Decentralized Smart Charging of Electric Vehicles in Residential Settings: Algorithms and Predicted Grid Impact

Unrestricted charging of electric vehicles (EVs) can result in violations of the grid’s operating limits, and/or equipment damage or failure. To address this, the researchers propose a two-stage smart charging (SC) algorithm for EVs in single-family residences. In the first stage, the researchers pose an SC optimization problem considering only the EV owner’s interests. In the second stage, they leverage the existence of multiple optimal (or near-optimal) solutions to this optimization problem to reduce the grid impact of EV charging at no (or negligible) cost to the EV owner. The researchers then assess the grid impact of our SC strategy in a residential area, where all EVs are controlled in a decentralized manner (i.e., independently of one another). For comparison, the researchers also assess the grid impact of rapid charging and other known SC strategies. The researchers' assessment utilizes Monte-Carlo simulation techniques and a physics-based distribution feeder model. Focusing only on the price-minimization SC problem, the researchers show that (i) if existing SC strategies are employed, then SC can have the same undesirable effects as unrestricted, rapid charging, and (ii) if our proposed SC strategies are employed, then SC can significantly lower the grid impact of EV adoption at no additional cost to the EV owner.

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