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Optimal electrical fast charging stations by enhanced descent gradient and Voronoi diagram

handle: 11583/2995891
Abstract In this article, a synergy of Enhanced Heuristic Descent Gradient (EHDG) algorithm and Voronoi diagram is applied for the optimal planning of electrical Fast Charging Stations (FCSs) for electric buses. The proposed novel technique aims at achieving the optimal locations of charging stations based on route distributions, consumption profiles, and operating costs. The Enhanced Descent Gradient is applied to produce the optimal layout that is graphically represented by Voronoi diagram. A real world case study is presented to the bus network in city of Toronto to be replaced with electric buses that need electrical charging stations. The proposed technique is based on two incorporated stages: analyzing and estimating of the energy consumption of the bus network, then optimizing the allocation of charging stations to minimize the energy consumption and operating cost. The proposed technique is verified and compared with a well-established benchmark algorithm, which is particle swarm optimizer.
Electric bus network; Energy consumption; Enhanced descent gradient; Fast charging stations; Operating cost; Optimal planning; Voronoi diagram
Electric bus network; Energy consumption; Enhanced descent gradient; Fast charging stations; Operating cost; Optimal planning; Voronoi diagram
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).38 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
