@proceedingsBeh2019, Author = {Behzad Hashemi, Payam Teimourzadeh Baboli}, Title = {Technical Evaluation of Plug-in Electric Vehicles Charging Load on a Real Distribution Grid}, Year = {2019}, Publisher = {Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1004)}, Booktitle = {Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1004)}, Organization = {: Distributed Computing and Artificial Intelligence, 16th International Conference}, Doi = {10.1007/978-3-030-23946-6_18}, Url = {https://link.springer.com/chapter/10.1007/978-3-030-23946-6_18}, type = {proceedings}, Abstract = {The popularity of Plug-in Electric Vehicles (PEVs) in the last few years however is a turning point toward alleviating the global warming, but the inevitable effects of charging load of these vehicles on electric grids has become a concern for grid operators. While uncoordinated charging of a large number of PEVs may jeopardize the operation of the grids, intelligent methods can be used to coordinate the charging processes for the benefit of the grids. This paper presents a comprehensive model of future charging load of PEVs in a real distribution grid by considering PEVs’ characteristics and different driving patterns. Domestic and public charging are both considered. Moreover, an intelligent approach based on Non-dominated Sorting Genetic Algorithm (NSGA-II) will be introduced to coordinate PEVs’ charging with the aim of minimizing the power losses cost of the grid and maximizing the PEV owners’ satisfaction and considering technical constraints in our next work. This study is carried out on a real medium voltage distribution grid of Tehran Province Distribution Company in Lavasan city in Iran. The results show the detrimental effects of uncoordinated charging of PEVs on the operation of the grid which can be reduced by implementing the mentioned intelligent coordination approach.} @COMMENTBibtex file generated on