Multi-objective Optimization Approach for the Allocation of Fast Charging Stations and Distributed Energy Resources

The increasing inclusion of Electric Vehicles (EVs) in distribution systems is a global trend due to their several advantages, such as increased autonomy and reduced price. However, the high amount EVs requires installation sufficient EV Charging Stations (EVCSs) recharge them. If there no adequate planning for EVCSs allocation, it can result reduction power quality indices losses system voltage variation outside limits established IEEE Std 1547-2018. Therefore, this paper aims define best locations system, addition performing optimal allocation sizing Distributed Energy Resources (DERs) order mitigate problem related levels. Moreover, Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used with purpose minimizing investment operation costs deviation system. validation methodology performed using 13 34 node test feeders, possible compare optimized solutions based on Pareto curve both systems, which made minimize objective functions.