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Due to the increasing concern for greenhouse gas emissions and fossil fuelsecurity, electric vehicles (EVs) have attracted much attention in recentyears. EVs can aggregate together constituting the vehicle-to-grid system.Coordination of EVs is beneficial to the power system in many ways. In thispaper, we formulate a novel large-scale EV charging problem with energy tradingin order to maximize the aggregator profit. This problem is non-convex and canbe solved with a centralized iterative approach. To overcome the computationcomplexity issue brought by the non-convexity, we develop a distributedoptimization-based heuristic. To evaluate our proposed approach, a modifiedIEEE 118 bus testing system is employed with 10 aggregators serving 30 000 EVs.The simulation results indicate that our proposed distributed heuristic withenergy trading can effectively increase the total profit of aggregators. Inaddition, the proposed distributed optimization-based heuristic strategy canachieve near-optimal performance.

Coordinated Electric Vehicle Charging Control with Aggregator Power Trading and Indirect Load Control