Fair and Privacy-Aware EV Discharging Strategy Using Decentralized Whale Optimization Algorithm for Minimizing Cost of EVs and the EV Aggregator

A key motivation to fasten roll-out of electric vehicles (EVs) the market is implement Vehicle-to-Grid (V2G) functionalities. With V2G in place, EV owners can have extra freedom interact their battery energy with power grids, namely by selling grid when EVs are not use. On other hand, aggregators and utility companies leverage flexibility collected various ancillary services which may significantly reduce costs of, for instance, running spinning reserve traditional plants on side. However, this also poses practical challenges terms how devise a discharging strategy group that fair some sense optimal. In paper, we present new design typical trading framework whilst leveraging whale optimization algorithm decentralized manner, metaheuristic has been shown effective solving large-scale centralized problems. We demonstrate using simple ideas data shuffling aggregation, one an fair, optimal privacy-aware where privacy refers fact no critical information should be exchanged aggregator, vice versa. The fairness implies common discharge rate needs sought all so gets better benefits than others same programme. Simulation results presented illustrate efficacy our proposed system.