Electric vehicles (EVs) tend to increase peak power for residences in the evening when house owners return home and begin charging. The aggregated EV charging demand can cause a sudden rise in the peak power at the distribution system level, resulting in a “dragon curve” Such phenomenon, combined with the “duck curve” that is caused by high photovoltaic (PV) penetration in residential communities, requires fast ramping rates and expanded capabilities for local distribution transformers and main feeder cables provided by the utility. As a solution, a residential energy storage system (RESS) can store surplus PV generation during midday and use the stored energy to support the peak power demand in the evening. House owners benefit from this strategy by avoiding electricity sales to the grid at low rates and by reducing energy usage during high Time-of-Use (ToU) periods. In this paper, a community with smart homes that include PV systems, RESSs and EVs was modeled. The EV models were developed based on data from the National Travel Household Survey (NHTS). The EV charging and RESS operation were scheduled to reduce the daily utility charge. The entire power system worked as virtual power plant as it kept the aggregated power constant for a long period of time.

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Conference Proceeding

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Notes/Citation Information

Published in 2020 IEEE Transportation Electrification Conference & Expo (ITEC).

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The document available for download is the authors’ manuscript version accepted for publication. The final published version is copyrighted by IEEE and is available as: Gong, H., and Ionel, D. M., “Optimization of Aggregated EV Power in Residential Communities with Smart Homes”, 2020 IEEE Transportation Electrification Conference & Expo (ITEC), Chicago, IL, USA, 2020, pp. 779-782, doi: 10.1109/ITEC48692.2020.9161532

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Funding Information

This research was supported in part by the DE-EE0008352 project “Solar Power Electronics Modular Integrated Node Platform” led by FlexPower, Inc. and sponsored by the Department of Energy. The support of the University of Kentucky, the L. Stanley Pigman endowment, and of the SPARK program is also gratefully acknowledged.