Optimal V2G and Route Scheduling of Mobile Energy Storage Devices Using a Linear Transit Model to Reduce Electricity and Transportation Energy Losses

TL;DR

This paper introduces a co-optimization strategy for mobile energy storage devices that minimizes energy losses in power and transportation networks by jointly scheduling their routes and power outputs using a linear transit model.

Contribution

It presents a novel linear transit model integrated with linearized constraints for optimal MESD operation, enabling global optimization with a mixed-integer linear programming approach.

Findings

Significant reduction in total energy losses compared to stationary batteries.

Effective coordination of MESD routes and power outputs under various network conditions.

Validation through simulation case studies demonstrating improved efficiency.

Abstract

Mobile energy storage devices (MESDs) operate as medium- or large-sized batteries that can be loaded onto electric trucks and connected to charging stations to provide various ancillary services for distribution grids. This paper proposes a new strategy for MESD operation, in which their power outputs and paths are co-optimally scheduled to minimize the total energy loss in both power and transportation networks. The distances moved by MESDs and time at different locations are modeled using a set of linear equations, considering the time-varying traffic flow. The linear transit model is integrated with linearized constraints to support the reliable operation of the distribution grid. In particular, an optimal scheduling problem is formulated considering the maximum limits on incremental variations in bus voltages and line power flows for active and reactive power outputs of MESDs. A mixed-integer linear programming solver can be readily applied to the optimization problem, ensuring the global optimality of the solution. Simulation case studies are carried out under various power and transportation network conditions. The results of these case studies confirm that the proposed strategy using MESDs is effective in reducing total energy losses, compared to conventional methods using stationary batteries and plug-in electric vehicles.