Teaching-Learning Based Optimization Method for PEV Scheduling Incorporating PV Units in a Distribution Power Network

Abstract

Integration a large number of plug in electric vehicles (PEVs) to the grid, results in the bus voltage deviation and active power loss raise tremendously. Further, we face overvoltage and increased grid loss by increasing the number of installed photovoltaics (PVs) on the grid.This paper employs a novel Teaching and Learning Based Optimization (TLBO) approach to mitigate the corresponding serious side effects. In this work, the proposed strategy finds the optimum schedule of PEVs in order to improve the system voltage profile and reduce active power losses, while the PV units are supplying the system. To investigate the efficiency, a TLBO-based proposed method is applied to a typical standard IEEE distribution network.By looking at the TLBO simulation results, PEVs have been charged during the day hours and discharged at the peak hours. Discharging PEVs at peak hours causes less active power losses in the grid. By discharging PEVs at these hours some part of load demands are provided locally through the PEVs. Therefore, there is no need to increase power flow from the upper network.Finally, TLBO optimization method proved successful function to alleviate the PEVs penetration impact in cooperation of PV generation units.