Comparative Analysis of Optimal Allocation of PV Units Considering Plug-In Hybrid Electric Vehicle Charging Demand in Radial Distribution System
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Abstract
The growing adoption of distributed generators (DGs) and plug-in hybrid electric vehicles (PHEVs) is driving significant changes in the operation of distribution systems. This study aims to optimize the integration of Photovoltaic (PV) distributed generators deployed in radial distribution networks to support load requirements by PHEVs. To achieve this, a optimization approach is applied, focusing on minimizing voltage variations, and reducing energy losses. The impact of PHEV charging demand on distribution system performance is analyzed under peak, off-peak, and stochastic charging conditions. PV unit placement is then optimized using the advanced Electric Eel Foraging Optimization (EEFO) algorithm, which accounts for PHEV demand variability within the distribution network. Standard IEEE 33-bus and IEEE 69-bus test systems are employed to conduct comprehensive case studies, examining the effect of varying numbers of PV units on the system’s performance. Comparative evaluations highlight the EEFO algorithm’s effectiveness in solving the PV allocation problem, outperforming DE, GWO optimization methods.
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