Affiliations: [a] Department of Power and Control Eng. School of Electrical and Computer Eng. Shiraz University, Shiraz, Iran | [b] Nourabad Mamasani Branch, Islamic Azad University, Nourabad Mamasani, Iran
Abstract: By rapid growth in the technology of the electric vehicles (EVs), the new smart power grids will include millions of these devices in the near future. The high penetration of EVs especially in the form of plug-in hybrid EVs (PHEV) can result in new challenges in the optimal operation and management of the systems. The charging behavior of PHEVs in a typical system is affected by a number of uncertain parameters which makes the overall charging behavior of PHEVs uncertain. Therefore, this paper makes use of a newly introduced smart model for charging demand of PHEVs to assess their effect on the reconfiguration issue as a precious and significant strategy in the smart automated distribution systems (ADS). In this regard, two different charging modes including charging at the public station and in a local residential community are investigated. Also, a sufficient scenario-based stochastic framework is proposed to model the uncertainties associated with the PHEVs on the reconfiguration problem. The proposed stochastic framework employs the roulette wheel mechanism in conjunction with a modified evolutionary-based optimization technique to deal with the targets. The feasibility and effectiveness of the proposed method is investigated on the 69 bus IEEE distribution system.
Keywords: Plug-in Hybrid Electric Vehicles (PHEVs), reconfiguration, uncertainty, stochastic framework, smart automated distribution systems, θ modified cuckoo search algorithm
