Aggregation Model-Based Optimization for Electric Vehicle Charging Strategy

Optimal Charging Scheduling of Electric Vehicles in Smart Grids by Heuristic Algorithms

“…In a dynamic analysis, such as EV control, dynamic models of the EV batteries must be considered [16] where EV batteries can be approximated by a voltage source V OC in series with an equivalent constant resistance of the battery cell R i in which the active power characteristic of the EV battery represents the charging process. However, for planning and scheduling purposes, we consider that the EV aggregator manages the EVs' distributed storage batteries to provide DSO the required flexibility of services.…”

“…It is considered that the V2G exchange is possible only when EVs are plugged-in at home; therefore, two timeframes are considered: daylight (7:00-18:59), when 10% of the V2G stored energy can be injected into the network, and during the night, when 90% of the EVs are plugged-in at home and are capable of delivering part of their stored energy to the grid. According to the 2020 forecast of EV penetration levels [16], a smart G2V + V2G analysis has been developed for a medium penetration level of EVs in the network. As shown in Figure 22, the smart G2V + V2G load management technique (green columns) improves the post-operation load profile of the smart G2V main transformer.…”

“…The flexibility of the EV demand will improve the operation of power systems in terms of flattening the load curve on main substation transformers, providing, in addition, peak shaving services, reduced power system losses, reduced aging of transformers and lines, and increased renewable energy penetration [11] as well as providing financial support [9][10][11][12][13][14][15][16][17][18]. In an uncontrolled, or "dumb", scenario, EVs should be charged when the owner arrives at his home [16,19]; however, potential problems such as sudden peak demand or sudden overloading could be shaped or flattened by using a smart charging schedule for the EV's batteries [20]. Moreover, the optimal scheduling of EV battery charging could allow high EV penetration without requiring any upgrades to the existing electricity infrastructure [21] (cables and transformers), thereby reducing investment expenses.…”

“…In [16], a GA drives the charging process to minimise the impact on peak load avoidance, parking availability and the charging control. Shaaban and Saadany [30] implemented the optimal charging of EVs using GAs and incorporated only light-duty fleet users' behaviours without considering peak load shaving in their formulation.…”

Optimal Planning of Charging for Plug-In Electric Vehicles Focusing on Users’ Benefits

“…Numerous studies have been performed toward controlling EVs' charging behaviors in various ways to mitigate the negative impacts on the power grid [6,7]. A centralized charging strategy with an aggregated EV charging model was developed to flatten the daily load curve in [8,9], developing an energy management system to perform peak-load shifting by utilizing EVs, used EV batteries, and photovoltaicpanels. A new coil design set with a special arrangement which is effective for dynamic charging of EVs has been proposed to maintain a nearly uniform coupling factor and negligible power transfer fluctuation in [10].…”