Effective Deterministic Methodology for Enhanced Distribution Network Performance and Plug-in Electric Vehicles

The rapid depletion of fossil fuel motivates researchers and policymakers to switch from the internal combustion engine (ICE) plug-in electric vehicles (PEVs). However, power distribution networks are congested, which lowers accommodation PEVs produces higher losses. Therefore, study proposes an effective deterministic methodology maximize percentage loss reduction (%PLR) in radial (RDNs). In first stage, allocated best bus, is chosen based on loading capacity index (LCPLI), profile developed varying states charge (SoC) battery capacities (BCs). second losses minimized PEV integrated with allocation DG units using a recently parallel-operated arithmetic optimization algorithm salp swarm (AOASSA). third charging discharging ratios optimized analytically minimize after planning DGs. outcomes reveal that bus-2 most optimal bus for PEVs, as it has highest level LCPLI, 9.81 33-bus system 28.24 69-bus system. can safely accommodate largest number vehicles, 31,988 92,519 Additionally, AOASSA mechanism leads at least 0.09% 0.25% compared other algorithms have been previously applied systems, respectively. Moreover, ratio IEEE-33-bus network (RDN), %PLR further improved by 3.08%, 4.19%, 2.29% presence one, two three units, IEEE-69-bus RDN, 0.09%, 0.08% discharge two, proposed intends help local companies RDNs.