A comparative analysis for impact of distributed generations with electric vehicles planning

Abstract

In the approaching years, the utilization of Distributed Generations (DGs) with Electric Vehicles (EVs) will accelerate. Future issues will be exacerbated by the relationship between the distribution system of DGs solely, DGs with Fuel Cell Electric Vehicle (FCEV), and DGs with Extended Plug-in Hybrid Electric Vehicles (Ex-PHEV). This paper discusses the use of a multi-tasking Genetic Algorithm to optimize DGs with EVs planning in distribution systems for load models for rating and placement determination. From a system perspective, the goal of this research is to reduce total real power loss. The various types of DGs with EVs are taken into account from the standpoint of the analysis. Photovoltaic, diesel engines, synchronous condensers, and doubly-fed induction generators are examples of various types of DGs. In this analysis, EV types such as FCEV and Ex-PHEV are considered. Different forms of constant impedance (Z), constant current (I), and constant power (P) load models are included in DGs with EVs planning for improving system performance indices, such as Light-emitting diode, Laptop charger, Personal computer, Tungsten light, and Vacuum tube. The real power loss index (%ILP), the reactive power loss index (%ILQ), the voltage deviation index (%IVD), the short circuit current reduction (%IC), the active power DGs with EVs penetration (% PPWDGs & EVs), and the reactive power DGs with EVs penetration (%PQWDGs & EVs) are all measured in this paper. On the 37-bus test distribution system, the effectiveness of the listed approach was verified.This article is very much useful for researchers, industrial, scientific persons, and those who are working in the smart grid with DGs and EVs.