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The penetration level of Plug-in Electric Vehicles (PEVs) is projected to continue to rise in the future, which will lead to significant stress to the power grid due to frequent charging behaviors and their high power density requirements. While many studies have demonstrated the static pressure caused by PEVs for specific scenarios, there is no software platform available for the visualization of the PEVs' dynamic impacts at the distribution level of the power grid. This thesis presents a Distribution Grid RespOnse Monitor (DGROM) that fills this gap. DGROM allows for easy parameter definition, including driving habits, PEV types, and penetration levels. Its back end allows fast integration and data processing for scattered PEV charging over wide areas. DGROM also considers mitigation efforts by providing built-in algorithms for coordinated charging and location planning of charging stations. By coordinating PEV charging, we can flatten load spikes over time and space, and thus mitigate PEV's impact. This paper presents the optimization basis and algorithms for PEV coordination. In addition to reducing distribution grids' stress, these algorithms will allow the maximization of end-user benefits under varying retail electricity prices. DGROM is demonstrated on the IEEE 8500 node test case and power systems within Columbus, OH ranging from 81 to 1230 nodes. |
