Optimal Charging Strategies for Unidirectional Vehicle-to-Grid

TLDR

Vehicle‑to‑grid (V2G) can boost electric‑vehicle adoption, and unidirectional V2G is especially attractive because it requires only communication with an aggregator, which aggregates many EVs to bid into energy markets. The study develops an algorithm for unidirectional regulation to be used by an aggregator. The algorithm employs smart charging schemes that adjust the charge‑rate pivot point during regulation and a profit‑maximization routine that incorporates optional system‑load and price constraints. Simulations with 10,000 commuter EVs in the Pacific Northwest show that the optimal algorithms raise aggregator profits and lower both system‑load impacts and customer costs.

Abstract

Vehicle-to-grid (V2G) has been proposed as a way to increase the adoption rate of electric vehicles (EVs). Unidirectional V2G is especially attractive because it requires little if any additional infrastructure other than communication between the EV and an aggregator. The aggregator in turn combines the capacity of many EVs to bid into energy markets. In this work an algorithm for unidirectional regulation is developed for use by an aggregator. Several smart charging algorithms are used to set the point about which the rate of charge varies while performing regulation. An aggregator profit maximization algorithm is formulated with optional system load and price constraints analogous to the smart charging algorithms. Simulations on a hypothetical group of 10 000 commuter EVs in the Pacific Northwest verify that the optimal algorithms increase aggregator profits while reducing system load impacts and customer costs.