Plug-in electric vehicles (PEVs) and wind distributed generations (WDGs) will represent key technologies in the future smart grid configurations. PEV charging at high penetration levels requires substantial grid energy that can be partially supplied by WDGs. This paper examines the impacts of WDGs on performance of recently implemented online maximum sensitivities selection based coordination algorithm (OL-MSSCA) for PEV charging. The algorithm considers random arrivals of vehicles and time-varying market energy price to reduce the total cost of energy generation for PEV charging and the associated grid losses while providing consumer priorities based on defined charging time zones. OL-MSSCA will be improved to also consider DGs while maintaining network operation criteria such as maximum generation limits and voltage profiles within their permissible limits. Detailed simulation is performed on the modified IEEE 23kV distribution system with three WDGs and 22 low voltage residential networks populated with PEVs. The main contributions of this paper are inclusion of WDGs in OL-MSSCA, as well as detailed investigations on the impacts of their peak generation times, penetrations and locations on the performance of smart grid populated with PEVs.