Enhancing of Distribution System performance in the Presence of DGs and EVCSs using Evolutionary Optimization Techniques

Abstract

Electric vehicles (EVs) are rapidly penetrating the transportation sector, leading to a sharp increase in electric vehicle charging stations (EVCSs), which significantly affect power distribution networks. Improper placement of EVCSs can cause transformers and feeder overloading, higher energy losses, degraded voltage profiles, and reduced voltage stability. This paper proposes a multi-objective optimization framework for the optimal allocation and sizing of Distributed Generators (DGs) in the presence of EVCSs using the Whale Optimization Algorithm (WOA) and Puma Optimization Algorithm (POA). The objective functions are minimizing real power losses and enhancing the Voltage Stability Index (VSI). The proposed methods are validated on the IEEE 33-bus distribution system. Simulation results show that, compared to the base case with 201.99 kW active losses, minimum voltage 0.913 pu, optimally placed EVCSs with Type-I DGs reduce power losses by 66.8% (POA) and 64.7% (WOA), while improving the minimum voltage to 0.9679 pu and 0.9690 pu, respectively. For Type-II DGs, power losses are reduced by 24.15% (POA) and 25.08% (WOA) with minimum voltages of 0.9371 pu and 0.9264 pu, respectively. The findings confirm that PQ-mode DGs provide the most effective enhancement in reducing losses, improving voltage profiles, and strengthening system stability. The results highlight the superior performance of the proposed optimization techniques in mitigating the adverse impacts of EVCSs on distribution systems.

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