a bi-level model for optimal placement and sizing of ev fast charging stations considering traffic and power network interactions

This paper presents a bi-level optimization modelfor the siting and sizing of electric vehicle fast charging stations(fcss), considering the constraints of the power distributionnetwork. in the presented method, queuing theory and a userequilibrium-based traffic assignment model are used todetermine the size of fcss. the upper-level problem aims tomaximize the profit of the fcs owner by determining optimallocations and capacities of fcss. the lower-level problemminimizes the operational cost of the distribution network whileconsidering power flow constraints and ev charging demands.the bi-level model is transformed into a single-levelmathematical program using the karush-kuhn-tucker (kkt)primal-dual optimality conditions of the lower-level problemdue to the linearity of the ll problem. simulation results on theieee 33-bus distribution system and a 25-node transportationnetwork show that two fcss are optimally installed at buses 25and 32 with 9 and 7 chargers, respectively, yielding a daily profitof approximately $6,147 for the investor. sensitivity analysisdemonstrates that higher electricity selling prices lead toincreased profitability and expansion of charginginfrastructure, highlighting the effectiveness of the proposedframework in capturing the economic interaction between thedso and private investors.