Cost-Effective Strategy for the Deployment of Charging Stations for Electric Vehicles Using Flower Pollination Algorithm

Abstract

The adoption of electric vehicles (EVs) is increasingly prevalent due to their advantages such as reduced emissions, lower noise pollution, decreased maintenance requirements, and efficient power consumption. Many modern countries are integrating EVs as part of their initiatives to enhance environmental sustainability and energy efficiency. However, the strategic placement of EV charging stations is crucial as it can impact voltage stability, peak load, power quality, and transformer lifespan within the power system. Thus, optimizing the location and sizing of EV charging stations is essential for cost-effective distribution system planning. This paper presents an approach for determining the optimal placement and sizing of charging stations using the Flower Pollination Algorithm. The proposed method is evaluated on a distribution power system, demonstrating its efficacy in optimizing charging station locations and sizes while minimizing operational costs. The results indicate that the Flower Pollination Algorithm outperforms the Artificial Bee Colony Algorithm in terms of cost efficiency and overall performance.