Computation of electrical vehicle charging station (evcs) with coordinate computation based on meta-heuristics optimization model with effective management strategy for optimal charging and energy saving

The wide deployment of grid-connected environments leads to the growth of electric vehicles (EV). On other hand, it put forth the development of EV stations and reduced energy as well as arbitrage. The users concentrated on the charging point of the Electrical Vehicle Charging Stations (EVCS) to be minimal power variation at PCC (point of common coupling). Consequently, it demands improved energy storage for optimal placement and energy savings. This paper proposed a MOO (multi-objective optimization) method for reducing energy consumption and time. To achieve the objective optimal location is considered an effective tool for EVCS with coordinated charging. The proposed model incorporates the integration of MATPOWER integrates with a meta-heuristics algorithm for EMS (Energy Management System) in a microgrid. Placement is achieved with the objective of optimal energy saving by means of clustering in EVCS at various nodes of a microgrid at distributed energy sources.

Automated summary

This paper proposes a multi-objective optimization method for reducing energy consumption and time of EV charging stations, integrating energy management system and meta-heuristics algorithm to achieve effective placement in a microgrid, and optimal energy savings through clustering.