The growing adoption of electric vehicles (EVs) has introduced substantial challenges to the grid. Uncontrolled EV charging may lead to grid overloading, voltage instability, increased power losses, accelerated aging of distribution transformers, and risk of outages. Therefore, a strategic approach is required to tackle the adverse impacts of uncontrolled EV charging to the grid. A promising approach is using EV batteries collectively as a flexible load. Residential areas have the most pronounced EV flexibility potential due to the significant length of uninterrupted parking. In this paper, models of EV charging in residential areas are formulated, followed by Monte Carlo simulations. Three charging models are developed: uncontrolled charging, controlled charging without considering grid limitation and controlled charging considering grid limitation. An optimization problem based on quadratic programming is used in the controlled charging. A residential area based on the IEEE European LV test feeder adopting the deregulated Swedish electricity market is taken as a case study for the simulation. The case study findings indicate that incorporating grid limitation into controlled charging strategies can prevent grid overload and significantly reduce charging and battery degradation costs. In this case study, controlled charging can reduce the charging costs to approximately 42% compared to uncontrolled charging. Considering the battery degradation costs, controlled charging costs are 24% lower than uncontrolled charging. It is possible to postpone the costly grid reinforcement by applying strategic EV charging scheduling. The methods and outcomes pave the way for developing, testing, and implementing business models to manage the grid impacts of growing EV charging.