Smart plug-in electric vehicle charging to reduce electric load variation at a parking place

Electricity demand having less variation at different times in a day avoids any detrimental effect on power electronic equipments, reduces electricity cost, and simplifies the electric energy demand prediction from the smart grid. This paper delineates an intelligent aggregator architecture to automate Plug-in Electric Vehicle (PEV) charging in large parking places to reduce dynamic load variation. We present a set of novel rectangle placement based algorithms to schedule the PEV charging based on their arrival, departure time at parking place and their charging requirement. The proposed algorithms also determine the voltage level at which PEVs should be charged to improve demand side electric load profile. The presented algorithms meet the charging requirement of every PEV, reduce load variation, and increase load factor at the parking place. Simulation results interpret that the proposed method provides significant improvement regarding load variation and load factor. Notably, the methodology performs better than the traditional First come, First serve (FCFS) based PEV charging at a parking lot.