex problem. The tree decomposition method is then used to further reduce the complexity of the system network. After solving the grid-level OPF routing problem, a forecast-based scheduling problem is formulated at the EV level to coordinate EVs by providing the V2G regulation service. To cope with the forecast uncertainties, an online scheduling problem is in turn formulated. In order to solve these problems in a scalable manner, decentralized algorithms are then devised to control the EV schedules. The simulation results show that the devised online scheduling algorithm can outperform the existing algorithms, which is able to flatten the power fluctuations at the buses with EVs attached. Additionally, we show that grid stability issue can be alleviated through the proposed model. Finally, for different power systems, the uses of PFRs can reduce the system power loss in a great manner while providing voltage regulation.