PROJECT TITLE :
Expected Cost Minimization of Smart Grids With Plug-In Hybrid Electric Vehicles Using Optimal Distribution Feeder Reconfiguration
Stochastic charging behavior of plug-in hybrid electric vehicles (PHEVs) underneath different charging methods brings new challenges for distribution networks like feeder overloading and loss increase. In this way, the augmented penetration of those vehicles mandates employing new operative tools to inspect their impacts on electrical grids. Therefore, this paper proposes a completely unique optimal stochastic reconfiguration methodology to moderate the charging result of PHEVs by changing the topology of grid using some remote controlled switches. Uncertainties associated with network demand, energy worth, and PHEV charging behavior in several charging frameworks are handled with Monte Carlo simulation and the proposed stochastic drawback is solved with krill herd optimization algorithm. Numerical studies on Tai-power distribution system verify the efficacy of proposed reconfiguration to enhance the system performance considering PHEV charging masses.
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