Empowering Urban Mobility: Revolutionizing Public Transport with Efficient Planning of Electric Taxi Charging Stations Deployment in Power Distribution Networks

With the increasing prevalence of Electric Taxi Public Transport Vehicles (ETPTVs) in urban transportation systems, the integration of Electric Taxi Public Transport Vehicle Charging Stations (ETPTVCS) into Power Distribution Networks (PDNs) has become a significant challenge. The rising demand for ETPTVs, driven by environmental goals and the transition towards cleaner urban mobility, adds new layers of complexity to maintaining the stability, reliability, and efficiency of distribution networks. This paper presents a comprehensive approach that addresses not only the optimal planning and deployment of ETPTVCSswithin PDNs, but also incorporates demand response programs (DRPs) and the Fuzzy Decision-Making Method (FDMM) has been used to select the optimal solution from the set of solutions of multi-objective optimization problems. From a technical standpoint, the study explores key issues such as voltage regulation, network losses, and load balancing, while also focusing on economic objectives like minimizing installation, operational, and charging costs, and improving network efficiency. To manage the complexity of station placement and scheduling, the Frilled Lizard Optimization (FLO) algorithm-a nature-inspired metaheuristic-is employed. The FLO algorithm is particularly effective in handling uncertainties related to fluctuating charging demands and dynamic network conditions. Simulation results confirm the algorithm's capability to enhance network performance, ensure reliable energy delivery, and reduce overall costs. The findings underscore the strategic importance of well-positioned ETPTVCSs, demonstrating that optimal placement can support the growing use of electric taxis while simultaneously improving both the technical and economic performance of PDNs.