With increasing penetrations of renewable distributed generations (DGs) and electrified vehicles (EVs), the volatility of the renewable sources and the huge load of the EVs induce tremendous challenges for the power grid. The two technologies also have considerable synergetic potential to alleviate these challenges if they are intelligently coordinated. The aim of this paper is to investigate how the (dis)charging of EVs could be intelligently coordinated with the production of the local DGs to reduce the peak load on the power grid. We consider a neighborhood energy community that is composed of prosumer households. Three EV (dis)charging scenarios are compared: the dumb strategy where all EVs are charged for the next commute as soon as they return from the previous commute, the centralized (dis)charging strategy where the EVs are managed by a centralized scheduling unit, and the distributed (dis)charging strategy where the households autonomously schedule their EVs while coordination is achieved through providing dynamic pricing based incentives. Our simulation results show that the distributed and centralized charging strategies can reduce the peak load up to 44.9% and 75.1%, respectively, compared to the dumb charging strategy. Moreover, the relative performance of the algorithms with respect to environmental values.