4.6 Article Proceedings Paper

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

Journal

IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
Volume 56, Issue 1, Pages 34-47

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TIA.2019.2954072

Keywords

Energy loss; linear transit model; mixed-integer linear programming (MILP); mobile energy storage device (MESD); power and transportation networks; stationary batteries; traffic flows

Funding

  1. Energy Cloud R&D Program through the National Research Foundation of Korea - Ministry of Science, ICT [NRF-2019M3F2A1073402]
  2. National Research Foundation of Korea [2019M3F2A1073402] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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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 article 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.

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