A Hierarchical Charging Control of Plug-in Electric Vehicles with Simple Flexibility Model

Journal Article · Fri Nov 01 00:00:00 EDT 2019 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2019.113490· OSTI ID:1547373

Wu, Di  ^[1]; Radhakrishnan, Nikitha  ^[1]; Huang, Sen ^[1]

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1. BATTELLE (PACIFIC NW LAB)

The demand for plug-in electric vehicles (PEVs) is increasing exponentially, which could have significant effects on the power grid, because charging one PEV is nearly equivalent to adding three houses to the power system. Even though PEVs increase demand on the electric grid, their capability to actively interact with the grid presents excellent opportunities for load management, demand response, and various other grid services. This paper proposes an innovative scheduling and control framework to enable smart PEV charging for grid services while meeting PEV owners’ travel needs. In the proposed framework, each set of electric vehicle supply equipment (EVSE) is equipped with a controller that estimates charging power and energy flexibility based on vehicle characteristics, EVSE power rating, battery energy state, and upcoming trip information. With the charging flexibility model received from each EVSE controller, the central coordinator determines the optimal power allocation for a look-ahead time window for the given grid services. The proposed charging coordination strategy can help reduce the computational complexity and communication requirement compared with existing methods. It is also scalable to the expanding PEV fleet and robust to uncertainties in upcoming vehicle trips and future system condition. The proposed method is studied using a prototypical feeder developed at Pacific Northwest National Laboratory and detailed trip information extracted from the National Household Travel Survey.

• Research Organization: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-76RL01830
• OSTI ID: 1547373
• Report Number(s): PNNL-SA-136731
• Journal Information: Applied Energy, Vol. 253
• Country of Publication: United States
• Language: English